What Is a Next-Gen WAF and Why Does It Matter for DevOps?

Traditional Web Application Firewalls (WAFs) were designed primarily as perimeter defenses—statically configured rule sets that inspect HTTP traffic and block suspicious requests. While effective in narrow scenarios, legacy WAFs are often criticized for being opaque “black boxes” that block requests without surfacing contextual information about why a request was flagged. This lack of visibility is a poor fit for modern DevOps practices, where speed, feedback loops, and observability are foundational principles.

A next-generation WAF addresses these shortcomings by operating as an integrated security data layer rather than a standalone gate. Instead of just blocking traffic, it collects Layer 7 (application-layer) telemetry, exposes that data through APIs and integrations, and feeds actionable intelligence back into the tools that development, security, and operations teams already use.

Security Visibility at Every Stage of the DevOps Lifecycle

The DevOps lifecycle is typically broken into continuous stages: Plan, Code, Build, Test, Release, Deploy, Operate, and Monitor. A next-gen WAF can contribute meaningful security signal at each of these stages—not just at the perimeter in production. The sections below outline where and how that value is delivered.

Code: Surface Real-World Vulnerabilities for Developers

Static analysis and code review catch many issues before deployment, but they cannot fully replicate the conditions of production traffic. A next-gen WAF observes how attackers actually attempt to exploit your running application and can surface patterns that indicate high-value security bugs—such as injection attempts repeatedly targeting a specific endpoint. This gives developers a prioritized, evidence-based list of vulnerabilities to address in the next sprint rather than relying solely on theoretical threat models.

Build: Visibility Into Cloud-Native Attack Surfaces

Modern cloud-native applications—deployed across microservices, containers, and managed platforms—introduce web-layer attack surfaces that traditional network controls do not adequately cover. Cloud providers offer robust infrastructure security, but application-layer visibility is typically the team’s own responsibility. A next-gen WAF deployed alongside cloud-native workloads provides that missing layer of context, enabling security and platform teams to understand the real-world threat landscape their architecture faces before a vulnerability becomes an incident.

Release: Protection Without Code Changes on Every Deployment

DevOps teams release frequently—often multiple times per day. Requiring a manual security review or configuration change on every release is a bottleneck that directly conflicts with continuous delivery. A next-gen WAF solves this by decoupling application security from the release artifact itself. Whether deployed as a sidecar agent, a reverse proxy, or a cloud-delivered WAF service, protection travels with the infrastructure configuration rather than the application code. Teams can release confidently knowing their WAF policy follows the deployment automatically.

Operate: Production Monitoring on Key Application Metrics

Operations teams are responsible for availability, performance, and reliability. Security events—such as a volumetric request flood or a spike in invalid authentication attempts—directly threaten these objectives. A next-gen WAF contributes to operational observability by exposing security-relevant metrics alongside standard application performance indicators. When operations teams can see attack patterns and application health in a unified view, they can respond faster and make more informed decisions about scaling, rate-limiting, or incident escalation.

Monitor: Real-Time Alerting and Integration With Your Toolchain

After deployment, continuous monitoring is essential. A next-gen WAF integrates with the broader security and DevOps toolchain—sending alerts and telemetry to SIEM platforms, incident management systems, messaging tools like Slack or PagerDuty, and monitoring dashboards—so that security signals appear in the same places where teams are already working. This removes the need to context-switch into a separate security console to understand what is happening in production.

Next-Gen WAF as a Force Multiplier for Security and DevOps Teams

Security and DevOps teams are almost universally resource-constrained. A next-gen WAF can operate in two complementary modes that reflect different team maturity levels:

• Automated protection mode: Teams that need immediate coverage without deep customization can rely on the WAF’s automated detection and blocking capabilities. This allows smaller teams to maintain a strong security posture without dedicating significant engineering time to rule tuning.
• Intelligence and KPI mode: More mature teams can treat the WAF as a security data source, using its management console and API to extract KPIs, analyze attacker behavior, and feed that intelligence back into their development and security processes. This produces compounding improvements in application security over time.

Key Capabilities to Look for in a Next-Gen WAF

When evaluating next-gen WAF solutions for a DevOps environment, prioritize the following capabilities:

• API-first architecture: Security data should be accessible programmatically so it can be integrated into pipelines, dashboards, and automation workflows.
• Flexible deployment models: Support for agent-based deployment, reverse proxy, and cloud-delivered WAF ensures the solution fits different infrastructure topologies.
• Contextual blocking decisions: Every block or flag should include enough context for a developer or analyst to understand and act on the decision.
• Native integrations with DevOps tooling: Pre-built integrations with CI/CD platforms, monitoring systems, SIEM tools, and communication platforms reduce integration effort.
• Low false-positive rate: In a continuous delivery environment, a WAF that generates excessive false positives will be bypassed or disabled. Accuracy is a prerequisite for adoption.
• Support for modern traffic patterns: The solution should handle REST APIs, GraphQL, gRPC, and other contemporary application protocols in addition to traditional web traffic.

Summary

A next-generation WAF is not simply a more powerful version of a legacy firewall. When properly integrated into the DevOps lifecycle, it becomes a source of continuous security intelligence that informs coding decisions, validates builds, protects releases, supports operations, and feeds monitoring workflows. For teams practicing continuous delivery, the ability to decouple application security from the release artifact—while maintaining full observability of the production threat landscape—is a meaningful operational advantage.

If you are evaluating next-gen WAF options for your organization, focus on solutions that expose their data through open APIs, integrate with the tools your teams already use, and are designed from the ground up for cloud-native and containerized environments.

DevOps is helping organizations develop software faster. DevOps is a software development approach that utilizes the Agile methodology to integrate and streamline the development and operations process. The result is a faster and more efficient development process. 

The downside of DevOps is that the fast pace it promotes doesn’t cover security. The solution is to include security protocols and practices across the DevOps pipeline. If you’re interested in adopting the DevOps approach, read on to learn about the challenges that await you, and how to overcome them.

What Makes DevOps Security Different from Traditional Security?

Before the introduction of the DevOps methodology, the development process followed a “waterfall” model. The waterfall model creates a sequential system, divided into phases. The output of one phase forms the input of the next. Teams that follow a traditional waterfall model typically work independently from each other. The waterfall model often introduces security testing only during the last stages of the process. This often results in several changes until the product complies with the recommendations of the security team. The endless changes and patches make the development process longer and more expensive.

Implementing a DevOps model requires collaboration between teams across the software development lifecycle. This approach makes changes part of the development process, which helps produce a secure product faster.

Automation is also a critical part of the DevOps process, through the use of Continuous Integration/Continuous Deployment (CI/CD). Continuous testing forms part of the CI/CD model, implementing tests at set intervals during the pipeline.

5 DevOps Security Challenges

DevOps has become the standard of software development in the past years. Introducing DevOps security presents its own set of challenges, as explained below.

1. Faster development processThe fast pace of a DevOps process can lead to an increase in coding mistakes, which could result in undetected bugs and errors. Attackers look for coding mistakes they can exploit to gain access to digital assets.
2. Serverless computingThe term refers to a cloud computing model where the cloud provider manages the infrastructure resources. The cloud platform also manages the security of the applications hosted in it. Migrating to a serverless computing environment presents some challenges for organizations. When migrating applications or data to the cloud, you can’t always be sure how the platform’s security work until deployment. Another concern is the exposure of sensitive data during migration.
3. Collaboration challengesDevOps requires the collaboration of two different teams: development and operations. Considering that they are used to working in a siloed way, unifying their processes can be challenging. Undefined roles and policies can lead to gaps in security.
4. The interconnectedness of the DevOps processOne of the characteristics of DevOps is that requires the constant collaboration of the teams. This highly interconnected environment allows for the exchange of privileged information. Teams share account credentials, tokens, and SSH keys. Systems such as applications, containers, and microservices also share passwords and tokens. A common pitfall of DevOps environments is poor secrets management. This provides a path for attackers to disrupt operations, and steal information.
5. Implementing security in CI/CDIn a traditional siloed development environment, security has always come at the end of the pipeline. Typically, a security team performs security testing after the development stage, before sending the application into production.Integrating security into the pipeline can be challenging. By nature, security teams tend to take their time to secure every part of the code, which in turn clashes with the fast pace of the DevOps process. Security risks can arise during the integration stage until the DevOps model is fully implemented and running.

8 Security Tips for DevOps

Ensuring the security of your application development can be a daunting task. The following tips can help you avoid security issues and are a good start to revise your security practices.

1. Assign security responsibility to one person from your DevOps teamHaving a single person in charge of the security process can ensure that teams don’t overlook security protocols. You can create a new role, or add to the existing functions of a member of the security team.
2. Identify compliance requirements beforehandPlanning the security policy around compliance requirements saves a lot of time and headaches. You can also automate compliance reports, for maximized efficiency. For example, you can set the audit logs to upload in real-time to a read-only folder shared with the auditor. This can help you avoid the last-minute log search when it’s time for the audit.
3. Implement threat modelingYou should visualize the entire pipeline process and how it can be attacked. Identify the weak spots, both for the product and the CI/CD pipeline. Then set up your security accordingly.
4. Verify cloud infrastructureA best practice is to verify the compatibility of cloud security with your application requirements. This will help you ensure that your internal security practices align with the cloud provider’s. This can help you enhance your security posture.
5. Include security early in the life cycleIncluding security tests early in the software development lifecycle can minimize the number of revisions and patches. This helps you to identify code vulnerabilities as soon as they appear.
6. Automate as much as possibleDevOps typically promotes the use of automation tools to increase consistency. Automating security processes reduces the chances of human error. Here are some security tests you can use:
   • Static Application Security Testing (SAST)—evaluates the source code, identifying vulnerabilities.
   • Dynamic Application Security Testing (DAST)—evaluates the applications while running, and identifies compliance and security problems.
   • Runtime Application Self Protection (RASP)—analyzes traffic and user behavior while the application is running. These tests can send alerts and respond automatically.
7. Implement secure coding practiceOne of the core values of DevOps is to follow secure coding practices. Enforcing secure coding policies is especially important when using open-source software. Some tips for secure coding include:
   • Validate input from external sources—input validation tests input.This practice can prevent the majority of source code vulnerabilities. You should use a whitelist approach, meaning only passing data “on the list”.
   • Beware of language flaws—programming languages often have vulnerabilities that can be exploited. For instance, some are vulnerable to buffer overflow while others have flaws that make them open to attacks by code injection.
   • Use secure encryption—using existing libraries can help you ensure the safety of the encryption source. In addition, you can add the encryption faster, as you don’t have to actually create it.
   • Apply the principle of least privilege—this principle implies that every user has the minimum required permissions to complete the job.
8. Leverage containerizationDeveloping with containers improves collaboration between teams, by letting them share their software with ease. The individuality of container building blocks enables them to be easily isolated, thus supporting security for applications and microservices.

The Bottom Line

Security is not a thing worth procrastinating on, as the consequences of a security incident can be disastrous. When implementing a DevOps model, it makes sense to include security practices and protocols from the start, to avoid stalling the development pipeline with endless changes and patches. You can integrate security testing and controls from the beginning, making changes as you go. This will result in secure and fast product delivery. Use the tips in this article to get started, and make your applications are as secure as possible.

Data Theorem, Inc. a provider of modern application security, introduced a new SPA security service that delivers automated discovery and continuous dynamic runtime vulnerability inspection of modern web single-page applications (SPAs). Purpose-built for SPAs, the new service is differentiated in its runtime security analysis that supports both GraphQL and REST API services, the popular services for SPAs that dynamically deliver a faster and richer web user experience.

With DevOps teams rapidly building web SPAs, security and IT teams using traditional web app scanners lack the ability to gather application insights and inspect for security vulnerabilities on these new modern web apps. Now with this new offering from Data Theorem, for the first time users can fully discover and inspect vulnerabilities with dynamic runtime analysis for both GraphQL and REST API services.

Tech News: Dremio Releases Data Lake Engines for AWS, Azure, and Hybrid Cloud; Enhances Performance on Data Lake Storage

“SPA security is the new frontier for modern web application security, and like mobile it is tightly coupled to the explosion and growth of GraphQL and API backend services,” said Doug Cahill, senior analyst and group practice director of cybersecurity for ESG. “To best protect these services from attack, organizations need a solution that delivers both continuous security vulnerability inspection and runtime analysis that supports both GraphQL and REST API services.”

Businesses today delivering modern web applications build SPAs to deliver a richer and faster user experience that is similar to what they deliver with their mobile apps. Similar to mobile app protection, traditional web app scanners lack the ability to add security insights to SPAs because of the dynamic nature of the SPA JavaScript architecture. In addition, GraphQL adds a new attack surface due to the enhanced flexibility it provides, making it difficult to protect against malicious queries. These attack queries could lead to denial of service attacks, or unauthorized access to private data.

“Growth of SPA deployment and usage increases every year because organizations want their web experience to be as good as their mobile app experience,” said Doug Dooley, Data Theorem COO. “But security tools have not kept up with this modern software development trend. With our first web app security offering launching today, Data Theorem is leaping ahead of the competitive landscape to now serve users’ complex security needs beyond API and mobile. We were already leading in runtime analysis for mobile apps, and now we offer similar depth of runtime analysis to protect these popular SPAs.”

Tech News: Oracle Expands its Security Portfolio with New Cloud Services; Unveils New Innovations for its Data Management Portfolio

Today’s SPA security solution is offered as a component of Data Theorem’s API Discover and API Inspect, which together address security concerns such as Shadow APIs, Serverless Applications, and API Gateway cross-check validation by conducting continuous security assessments on API authentication, authorization, encryption, availability, serverless functions, and policy compliance.

The API security solutions support Amazon Web Services, Google Cloud, and Microsoft Azure to discover modern APIs and to enumerate the specification using standards such as Swagger and Open API 3.0.

“Organizations are increasingly adopting DevOps environments in hopes of achieving transformative velocity and innovation. But like any new business initiative, this comes with challenges — and in the case of DevOps, it’s often around culture and areas of responsibility.”

Elizabeth Lawler, VP of DevOps Security, CyberArk

Even problems that look technical on the surface are usually rooted in people. Security is a prime example: it is as much a matter of culture and ownership as it is a technology problem. And even high-functioning DevOps teams struggle to make security — and security teams — genuinely integral to the development process.

This friction is both a driving force behind the DevSecOps movement and, paradoxically, a source of resistance to it. Below, we identify the three most common cultural roadblocks and then share five concrete strategies from practitioners for overcoming them.

The 3 Cultural Challenges Blocking DevSecOps Adoption

Challenge 1: Security Is Still Treated as Something That Happens “Later”

“The biggest change in mindset necessary to create a mature DevSecOps practice is to understand that security cannot be done as an afterthought. Rather, it requires the attitude that it is built into the continuous delivery pipeline.”

Premand Chandrasekaran, VP of Software Engineering, Barclaycard

The traditional model treated security as a post-mortem: infrastructure was built first, then a security audit was bolted on at the end. That model breaks down completely in modern cloud-native environments, where entire infrastructure stacks can be spun up and torn down in hours.

“Today, DevSecOps professionals are tasked with baking security into architecture as they build, and into the system as it’s deployed.”

Tim Jefferson, VP of Public Cloud, Barracuda Networks

When environments are ephemeral, a security review scheduled for “after deployment” may never happen at all. Shifting security left — earlier in the pipeline — is not optional; it is a structural necessity.

Challenge 2: An Us-Versus-Them Mindset Between Dev and Security Teams

The tension between developers and security practitioners is not new. The root cause, according to Meera Rao, Senior Principal Consultant at Synopsys Software Integrity Group, is that each team operates with its own roadmap, its own priorities, and — critically — completely different incentives.

“Security teams have long thought that developers were not interested in security. Along those same lines, security teams also thought developers believed that security wasn’t their responsibility.”

Franklin Mosely, Senior Application Security Engineer, PagerDuty

Neither assumption is necessarily true. But the divide persists even in relatively mature DevOps shops. As long as security remains a separate entity — organizationally siloed from development and operations — the us-versus-them dynamic is structurally reinforced, regardless of individual goodwill.

Challenge 3: The Belief That Security Hinders Innovation and Velocity

“We are all very used to this romantic image of the resourceful developer who codes swiftly and slickly — but not necessarily securely, because security has been viewed as the antithesis of function. Thus, a big cultural challenge for DevSecOps is to instill order in the face of a legacy of chaos, and somehow accomplish this without hindering innovation.”

Robert Hawk, Privacy and Security Lead, xMatters

Years of bolt-on, last-minute security reviews have created a deep-seated perception that security teams exist to slow things down. As pressure for faster, more frequent releases intensifies, this perception hardens into outright resistance. The irony is that this cultural challenge is precisely what DevSecOps is designed to solve — yet it is also one of the primary reasons organizations resist adopting it.

“Speed, velocity, and resiliency do not need to be sacrificed in order to be secure and have more stakeholders at the table.”

Elizabeth Lawler, CyberArk

Note that all three challenges are interconnected. Treating security as an afterthought breeds siloed teams, and siloed teams reinforce the belief that security blocks progress. They tend to compound each other.

5 Strategies for Building a DevSecOps Culture

Overcoming these cultural obstacles requires movement on two fronts simultaneously: organizational alignment and technical strategy. The following five approaches are drawn directly from practitioners who have implemented them.

1. Have People Walk in Each Other’s Shoes

Ignorance breeds resentment. When developers do not understand what security teams deal with, and security teams do not understand how software actually gets built, mistrust fills the gap. Many DevOps teams already create cross-functional empathy by rotating developers through on-call duties alongside operations staff. The same principle applies to security.

“The security professional needs to walk in the developer’s shoes and learn how software is made and the issues that are faced. It’s best to work with developers to come up with solutions that allow them to do the right thing when it comes to security.”

Franklin Mosely, PagerDuty

The reverse is equally important. Developers need to engage with security colleagues to understand best practices for securing modern infrastructure and applications. As Lawler notes, security must be built into development processes early — and that can only happen when both teams actively collaborate rather than lobbing requirements over the wall at each other.

2. Provide Real Learning and Training Opportunities

Many DevSecOps cultural problems stem from a straightforward lack of knowledge. A developer who has never been held accountable for the security of their code has had little incentive to learn secure coding practices. A siloed security team may have little idea how the software they audit actually gets built.

“Most developers aren’t trained in secure coding best practices. This creates a situation where engineers are not implementing security thinking and awareness into design, coding, and testing.”

Franklin Mosely, PagerDuty

Training takes many forms. Formal secure coding curricula, regularly scheduled security audits, and unannounced audits all create learning moments. Chandrasekaran of Barclaycard also recommends adversarial exercises such as “hack days” or capture-the-flag (CTF) events, where cross-functional teams actively find and exploit vulnerabilities in a controlled setting. These exercises build empathy and practical knowledge simultaneously.

3. Embed Security Professionals on Development Teams

The fastest way to break down a silo is to physically remove it. Embedding a security engineer directly on a development or DevOps team gives security a literal seat at the table from day one of a sprint, rather than a seat at a review meeting after the code ships.

“IT leaders should create avenues for security experts to be involved in designing, developing, and testing code. One way is to embed security team members directly into development teams.”

Kiran Chitturi, CTO Architect, Sungard Availability Services

PagerDuty has used this approach in practice. According to Mosely, embedding a security engineer on a product team allowed that engineer to learn the team’s tools and processes, while the development team gained direct exposure to security best practices. The result: the security team became better at adding value without blocking delivery, and the product team became more conscious of protecting customer data.

4. Launch a Security Champion Program

Not every team can spare a dedicated security engineer. A security champion program is a practical alternative. A security champion is typically a developer or DevOps practitioner — not necessarily a trained security specialist — who volunteers to develop deeper security knowledge and acts as a liaison between their team and the security organization.

“Establishing a training and security champions program allows members of development teams to learn and volunteer to build software security skills and awareness through mentoring, training, and working closely with the application security teams. These security champions form the front line when it comes to guiding development teams on application security and bridge the gap that exists between DevOps and security teams.”

Meera Rao, Synopsys Software Integrity Group

For this model to work, the role needs to come with real incentives — recognition, career development opportunities, or dedicated time to pursue security learning — not just additional responsibility on top of an existing workload.

5. Embrace Automation — and Use It to Win Over Skeptics

One underappreciated reason cultural resistance to DevSecOps exists is that, at first glance, it looks like net-new work nobody asked for. Asking developers to “just do more security” without changing anything else is a reliable way to generate resentment. Automation is the answer to this objection.

Integrating automated static analysis, dynamic scanning, and runtime security checks directly into the CI/CD pipeline means security gates run without anyone having to manually trigger them. Security becomes part of the pipeline rather than an interruption to it.

“A lot of verification needs to be automated through the use of a combination of static, runtime, and chaos engineering tools to reduce the amount of grunt effort involved.”

Premand Chandrasekaran, Barclaycard

Automation also relieves the anxiety that developers will need to become security experts themselves. The goal is not for every engineer to define security policy — it is for security policies, defined by experts, to be encoded into automated tooling that everyone follows.

“It’s all about automation. The developer, the tester, the designer, the operations person — all need to be able to have responsibility for following security-relevant processes, not defining them. Once you have the processes in place, you can manage by exception: instead of trying to check that people do the right thing all of the time, spot when they do the wrong thing and sort it out from there.”

Mike Bursell, Chief Security Architect, Red Hat

The Bottom Line

DevSecOps is not primarily a tooling problem — it is a people and process problem. The three cultural obstacles outlined here (security as afterthought, organizational silos, and the speed-versus-security false dilemma) are deeply interrelated and tend to reinforce each other. Addressing them requires a combination of structural changes — embedding security into teams, launching champion programs, building training into the workflow — and technical enablers like pipeline automation that reduce manual toil.

The organizations making the most progress on DevSecOps are not the ones with the most sophisticated security tooling. They are the ones that have made security everyone’s shared responsibility, supported by automation that makes doing the right thing the path of least resistance.

This article draws on quotes originally published by enterprisersproject.com.

The Speed-Security Tension in Modern Software Delivery

The always-on digital economy is pushing organisations to ship application updates on a near-continuous basis. Customer expectations, competitive pressure, and the rapid pace of feature development mean that release cycles have compressed dramatically. In this environment, security is one of the first disciplines to be deprioritised when a deadline looms.

The consequences of that trade-off are well documented. High-profile vulnerabilities such as the Meltdown and Spectre CPU flaws, and the global spread of the WannaCry ransomware, demonstrated how technical debt in security can translate into catastrophic real-world damage. These incidents serve as a consistent reminder that speed without security is not a sustainable competitive advantage.

What DevSecOps Actually Means

DevSecOps is the practice of integrating security concerns directly into the software development lifecycle, rather than treating security as a gate at the end of the pipeline. The goal is to make security a shared responsibility across development, security, and operations teams from the very first commit.

In practical terms, DevSecOps means:

• Running static application security testing (SAST) and dynamic application security testing (DAST) as part of the CI/CD pipeline.
• Embedding security engineers or security champions within development squads.
• Using infrastructure-as-code scanning tools to catch misconfigured cloud resources before deployment.
• Automating dependency and software composition analysis to detect vulnerable third-party libraries.
• Treating security findings as bugs that block releases, not as optional post-release improvements.

When security checks are automated and integrated into existing developer workflows—pull requests, code reviews, deployment pipelines—they add far less friction than traditional end-of-cycle penetration testing or compliance audits.

Collaboration: Breaking Down the Security Silo

One of the most significant cultural shifts DevSecOps demands is genuine collaboration between teams that have historically operated in isolation. Security teams and development teams often have conflicting incentives: developers are measured on feature velocity, while security teams are measured on risk reduction. Those metrics can pull in opposite directions.

Bringing security stakeholders into sprint planning, architecture reviews, and threat modelling sessions—rather than only into incident response—resolves much of this tension early. When a security engineer is present at the design phase, potential attack vectors can be identified and mitigated in the architecture itself, rather than patched awkwardly after the fact.

Key collaboration practices that support this include:

• Threat modelling at design time: Reviewing new features for potential attack surfaces before a single line of code is written.
• Security champions programmes: Training a volunteer developer in each squad to act as a first line of security review.
• Shared definition of done: Including security acceptance criteria alongside functional requirements in user stories.
• Joint retrospectives: Reviewing security incidents and near-misses together so that both teams learn from the same event.

Diversity of background and perspective within these cross-functional teams also matters. Engineers who have worked in operations, security research, or regulated industries bring threat awareness that pure application developers may lack. Cultivating that diversity is not just a cultural aspiration—it is an engineering advantage.

Security as a Continuous Commitment, Not a One-Time Project

Embedding security into a development process is not a migration that has a completion date. The threat landscape changes continuously: new vulnerability classes emerge, dependencies release patches, compliance requirements evolve, and attacker techniques become more sophisticated. DevSecOps must therefore be treated as an ongoing operational discipline rather than a one-off initiative.

Practical ways to maintain that ongoing commitment include:

• Continuous developer security training: Regular, short security awareness sessions focused on practical coding patterns—SQL injection prevention, input validation, secrets management—rather than annual compliance tick-boxes.
• Automated dependency monitoring: Tools that alert teams when a library they use publishes a security advisory, integrated directly into issue trackers.
• Regular attack surface reviews: Periodic reassessment of exposed APIs, authentication flows, and third-party integrations as the application evolves.
• Partnerships and tooling investment: Evaluating and adopting tooling for application security testing, secrets scanning, and release automation as the market matures.

Measuring the Effectiveness of DevSecOps

Like any engineering practice, DevSecOps needs measurable outcomes to improve over time. Without baselines, teams cannot determine whether their security investment is paying off or where bottlenecks are forming. Useful metrics to track include:

• Mean time to remediate (MTTR) vulnerabilities: How long it takes from vulnerability discovery to a deployed fix.
• Vulnerability escape rate: The proportion of vulnerabilities first found in production versus found earlier in the pipeline.
• Number of critical findings per release: A declining trend indicates that security is being addressed earlier in development.
• Time to deployment: To verify that security integration is not significantly degrading release velocity.
• Security debt backlog size: Tracking open security findings over time to ensure they are being resolved rather than accumulating.

Establishing a baseline before making process changes is essential. Without a starting point, it is impossible to demonstrate improvement to engineering leadership or to justify continued investment in security tooling and training.

The Business Case for Shifting Security Left

Security vulnerabilities are significantly cheaper to fix when caught during development than when discovered after release. Fixing a flaw identified during code review typically requires a developer to spend an hour addressing the issue. Fixing the same flaw after a production incident can involve incident response teams, customer notification, regulatory reporting, and reputational recovery—costs that dwarf the original engineering effort.

DevSecOps is therefore not simply a risk-reduction strategy; it is a cost-reduction strategy. Organisations that invest in automating security checks earlier in the pipeline and training developers to write more secure code by default reduce the volume and severity of late-stage security findings. The result is faster, cheaper, and more predictable software delivery.

Getting Started

For teams that are not yet practising DevSecOps, the most effective starting point is usually not a comprehensive tooling overhaul but a focused cultural change:

1. Identify one or two security checks—such as secrets scanning or dependency vulnerability scanning—that can be added to the existing CI pipeline with minimal disruption.
2. Nominate a security champion in each development squad and give them time and resources to develop that expertise.
3. Schedule a threat modelling session for the next major feature or architectural change, with both developers and a security engineer in the room.
4. Define three to five metrics to track from day one so that progress can be demonstrated over the following quarters.

These incremental steps build the habits, relationships, and tooling familiarity that make DevSecOps sustainable at scale. Security does not need to compromise agility—when integrated thoughtfully, it becomes part of what agility means.

The answer is not to slow developers down, nor to bolt security on at the end of the pipeline. It is to integrate security into every stage of the software development lifecycle—an approach known as DevSecOps. Getting there requires deliberate cultural and organisational change. Three practical strategies can help.

Why the Developer–Security Divide Persists

Different cultures, priorities, and toolchains keep development and security teams apart. Developers are typically rewarded for shipping features quickly; security teams are rewarded for preventing incidents. These incentives are not naturally aligned, and without deliberate effort to reconcile them, the gap widens over time.

Closing that gap requires action on three fronts: trust, accountability, and cooperation.

1. Develop Trust

Trust is the foundation on which any DevSecOps programme must be built. Security professionals who approach development teams as a compliance police force will meet resistance. A more effective starting point is empathy: understanding what motivates developers and finding ways to align security with those motivations.

Most developers are energised by learning new technologies and solving technically interesting problems. Security is rarely perceived as cutting-edge, and that perception is a barrier worth addressing directly. One effective approach is a Security Champions programme: identify a small cohort of respected senior engineers who are willing to engage with security topics, involve them in co-developing security best practices, and then recognise and reward them publicly when those practices are followed.

The mechanics of this approach typically follow three steps:

1. Identify motivated senior architects or engineers with credibility among the wider development team.
2. Engage that group to co-author security guidelines, so the guidelines reflect real-world development constraints.
3. Leverage those respected peers to promote and model secure practices across the organisation.

Shifting the security team’s posture from enforcement to enablement is what earns the development team’s trust and respect over time.

2. Create Accountability

In traditional software delivery, security responsibility was siloed: the security team owned security, full stop. In a DevSecOps model, developers share that ownership—just as they have come to own code quality, test coverage, and deployment reliability.

Building that sense of ownership rarely happens through policy alone. Practical demonstrations are more effective. Consider running joint sessions where both development and security engineers examine simple, real-world exploits against internal or staging applications—for example, demonstrating how an unvalidated input field could be abused, or how a misconfigured access control rule could expose data. These sessions do not need to be adversarial; framed as shared learning, they open both teams’ eyes to the real-world consequences of security oversights.

Key outcomes of this approach include:

• Developers gain concrete understanding of why security controls exist, not just what they are.
• Security engineers gain insight into the constraints and trade-offs developers face.
• Both teams develop a shared vocabulary and a shared stake in the outcome.

3. Promote Cooperation Through Embedding

Application security teams are typically small relative to the number of development projects they must support. The common model—assigning a security reviewer to audit work at specific checkpoints—creates a bottleneck and breeds resentment on both sides. Security engineers feel ignored; developers feel ambushed by late-stage feedback they cannot easily act on.

An alternative is to embed security engineers directly into development teams, at least for the organisation’s highest-priority projects. Rather than acting as external auditors, embedded security engineers participate in sprint planning, architecture reviews, and pull-request discussions. The goal is to build a replicable DevSecOps blueprint within a controlled set of projects that can later be scaled across the portfolio.

When security professionals are embedded this way, they are able to:

• Participate in daily development processes and ceremonies rather than reviewing output after the fact.
• Raise security concerns at the point in the development cycle when they are cheapest to fix.
• Build genuine understanding of the time, technology, and business constraints the development team operates under.
• Communicate security requirements with greater credibility because they have earned it through collaboration.

For the model to work at scale, the practices established in embedded pilots must be documented clearly enough that other teams can adopt them without requiring a dedicated embedded security resource on every project.

Putting It All Together

None of these three strategies delivers results overnight. Trust takes time to build. Accountability requires consistent reinforcement. Cooperation depends on structural changes that may be politically difficult in larger organisations. Positive recognition of progress—from leadership as well as peers—matters throughout the journey.

What organisations gain from the effort is substantial: a development pipeline where security is a first-class concern rather than a last-minute check, and a culture where developers and security engineers see themselves as partners working toward the same goal—software that ships fast and ships securely.

Building a DevSecOps culture is ultimately about changing how people work together, not just which tools they use. Get the people side right, and the tooling decisions become significantly easier.

Why Traditional AppSec Fails in a DevOps World

Traditional application security was designed around a clear perimeter: harden the boundary, scan before release, and trust what is inside the wall. That model breaks down in modern software delivery. Continuous integration and continuous delivery (CI/CD), containerisation, cloud-native architectures, and heavy reliance on open source components all dissolve the concept of a stable perimeter. Worse, they accelerate the pace at which code moves from a developer’s laptop to production — often in hours rather than months.

The core tension is straightforward: DevOps teams prize speed and agility. Security gates that halt pipelines or demand lengthy manual reviews are simply skipped, worked around, or deprioritised. The only sustainable answer is to integrate security directly into the DevOps process itself rather than bolting it on at the end.

Key Application Security Challenges as DevOps Matures

According to Tim Mackey, the biggest security challenge in a DevOps environment is developing a clear picture of your overall information flow. That means answering three questions continuously:

• What data moves through your system, and where does it go? Understanding data flow is a prerequisite for identifying what needs protecting and from whom.
• What are the actual security risks at each stage? Risk profiles differ between development, staging, and production environments, and between in-house code and third-party or open source components.
• What is the highest-priority problem right now? Not every vulnerability requires immediate action. Triage based on exploitability, data sensitivity, and regulatory exposure is essential.

Mackey also highlighted that regulations such as GDPR raise the stakes for security failures. A data breach is no longer just a reputational event — it carries direct regulatory and financial consequences, which changes how organisations should weigh the cost of fixing a known vulnerability against the risk of leaving it unaddressed.

Why Building AppSec Into DevOps Matters

When security is not embedded in the DevOps workflow, teams discover vulnerabilities late — often after a component with a known flaw has been deployed to dozens of environments or integrated into a customer-facing product. The later a vulnerability is found, the more expensive it is to remediate: code must be traced back through builds, containers must be re-imaged, and dependent services must be re-tested.

By contrast, integrating security tooling directly into CI/CD pipelines — through software composition analysis (SCA) for open source dependencies, static analysis for in-house code, and container image scanning — surfaces issues at the point where they are cheapest to fix: during development. Teams get actionable feedback without leaving their existing toolchain, and security becomes a quality gate rather than a separate process.

Open Source Risk: Three Trends from the Black Duck Report

Mackey referenced findings from a Black Duck report (released in the months prior to DevOpsCon 2018) that identified three dominant trends in how organisations interact with open source software:

1. Open source is the default. The overwhelming majority of commercial applications contain a significant proportion of open source code. This is not a niche practice — it is how modern software is built.
2. Security engagement with open source communities is lagging. Organisations consume open source components at scale but rarely participate in the communities that maintain them. They receive the benefits but contribute little to the security health of those projects.
3. Open source licence compliance is becoming a competitive and legal concern. Organisations are becoming more aggressive about auditing which licences govern the components they ship, particularly as legal teams and regulators pay closer attention.

The headline takeaway Mackey drew from these trends: organisations need to be not just consumers of open source, but active participants in the communities whose components underpin their products.

Should You Stop Using Open Source When Flaws Are Found?

A common instinct when a vulnerability is discovered in an open source component is to rip it out and replace it with an alternative. Mackey pushed back on this reaction. In practice, the replacement is often a fork of the same underlying codebase — carrying the same history, the same architectural decisions, and potentially the same flaws. Switching libraries is not the same as eliminating risk.

The more productive response is to:

• Report the vulnerability to the project maintainers and, where relevant, to a vulnerability database such as the National Vulnerability Database (NVD).
• Trace where your organisation obtained the component — directly from the upstream project, from a package mirror, or via a vendor — so that you can monitor when a patched version becomes available.
• Engage with the upstream community rather than treating the project as a black box. Organisations that contribute to open source security reviews, fund maintainers, or submit fixes directly strengthen the ecosystem that their own products depend on.

“Through the community engagement, we all win.”

Tim Mackey, Technical Evangelist, Black Duck by Synopsys — DevOpsCon 2018

Container Security: Immutability, Ephemerality, and Disclosure

In his DevOpsCon 2018 session, Mackey addressed the security characteristics of containers specifically. Two properties define the container model and directly affect how security must be applied:

• Immutability. Containers are built once from an image and run as many identical instances as needed. You do not patch a running container in place — you rebuild the image and redeploy. This is a security advantage when enforced correctly, but it means that vulnerable base images propagate into every instance until the image itself is updated.
• Ephemerality. A container should live only as long as it is needed. Orchestration systems may terminate containers without warning. Security controls that assume persistent processes or file systems do not translate cleanly to containerised workloads.

Mackey predicted that the rate of public security disclosures would continue to rise — a trend that has proved accurate in subsequent years as the attack surface of modern applications has expanded. He also highlighted that web service APIs introduce distinct risk profiles that teams need to account for, including:

• Disruption or discontinuity of service from a third-party API provider
• Loss of intellectual property through unintended data exposure
• Data breaches via poorly secured API endpoints
• Unintended reliance on unreliable or unmaintained external services

Not every external API or service can be trusted implicitly. Teams should treat third-party service dependencies with the same scrutiny they apply to open source library dependencies.

The Researcher Mindset: Report What You Find

Mackey closed his session with a call to action that reframes how engineers should think about their role. Every developer and operator who interacts with open source components is, in a meaningful sense, a security researcher. When you encounter unexpected behaviour, an undocumented API response, or a potential flaw in a library you depend on, you are in a position to act on that information in a way that benefits the entire community.

Responsible disclosure — reporting findings to maintainers, coordinating with security teams, and contributing to public vulnerability databases — is not an activity reserved for dedicated security professionals. It is a practice that any engineer can and should participate in. The cumulative effect of many teams reporting and engaging is a measurably more secure open source ecosystem for everyone.

Practical Takeaways for DevOps Teams

• Integrate security tooling into your CI/CD pipeline. Software composition analysis, static analysis, and container image scanning should run automatically on every build, not as a periodic manual audit.
• Maintain an accurate software bill of materials (SBOM). Know exactly which open source components — and which versions — are present in every artefact you ship.
• Monitor for new disclosures. A component that was safe when you added it may become vulnerable next week. Automated alerting against vulnerability feeds is essential.
• Engage with upstream communities. Report bugs, review security advisories, and where possible contribute fixes. Your organisation benefits directly from the health of the projects you depend on.
• Treat container images as code. Keep base images updated, scan images in your registry as well as at build time, and enforce immutability policies in your orchestration layer.
• Evaluate third-party API dependencies critically. Assess the reliability, security posture, and data handling practices of every external service your application calls.

The Case for Shifting Security Left

As engineering teams face mounting pressure to ship software faster, more and more aspects of the development process are being moved earlier in the lifecycle—a practice commonly called “shifting left.” Security is no exception. Because code is updated and delivered at an ever-increasing pace, treating security as a final gate before release is no longer viable.

“That’s why we profess to shift left security and basically embed it as early as possible in the development process so that developers can do a lot of the work in advance as they deliver the applications and not expect to throw it over the fence and have someone else take care of it,” said Rani Osnat, VP of Product Marketing at Aqua Security, a container security company.

Operations teams can no longer simply accept an application as delivered and then plan to secure it after deployment. The old model—where application security acted as a point-in-time governance gate before release—is increasingly incompatible with agile delivery and continuous deployment practices.

“As trends like agility, continuous delivery, or DevOps come into play, that role as a point-in-time gate and as a governance function is being questioned,” explained John Steven, Senior Director of Software Security at Synopsys.

What Top Performers Do Differently

According to Arkadiy Miteiko, co-founder and CEO of CodeAI, an AI-based security platform, the highest-performing organizations typically implement three practices in their security workflows:

1. Inject code analysis tools into the development process and enforce fixes before deployment, rather than after.
2. Automate attacks against pre-production code and block that code from reaching production if simulated attacks succeed.
3. Continuously test the production environment for weaknesses in an automated, ongoing fashion rather than relying on periodic audits.

These three pillars represent a maturity model that many organizations are still working toward. The challenge is not just technical—it is also organizational and cultural.

From DevOps to DevSecOps

The logical evolution of DevOps culture is DevSecOps—a model in which security considerations are embedded alongside development and operations rather than siloed into a separate function that engages only at the end of the pipeline.

In this model, security teams retain ownership of policy definition: determining what constitutes an acceptable level of risk and what controls must be in place. However, the implementation of those policies becomes a shared responsibility between security and development teams, rather than a unilateral mandate handed down from a separate group.

“There’s a lot of automation that you can do, which again is absolutely mandatory in these environments because of the speed in which code moves in the pipeline. It is just not manageable with purely manual control,” said Osnat.

The Cybersecurity Skills Gap Makes Shift-Left Urgent

A persistent shortage of cybersecurity professionals is one of the strongest arguments for shifting security responsibility toward developers. Osnat noted that at the time of reporting, there were hundreds of thousands of unfilled cybersecurity positions in the United States alone, and industry forecasts suggested that number could climb dramatically in the following years.

“Developers are developing more applications faster and delivering code faster than security can catch up to,” said Osnat. “That’s something where really the only way to address it is not to just give more work to security, but to move some of the burden to the developers in using best practices to secure applications when they are developed. But, of course, they need to be taught and told what they are expected to do. It’s not something that you can expect them to just figure out on their own.”

There are simply far more developers in the world than security specialists. Leveraging that larger population—while equipping them with security knowledge and tooling—is a more scalable approach than trying to staff every pipeline with dedicated AppSec engineers.

The Cultural Challenge: Silos Are Hard to Break

Shifting testing and security left requires more than tool adoption—it demands genuine cultural change. “Cultural imperatives are very hard for organizations to adopt because organizations reject culture change like viruses,” said Synopsys’ Steven.

Even organizations that nominally adopt DevOps often fall into a familiar trap: they hire a “DevOps engineer” who reports into operations, effectively creating a new role inside an existing silo rather than breaking silos down. “They’ve taken this cultural imperative to break down the walls, and they’ve turned it into a role in one of the silos, which is of course a perversion of the intent,” Steven explained.

The companies that have scaled successfully tend to be those that genuinely distributed security responsibility. In those organizations, the security team operates more like a coach—setting standards, providing visibility into what is working and what is not, and enabling other teams to act on that information—rather than functioning as a bottleneck gate.

Pete Chestna, Director of Developer Engagement at CA Veracode, added that organizational accountability structures matter enormously. If development teams are not held accountable for the security of what they build, they will naturally delegate that responsibility elsewhere. “Once that becomes a non-option then they start to make that change real,” he said.

Teaching Developers to Code Securely

Shifting the security burden toward developers only works if developers actually know how to write secure code—and that education often does not happen automatically. “It’s a muscle that development organizations don’t have,” said Chestna.

The solution is continuous feedback and targeted training rather than after-the-fact correction. “If you allow developers to continue to code incorrectly and then correct them later, you’re not really helping them be better,” Chestna explained. “DevOps is all about continuous improvement. So we need to take the knowledge of what they struggle with and feed that back to them in the form of training and then measure whether or not that training was effective.”

Chestna drew a useful historical parallel: twenty-five to thirty years ago, developers assumed that someone else would test their code after the fact. Over time, test-driven development and unit testing became standard practice—developers now write tests as they write code. Security, he argued, can follow the same trajectory.

“Similarly, if we start to put security into the vein, we’ll have the same effect where graduates walk into a company and know: code has to be secure, it has to function, and it has to perform well,” said Chestna. “Those are things where if they’re taught earlier on, it just becomes part of their nature.”

This points toward a longer-term need to change university curricula so that secure coding is treated as a foundational skill alongside functionality and performance—not an optional or advanced topic.

The Role of AI and Automation

Artificial intelligence is increasingly discussed as a lever for addressing both the skills gap and the scale challenges inherent in modern application security. Miteiko of CodeAI explained the core proposition: “AI is extremely good at recognizing patterns and making statistical predictions based on its pattern recognition. Noise is a recognizable pattern. Once it has been recognized it can be filtered out. The quality and security issues that we are dealing with in code today are the same coding errors we fixed years ago.”

This means AI systems can, in principle, be trained to identify known vulnerability patterns at scale, filter out false positives that slow developer workflows, and surface the issues most likely to represent genuine business risk—a problem that John Steven identified as a core struggle for many organizations: distinguishing between what general security guidance says to look for and what actually matters for a specific business’s risk profile.

“The future belongs to intelligent machines which are able to augment some of the security testing functions while working alongside humans,” Miteiko said. “A shortage of skilled security professionals on both sides—AppSec and CyberSec—and their relatively high cost will drive an adoption of intelligent automation powered by AI systems.”

Where the Industry Is Heading

Looking forward, the consensus among practitioners is that the trend toward embedded, automated, shift-left security will only accelerate. Cloud-native application architectures—containers, microservices, serverless functions—are designed to be portable and environment-agnostic, which makes language- or environment-specific security tooling of the past less relevant and creates an opening for more unified security approaches.

Osnat predicted that development platform vendors will increasingly embed security tooling directly into their platforms, rather than leaving it as an afterthought or an add-on. Software vendors themselves will be expected to ship secure tooling, not just functional tooling.

“If vendors are able to provide the industry with tools that have the capabilities required to win this security game, we’ll begin to see drastic improvements in the overall security posture,” said Miteiko.

Key Takeaways for DevOps Teams

• Embed security tools in the CI/CD pipeline so that vulnerabilities are caught at build time, not after deployment.
• Automate security testing at every stage—static analysis, dynamic testing against pre-production environments, and continuous monitoring in production.
• Make security a shared responsibility between development and security teams, with clear policy ownership residing in security and implementation accountability sitting with developers.
• Invest in developer security training and create feedback loops so developers understand the specific mistakes they are making and can correct them over time.
• Treat cultural change as seriously as tooling—breaking down silos requires organizational accountability structures, not just new job titles or tool purchases.
• Evaluate AI-assisted security tooling for pattern recognition, noise reduction, and risk prioritization to help smaller security teams operate at the scale of modern development velocity.

What Is Wallarm FAST?

In April 2018, cybersecurity company Wallarm announced the launch of its Framework for Automatic Security Testing (FAST), a new product designed to help development and security teams automatically generate and run security tests against running applications.

Unlike traditional static analysis tools that inspect source code without executing it, FAST targets running applications, generating HTTP-based test cases derived from existing functional tests and using fuzzing to probe for vulnerabilities and unexpected application behavior.

How FAST Works: IAST, Fuzzing, and Functional Test Reuse

Application security testing broadly falls into three categories:

• SAST (Static Application Security Testing) – analyses source code or binaries without executing the application.
• DAST (Dynamic Application Security Testing) – probes a running application from the outside, simulating an attacker.
• IAST (Interactive Application Security Testing) – instruments a running application to observe behavior during test execution, combining elements of both SAST and DAST.

According to Wallarm CMO Renata Budko, FAST sits closest to the IAST category: “FAST is not a SAST, it is more akin to an IAST tool. The idea is that it uses QA functional tests and a fuzzer as an inducer and analyzes the responses to detect vulnerabilities and anomalies.”

The core workflow is straightforward: FAST intercepts existing functional test traffic (for example, HTTP requests generated by a Selenium test suite), uses that traffic as a baseline, and then applies its fuzzing engine to generate a large volume of additional security-focused test cases. Application responses are then analyzed for signs of vulnerabilities or anomalous behavior.

The Fuzzing Engine

Fuzzing is a well-established security testing technique in which malformed, unexpected, or random inputs are injected into an application to observe how it responds. FAST includes a proprietary fuzzing engine built by Wallarm, not derived from open-source projects, according to Budko.

The fuzzer is policy-driven: “The fuzzer is governed by the policy which specifies what parameters of the payload or the header to fuzz, and how to tune up the fuzzing so that generated payloads are more relevant.” This policy-based approach allows teams to target fuzzing effort at the most security-sensitive parts of a request rather than applying brute-force mutation indiscriminately.

Language-Agnostic and API-First Design

Because FAST constructs tests as HTTP requests rather than language-level instrumentation, it is not tied to any specific programming language or framework. “FAST is not language specific, it can be used to test apps and micro-services written in any language,” Budko told eWeek. “It constructs tests as HTTP requests and applies fuzzing to the body and where applicable, the header of the request.”

All key FAST operations — test generation, policy management, test execution, and results retrieval — are exposed via APIs, making the tool straightforward to embed in automated workflows.

Integrating FAST into a DevOps Pipeline

The rise of DevOps has made continuous security testing — often called DevSecOps — a practical requirement for fast-moving development teams. FAST was designed with this context in mind.

Jenkins Integration

Wallarm’s stated primary integration target at launch was Jenkins, the widely used open-source CI/CD automation server. Budko described a typical use case: “We expect a typical use case to be a FAST test run to be launched from Jenkins as part of a build acceptance criteria sequence.”

In practical terms, this means a Jenkins pipeline stage could trigger FAST after a successful build, run security tests against a staging environment, and gate promotion to production on the results — treating security testing as a first-class step in the delivery pipeline.

Selenium Compatibility

Teams already using Selenium for browser-based functional testing of single-page applications (SPAs) can feed those existing test runs directly into FAST. Budko explained: “Selenium is very popular for automating HTTP tests for SPAs. These automated functional tests make ideal baselines for FAST to apply its multiplier and generate more security tests.”

This is a meaningful productivity argument: rather than requiring security engineers to write a separate, dedicated test suite, FAST reuses the work QA engineers have already done, extending its coverage for security purposes at relatively low incremental cost.

Docker-Based Deployment

FAST is delivered as a Docker container, meaning deployment requires a Docker-compatible container runtime. At launch, no cloud-provider-specific integrations were available for FAST itself, although the existing Wallarm Application Security Platform was certified on both AWS and Google Cloud Platform at the time.

FAST vs. the Wallarm Application Security Platform

It is worth distinguishing FAST from Wallarm’s existing platform. Prior to FAST, Wallarm sold an application security platform focused on runtime protection, including:

• Real-time attack mitigation
• Bot protection
• Web Application Firewall (WAF)
• Dynamic Application Security Testing (DAST) for vulnerability detection

FAST targets a different stage of the software lifecycle — the pre-production testing phase — placing it in the application security testing (AST) market rather than the runtime protection market. The two products are complementary rather than overlapping.

Company Background

At the time of the FAST announcement, Wallarm had been operating since 2013 and had raised a total of $2.9 million in funding. The company indicated plans to expand FAST into a broader product line aimed at larger development organizations.

Key Takeaways for DevOps and Security Teams

• Reuse existing QA tests: FAST amplifies Selenium and other functional test suites into security test coverage without requiring a separate authoring effort.
• Language-agnostic: Works at the HTTP layer, so it is compatible with any backend technology stack.
• CI/CD native: Full API coverage and Jenkins integration make it suitable for automated pipeline security gates.
• Docker-delivered: Simple to deploy in any environment that runs containers.
• Policy-controlled fuzzing: Lets teams tune relevance and scope of generated payloads rather than relying on generic mutation strategies.

Note: This article reflects Wallarm’s product capabilities and company status as of April 2018. Readers should consult current Wallarm documentation for up-to-date product information.

The DevSecOps Gap: Awareness Without Action

Synopsys Inc. released research data highlighting a troubling disconnect in how enterprises approach application security within their DevOps pipelines. Despite widespread acknowledgement of the benefits, security integration into continuous integration and continuous delivery (CI/CD) workflows remains inconsistent and incomplete across the industry.

The 451 Research report found that only half of CI/CD workflows include application security testing elements, even though survey respondents demonstrated clear awareness of why security testing matters. In other words, the bottleneck is not knowledge — it is execution.

Why DevOps Teams Are Moving Fast — and Taking on More Risk

Modern DevOps teams operate at a scale and pace that amplifies the consequences of any security gap. According to the survey, 63 percent of respondents expected to deploy software at least four times faster in a DevOps model compared to traditional delivery approaches. Each release often involves significant code changes, and the underlying infrastructure is increasingly large and complex.

This acceleration is exactly what DevOps promises to deliver — but without a deliberate and automated security strategy embedded into the pipeline, speed becomes a liability. Vulnerabilities that would previously have been caught in a slower, more manual review cycle can ship directly to production.

Key Challenges Organisations Cite for DevSecOps Adoption

The survey identified several recurring obstacles that prevent security from being effectively integrated into CI/CD workflows:

• Lack of automation and consistency: Security checks that rely on manual processes do not scale to the velocity of modern pipelines. Without automation, testing becomes a bottleneck rather than a safeguard.
• Reduced pipeline speed: Teams often perceive security tooling as slowing down builds and deployments, creating organisational pressure to skip or defer testing.
• False positive noise: Security scanners that produce a high volume of inaccurate alerts cause alert fatigue, erode trust in tooling, and lead developers to ignore findings — including genuine vulnerabilities.

Jay Lyman, principal analyst at 451 Research, summarised the situation clearly:

“While some DevOps teams are starting to incorporate application security into their CI/CD workflows, driven by factors such as improved software quality, compliance, and risk avoidance, there is ample room for improvement. In many cases, security testing is not being integrated often or early enough in the process for organisations to fully benefit from reduced risk and rework headaches.”

Jay Lyman, Principal Analyst, 451 Research

The Case for Shifting Security Left

Despite the challenges, the survey data reinforced a well-established principle in software engineering: integrating automated security tools early in the software development life cycle (SDLC) has a measurable positive impact on both the speed of delivery and the overall quality and security of the finished software.

“Shifting left” — the practice of moving security testing earlier in the development process rather than deferring it to a pre-release gate — reduces the cost and complexity of remediating vulnerabilities. A defect caught during development is far cheaper and faster to fix than one discovered after deployment. This is not a new argument, but the survey data suggests many organisations still struggle to act on it in practice.

Software Composition Analysis: The Most Critical Gap

One finding stands out as particularly urgent: Software Composition Analysis (SCA) was identified as the most critical application security capability that needs to be incorporated into CI/CD pipelines.

SCA is the process of identifying open source and third-party components within an application and checking them against databases of known vulnerabilities. Given that modern applications are built heavily on open source libraries and frameworks, SCA is not optional — it is foundational.

Yet the survey revealed a significant blind spot: nearly 40 percent of organisations either do not perform SCA at all or claim not to use any open source components. The second claim is almost certainly inaccurate at scale. A separate Open Source Security and Risk Analysis report by Black Duck Software found that over 95 percent of applications contain open source code. The gap between self-reported open source usage and actual usage suggests that many organisations simply do not have visibility into their own software supply chains.

What DevOps Teams Should Prioritise

Based on the findings, teams looking to strengthen their DevSecOps posture should consider the following practical steps:

1. Audit your open source inventory. Before you can secure your dependencies, you need to know what they are. Integrate an SCA tool into your pipeline to automatically detect open source components and flag known CVEs on every build.
2. Automate security testing at every pipeline stage. Static application security testing (SAST), dynamic testing (DAST), and SCA should all be automated triggers in your CI/CD pipeline, not manual gates performed on release day.
3. Tune your tools to reduce false positives. A scanner that developers do not trust is worse than no scanner, because it trains teams to ignore alerts. Invest time in baseline configuration and suppression rules to surface only actionable findings.
4. Define security requirements before writing code. Security requirements should be part of the story or ticket definition, not an afterthought during code review. This is the most literal form of shifting left.
5. Measure and report on security debt. Track the number of open vulnerabilities, mean time to remediate, and the stage at which defects are found. Visibility drives accountability and helps build the business case for further investment.

The Opportunity Is Real

The Synopsys and 451 Research data paints a picture of an industry at an inflection point. The awareness of DevSecOps benefits — better software quality, reduced compliance risk, fewer late-stage rework cycles — is already present in the enterprise. What lags is implementation.

Teams that bridge this gap by automating security testing early and consistently in their pipelines will not only reduce their exposure to breaches and compliance failures — they will also deliver software faster, because fixing vulnerabilities at build time is dramatically cheaper than triaging incidents after release.

The technology to do this exists today. The main barrier is organisational: prioritisation, tooling investment, and the cultural shift required to make security every developer’s responsibility, not just a security team’s periodic concern.

What Is DevSecOps and Why Does It Matter?

Traditional software delivery models treat security as a final checkpoint — code is written, tested for functionality, and only then reviewed for vulnerabilities. By that stage, flaws are expensive and time-consuming to fix. DevSecOps changes this by introducing security practices earlier in the software development lifecycle (SDLC), so that developers and security professionals can identify and resolve flaws continuously — even in small code increments.

The long-term goals of DevSecOps are twofold: prevent vulnerabilities from being introduced in the first place, and detect and resolve them quickly when they do appear. This requires reducing the overall attack surface and maintaining proper visibility and control at both the network and application layers.

Core Security Testing Approaches in a DevSecOps Pipeline

Several testing methodologies support a DevSecOps workflow. Understanding their differences helps teams choose the right combination:

• Static Application Security Testing (SAST): Analyzes source code, bytecode, or binaries without executing the application. It can be run early in development — even in a developer’s IDE — and is effective at catching issues like injection flaws and insecure coding patterns.
• Dynamic Application Security Testing (DAST): Tests a running application by simulating external attacks. It is typically applied later in the pipeline, against a deployed or staged version of the application.
• Interactive Application Security Testing (IAST): An evolving approach that instruments the application from within during runtime, combining aspects of both SAST and DAST. IAST can deliver more accurate results with fewer false positives, though it requires integration with the application under test.
• Penetration Testing: Manual or semi-automated adversarial testing conducted by security professionals. It provides an unbiased, real-world perspective on exploitable vulnerabilities that automated tools may miss.
• Manual Code Review: Human review of code for logic flaws, security antipatterns, and business-logic vulnerabilities. Used alongside automated tools, not as a replacement.

No single approach is sufficient on its own. A layered strategy — combining static analysis, dynamic testing, and periodic manual review — provides the broadest coverage.

Five Practical Steps to Integrate Security into DevOps

1. Assemble the Right Team

Effective DevSecOps is not solely a developer or security team responsibility. Your team should include:

• Software developers and QA engineers
• IT operations staff
• Application security specialists
• Internal auditors and compliance officers
• Business stakeholders and executives who understand risk tolerance and regulatory obligations

Security decisions made in isolation — without business context — often result in requirements that are impractical to implement or misaligned with actual risk priorities.

2. Define Specific Security Requirements

Security requirements go well beyond basics like password policies and encryption. Detailed requirements must address:

• Database configuration and access controls
• Cloud versus on-premises infrastructure security considerations
• Integration with existing network security controls (firewalls, IDS/IPS, WAFs)
• Secrets management for credentials, API keys, and certificates
• Compliance obligations (e.g., PCI DSS, HIPAA, SOC 2) that affect application design

Documenting these requirements early gives developers a clear target and reduces ambiguity about what “secure” actually means for your organization.

3. Inventory What You Have

Many organizations do not have a complete picture of their existing codebase and application portfolio. Gaps in your security program often trace back to overlooked or assumed-safe applications. A thorough inventory should cover:

• Internally developed applications and services
• Externally facing web and API endpoints
• Third-party libraries, open-source dependencies, and vendor-supplied code

Depending on your organization’s size and complexity, this may be a quick exercise for a small team or may require a formal cross-departmental audit. Regardless, all code in your environment counts when assessing DevSecOps risk.

4. Understand How Your Applications Are at Risk

Manual code reviews and basic vulnerability scans are necessary but not sufficient, particularly when applied only after development is complete. Comprehensive security assessments should include:

• Vulnerability scanning integrated into CI/CD pipelines
• Static source code analysis on every commit or pull request
• Dynamic testing against staging environments
• Periodic penetration testing by qualified security professionals

It is equally important to prioritize findings in business context. A discovered vulnerability does not automatically represent a critical business risk. Establishing clear security standards and severity thresholds helps teams make rational, risk-based remediation decisions rather than reacting to every scanner alert.

5. Act on What You Find

One of the most common failure modes in application security programs is discovering vulnerabilities and then failing to remediate them. Reporting findings without remediation leaves exploitable risk in production and creates organizational liability that compounds over time — especially after a breach or incident.

Remediation does not always mean immediately patching every flaw. It means having a defined, documented process for:

• Triaging findings by severity and business impact
• Assigning ownership and remediation timelines
• Tracking exceptions or accepted risks with proper business justification
• Verifying that fixes are effective through retesting

Even a single well-handled vulnerability — properly identified, fixed, and used as a learning opportunity — can raise the quality bar for the entire team going forward.

DevSecOps Is Not a Silver Bullet

DevSecOps is not a guaranteed solution to all application security challenges. Culture, skill sets, budget constraints, and organizational inertia are real obstacles. Teams that have adopted DevSecOps practices in good faith still encounter significant vulnerabilities when applications are reviewed with fresh eyes or different tooling.

This underscores the value of periodic independent security assessments — using an unbiased perspective and varied tooling that your internal team may not routinely use. The goal is not perfection but continuous improvement: reducing the attack surface, accelerating detection, and building a security-aware engineering culture over time.

Collaboration, speed, and agility are genuine benefits of the DevOps model, but they only deliver value if security is integrated properly. Shipping fast with unresolved critical vulnerabilities is not a DevSecOps success story.

Key Takeaways

• Shift security left: integrate testing into every stage of the SDLC, not just at the end.
• Use a layered approach combining SAST, DAST, IAST, and periodic manual penetration testing.
• Include security, compliance, and business stakeholders — not just developers — in DevSecOps planning.
• Maintain a complete inventory of internal, external, and third-party code.
• Prioritize remediation based on business risk, and always close the loop on findings.
• Treat security as a core component of your development program, not a checkbox activity.

The Security Pendulum in the DevOps Era

Cloud computing and DevOps practices have fundamentally changed how security responsibility is distributed across IT organizations. Where security teams once acted as centralized gatekeepers — reviewing every change before it shipped — those controls have been dispersed across developers, platform engineers, and operations staff. The result is faster delivery and greater agility, but also a new category of risk: an illusion of security that comes from treating built-in cloud controls as a complete solution.

The argument is not that DevOps is wrong. It is that the pendulum has swung from one extreme (security as an absolute authority) to another (security as an afterthought handled equally by everyone). Neither extreme serves the business well.

How We Got Here: From “Department of No” to Full Democracy

Before widespread virtualization and cloud adoption, software projects ran on timelines measured in months or years. Security teams had the time — and the mandate — to review everything before it reached production. This created low risk but also severe friction. Security departments became notorious bottlenecks, blocking or delaying projects in the name of thoroughness. The label “department of no” stuck for a reason.

DevOps emerged partly as a reaction to that friction. By embedding automation, continuous integration, and shared tooling across teams, organizations dramatically shortened feedback loops and release cycles. Security, too, began to be embedded into pipelines rather than bolted on at the end — a practice now commonly called DevSecOps.

But embedding security awareness across all teams is not the same as maintaining security expertise and accountability. As development teams have reached for off-the-shelf cloud security primitives — managed identity, encryption at rest, network security groups — they have sometimes treated those tools as a complete security posture rather than a baseline. Not all data is equal. Customer records, financial data, and intellectual property require layered controls that go well beyond what a cloud provider enables by default.

The Problem with Pure Security Democracy

In a fully democratized security model, everyone has an equal voice in security decisions and no single person or team carries ultimate accountability. This sounds collaborative, but it creates a dangerous diffusion of responsibility. When an incident occurs, the question “who was responsible for that control?” has no clear answer.

Networks and modern application architectures are complex. Attack surfaces shift every time a new service is introduced, a dependency is updated, or a configuration is changed at scale. Identifying those vectors requires specialized training that most developers — however security-aware — simply do not have. Reducing security specialists to advisory roles with no authority leaves organizations exposed.

A Better Model: Representative Security Democracy

The analogy that fits best is not a pure democracy but a representative democracy: power ultimately derives from the organization’s shared goals, but that power is exercised through accountable representatives with domain expertise. In security terms, that representative is the Chief Security Officer (CSO) or equivalent.

Under this model:

• The CSO is accountable to the business — not an independent authority who can veto anything for any reason.
• The CSO has genuine authority over how security policy is implemented, because they carry the accountability when something goes wrong.
• Development and operations teams are trusted partners, not subjects. Their expertise in delivery speed, infrastructure, and application behavior is essential input to security decisions.

This framing removes both extremes: the all-powerful security veto and the leaderless security committee.

Three Practices to Make It Work

1. Recognize Each Team’s Expertise

No single engineer can be an expert in application development, infrastructure automation, and security engineering simultaneously. Each discipline has genuine depth. Development teams understand application behavior and delivery constraints. Operations teams understand infrastructure dependencies and reliability. Security teams understand threat models, compliance requirements, and attack vectors. Effective collaboration starts with each team genuinely respecting what the others know — not just tolerating their involvement.

2. Invest in Cross-Functional Training

Mutual respect is easier when teams understand each other’s constraints. Security professionals benefit from hands-on exposure to modern development workflows: containerization, infrastructure-as-code, CI/CD pipelines, and serverless patterns. Developers benefit from structured security training that clarifies the limits of built-in cloud controls and teaches them when to escalate to a specialist. Training does not need to produce generalists; it needs to produce people who know where their knowledge ends.

3. Create Structured, Regular Communication

Cooperation does not happen spontaneously in fast-moving organizations. It requires a deliberate cadence. Regular cross-team reviews — even a monthly meeting — create a forum where teams can surface security needs on active projects, review shared threat models, and identify when specialist involvement is required. Proactive dialogue prevents the pattern where security is only consulted after a problem has already shipped.

Accountability in a High-Speed World

The pace of modern software delivery is not slowing down. Containers, serverless computing, and managed cloud services continue to raise the abstraction level, letting small teams build and operate at scale. That capability is genuinely valuable. But it compresses the time available to think carefully about security, and it multiplies the number of moving parts that can be misconfigured.

A single significant security incident can affect company valuation, customer trust, and regulatory standing. The risk is not hypothetical. The challenge for DevOps organizations is not to slow down, but to make security accountability as explicit and as scalable as the delivery pipeline itself. That means giving security specialists a genuine seat at the table — not just visibility after the fact, but authority to shape how controls are implemented before features ship.

Key Takeaways

• DevOps democratized security, but full democratization without clear accountability creates risk.
• Cloud provider controls are a baseline, not a complete enterprise security posture.
• The CSO model of representative democracy balances business agility with specialist accountability.
• Cross-team respect, training, and regular communication are the practical mechanisms that make shared security responsibility work.
• Speed and security are not opposites — but achieving both requires deliberate organizational design, not just good intentions.

Background: Java SE 9 Security and the Developer Knowledge Gap

Java SE 9 introduced several security-relevant enhancements that are worth understanding in depth. Among them are JEP-273 (DRBG-Based SecureRandom Implementations), JEP-290 (Filtering of Incoming Serialization Data), and the removal of the restriction on unlimited-strength JCE (Java Cryptography Extension) policies. However, Manico’s core argument is straightforward: having these controls in the specification is not enough. What matters is whether developers understand what each control does and how to apply it correctly.

Interview: Jim Manico on Java Security and DevOps

What Should Concern Enterprise Java Developers?

Cameron McKenzie: When it comes to enterprise Java security, what are the things that concern you most?

Jim Manico: The risks against Java applications are real, and to a lot of developers this is esoteric stuff — it’s not the most exciting feature of the language. But it’s necessary. For example, there is a JSR that addresses serialization and allows for direct whitelist filtering of exact classes at multiple tiers within a Java application. It is not exciting, but it is necessary to have a secure Java application. It gives you a concrete way to address known Java deserialization risks. It’s not sexy, but it’s important.

Avoiding Java Security Bugs in Everyday Development

Cameron McKenzie: Enterprise Java developers tend to focus on fulfilling business requirements. What security concerns should they be thinking about in their day-to-day coding to avoid introducing security bugs?

Jim Manico: The use of numeric types for financial processing is far more subtle than most developers expect. Beyond that, when you want to implement controls like output escaping to prevent cross-site scripting, that capability is not in the core Java language. There are some parts of it in the Java EE APIs and in various frameworks, but it is not a first-class, readily available control in the standard library — and it should be.

The same problem applies to cryptographic APIs. Some of the most developer-friendly cryptographic APIs are not in the Java core. Google Tink, for example, is a cryptographic library designed to make it easier for developers to interact with low-level cryptographic primitives safely. The closer these APIs are to the core language, the more likely developers are to actually use them. Proximity to the core lowers the barrier to adoption.

Every Developer Is Now a Security Engineer

Cameron McKenzie: You’ve argued that software developers and DevOps practitioners should consider themselves security engineers. What do you mean by that?

Jim Manico: The world has changed. Most developers — whether they acknowledge it or not — are security engineers now. The code they write is on the front lines of protecting organizations from data loss, financial damage, reputational harm, privacy violations, and regulatory fines. The code is the first line of defense across all of those risks. The only question is whether a given developer is going to take that responsibility seriously.

For organizations early in their security maturity, running penetration tests against developers’ own code and showing them actual exploits is a powerful way to change culture. Seeing a working exploit against your own application is a far more effective teacher than a policy document. As organizations mature, the goal shifts: security becomes part of the design conversation from the beginning, with shared authentication services, access control frameworks, and cryptographic libraries available to all developers as standard building blocks.

The Limits of DevOps-Based Security Automation

Cameron McKenzie: Does DevOps change the security game? How do you feel about DevSecOps?

Jim Manico: DevSecOps is a piece of the puzzle — it’s a useful concept, but it has real limits that practitioners need to understand clearly.

The value DevSecOps brings is in automation: integrating static analysis, dynamic testing, and unit tests into the CI/CD pipeline so that known vulnerability classes are caught before code reaches production. Automated dashboards and alerting also give operations teams better real-time security intelligence. These are not new ideas, but DevOps practice puts more rigor around them and tries to apply them consistently at scale.

However, there are classes of application security problems that automated tooling handles poorly. Specifically:

• Access control logic flaws — Automated scanners struggle to understand the intended authorization model of an application and therefore cannot reliably detect when access control is broken.
• Business logic vulnerabilities — These are flaws where the application does exactly what the code says, but what the code says is wrong from a security standpoint. No generic scanner can know what your application is supposed to do.
• Complex chained vulnerabilities — Multi-step attack paths that require understanding application state and flow are routinely missed by automated tools tuned for speed.

Manico’s conclusion is blunt: the dark side of DevOps security automation is the temptation to believe you can automate everything. You cannot. Skilled human reviewers — penetration testers who understand the application’s business context — will find things that no automated tool tuned for CI/CD pipeline speed will catch. Automation is necessary but not sufficient.

What Good Security Governance Looks Like in Practice

Cameron McKenzie: When you walk into an organization as a security consultant, what tools, governance models, and policies do you want to see already in place?

Jim Manico: The first thing I look for is a centralized, rigorous authentication service. Rather than having every development team implement their own authentication logic — which is a reliable source of bugs — the organization should provide a standard, well-tested authentication service that all developers consume in a consistent way. That locks down the front gate of every application built on top of it.

The second layer is access control. A proper access control service — one that supports database-driven rules, configuration-driven permissions, and fine-grained horizontal access control — is something every team should be able to leverage rather than reimplement. Access control is too critical to leave to individual developer judgment on a project-by-project basis.

Beyond authentication and authorization, Manico highlights several additional concerns for development teams:

• Secure UI construction — Understanding how the chosen front-end framework handles output encoding and script injection, and ensuring those defaults are not accidentally disabled.
• Client-side data handling — Knowing what data should and should not be persisted on the client, what logic belongs server-side, and how to keep access control rules consistent across both client and server.
• Developer onboarding — New developers should not be expected to independently figure out access control. The organization must have opinionated, documented patterns and shared libraries ready for them to use from day one.

Key Takeaways for DevOps and Security Teams

• Automated security tools in CI/CD pipelines are valuable for catching known vulnerability patterns, but they systematically miss access control flaws, business logic bugs, and complex multi-step attack paths.
• Developers writing production code are, functionally, security engineers — whether their job title says so or not.
• Security controls need to be close to the core of the platform and easy to use; controls that require developer expertise to locate and configure correctly will be misused or skipped.
• Shared, centralized authentication and access control services reduce the attack surface far more reliably than expecting each team to implement their own.
• Manual penetration testing by skilled humans remains a necessary complement to automated scanning, particularly for complex applications.
• Cultural change — showing developers working exploits against their own code — is often the most effective way to build security awareness in organizations early in their maturity.

What Is SecDevOps?

Agility has become a baseline expectation in software delivery. Organizations that cannot ship fast, iterate continuously, and respond to change quickly fall behind. DevOps provides the cultural and tooling framework to achieve that pace — but speed alone is not enough. The attack surface grows with every new service, every new deployment, and every new dependency.

SecDevOps (also written as DevSecOps, depending on the source) is the practice of embedding security directly into the DevOps development cycle rather than treating it as a gate at the end of the pipeline. The goal is to make security a shared, continuous responsibility across development, operations, and security teams — not a handoff that happens after code is already written.

The Problem SecDevOps Solves

In traditional software development, security was treated as a final checkpoint. A security team would review code or run penetration tests shortly before a release, find issues, and hand them back to developers to fix. This model had several compounding problems:

• Long release cycles made security reviews stale. If a release took eighteen months to two years, the threat landscape at ship time looked nothing like it did when development started.
• Late-stage fixes are expensive. Vulnerabilities found during final security review require rework that disrupts schedules and inflates cost. Research in software engineering has long suggested that defects cost more to fix the later they are found, though precise multipliers vary by context.
• Security teams became bottlenecks. A single security review gate before release created pressure to minimize findings rather than address them thoroughly.
• Developers lacked security context. Without security integrated into daily work, developers had little opportunity to build security intuition or catch issues as they wrote code.

DevOps accelerated release cycles dramatically — from years to months, weeks, or even days. That pace change created an opportunity: if code is being written and deployed continuously, security controls and checks can be integrated continuously as well.

SecDevOps in Practice: The Dana Foundation Example

One frequently cited early example of SecDevOps in practice is the Dana Foundation, a nonprofit organization whose technology operations span web-based grant management systems and digital publishing platforms. According to reporting by CIO Insight, the organization’s CIO James Rutt prioritized two things above all else: code quality and code security.

A key part of their approach was protecting against vulnerabilities catalogued in the OWASP Top 10 — a widely recognized list of the most critical web application security risks, including issues such as cross-site scripting (XSS), injection flaws, and cross-site request forgery (CSRF).

By integrating security practices directly into their development workflow, the Dana Foundation reportedly reduced code vulnerabilities by 40 to 50 percent while also speeding up their development process. The combination of improved security posture and faster delivery is the core value proposition of the SecDevOps model.

Core Principles of SecDevOps

SecDevOps is not a single tool or product. It is a set of principles and practices applied across the software delivery lifecycle:

1. Shift Security Left

Security checks move earlier in the pipeline — into the developer’s local environment and the CI/CD pipeline — rather than waiting for a final review. Static application security testing (SAST) tools, dependency scanning, and secrets detection can all run automatically on every commit.

2. Automate Security Gates

Manual security reviews cannot scale to the velocity of continuous delivery. Automated scanning for known vulnerabilities (using tools that check dependencies against CVE databases, for example) allows teams to catch a large class of issues without human intervention on every build.

3. Treat Security as Code

Security policies, compliance rules, and infrastructure hardening configurations are defined as code, stored in version control, reviewed like any other code change, and applied automatically. This brings security policy changes into the same audit trail as application changes.

4. Shared Responsibility

Security is not the exclusive domain of a dedicated security team. Developers, operations engineers, and security specialists collaborate from the beginning of a project. Security training for developers, threat modeling during design, and security-focused code review all distribute security knowledge across the team.

5. Continuous Monitoring and Feedback

Runtime security monitoring, anomaly detection, and incident response are built into operational processes — not added after a breach. Findings from production feed back into the development cycle to inform future security decisions.

Why the DevOps Pace Makes Security Integration Possible

The conventional argument against built-in security was that the threat landscape changes faster than software release cycles. By the time a new version shipped, new attack vectors had emerged that the security review never considered.

Continuous delivery changes this equation. When a team ships code weekly or daily, the gap between the threat environment at development time and at release time shrinks to near zero. Security controls can be updated and deployed with the same cadence as feature changes. A new vulnerability class emerges; a detection rule or code scan update can be in the pipeline within days.

This is the natural alignment between DevOps velocity and security responsiveness that SecDevOps exploits. It is not a workaround or a compromise — it is the model that the security community argued for long before DevOps tooling made it practically achievable.

Getting Started with SecDevOps

Teams transitioning toward SecDevOps typically begin with a few concrete steps:

1. Assess your current pipeline. Identify where security checks currently happen and how much of the process is manual.
2. Integrate SAST and dependency scanning into CI. Tools in this space include open-source options and commercial offerings that plug into most major CI platforms. Start by running them in report-only mode to understand your baseline.
3. Address OWASP Top 10 coverage. Review your application code and framework configuration against the OWASP Top 10. Many frameworks have built-in mitigations for common issues like XSS and CSRF that simply need to be enabled correctly.
4. Define security requirements before coding begins. Threat modeling during design — even a lightweight version — helps teams identify what they need to protect before writing a line of code.
5. Build a feedback loop. Route findings from scanning tools back to developers with clear, actionable guidance. Security findings that disappear into a ticket queue do not get fixed.

SecDevOps vs. DevSecOps: A Note on Terminology

The terms SecDevOps and DevSecOps are used interchangeably in most contexts and describe the same fundamental idea: integrating security into DevOps. Some practitioners argue that the ordering of the words carries meaning — DevSecOps emphasizes that security sits within a DevOps framework, while SecDevOps puts security first in the name to signal organizational priority. In practice, the terminology varies by organization and era; the substance is the same.

Summary

SecDevOps is not a new category of tooling or a one-time project. It is a durable shift in how engineering organizations think about security — from a final gate to a continuous, shared practice embedded in every stage of the development lifecycle. The pace of modern software delivery, rather than being an obstacle to good security, is the very thing that makes continuous security integration achievable. Organizations that align security with their delivery pipeline gain both: faster shipping and a more defensible codebase.

The reality is more nuanced, and a growing body of practitioner experience challenges the binary framing. Organizations that have embedded security into their DevOps pipelines report that the two goals reinforce rather than undermine each other. Understanding why requires examining two foundational principles.

Two Principles That Dissolve the Trade-Off

Security is built in, not bolted on. Treating security as a final-stage gate—a checklist applied before release—means vulnerabilities discovered late are expensive to fix and often shipped anyway under schedule pressure. Building security checks, threat modelling, and automated scanning into every phase of the pipeline makes the cost of remediation far lower and the coverage far higher.

Attackers are already agile. Threat actors iterate quickly, adapt their techniques, and exploit newly disclosed vulnerabilities within hours of public disclosure. A slow, waterfall-style security review process cannot keep pace. An agile security practice—one that continuously tests, monitors, and responds—is better equipped to match the speed of adversaries.

What Enterprise Leaders Actually Prioritise

A survey conducted by DigiCert, titled Making Security Agile, polled 300 enterprise leaders on how their organisations approach the relationship between security and DevOps velocity. The results challenge the trade-off assumption directly.

• 90 percent placed a high priority on improving information security.
• 88 percent placed an equally high priority on IT agility.
• 87 percent prioritised development agility.

The near-identical weighting across all three priorities signals that experienced enterprise leaders do not see these goals as competing. They want all three, and they are actively pursuing all three simultaneously.

On integration progress, the survey found that approximately 49 percent of respondents had already integrated security into their DevOps process, while another 49 percent were actively working toward that goal. Only 2 percent expressed no interest—a number so small the survey authors suggested it might reflect misread questions rather than genuine opposition.

The Real Challenge: Integration Takes Longer Than Expected

The survey surfaced one significant practical finding: organisations consistently underestimate how long DevSecOps integration takes. The typical expectation going in was seven to eleven months. The actual experience, according to respondents, was closer to one to two years.

This gap matters for planning. Teams that budget inadequate time and resources for integration often stall midway, leaving them with neither the speed gains they hoped for nor the security posture they need. Setting realistic timelines and obtaining sustained executive sponsorship are prerequisites for success.

Practical Steps for Integrating Security Into DevOps

The DigiCert survey recommended a specific set of actions for organisations working through this integration. These align well with broader DevSecOps best practices:

1. Establish a Cultural Champion

The survey recommended appointing a social leader responsible for driving cultural change—someone who can bridge the gap between security teams and development teams. Security integration is as much a people problem as a tooling problem. Without someone actively advocating for the shift, process inertia tends to preserve old silos.

2. Apply the Principle of Least Privilege

Limiting access—to environments, secrets, infrastructure controls, and production systems—reduces the blast radius of any single compromised credential or misconfigured service account. In a pipeline context, this means scoping CI/CD service accounts tightly and rotating credentials automatically.

3. Automate Certificate Management with PKI

Manual certificate management does not scale in a world of microservices, ephemeral containers, and frequent deployments. Automated public key infrastructure (PKI) ensures that services communicate over encrypted channels and that certificates are renewed before expiry—without requiring manual intervention that slows teams down.

4. Embed Automated Scanning in the Pipeline

Several categories of automated tooling belong in every mature DevSecOps pipeline:

• Static Application Security Testing (SAST): Analyses source code for known vulnerability patterns before a build is complete.
• Software Composition Analysis (SCA): Identifies known vulnerabilities in open-source dependencies.
• Dynamic Application Security Testing (DAST): Tests running applications for exploitable weaknesses.
• Container and infrastructure scanning: Checks base images and infrastructure-as-code definitions for misconfigurations and known CVEs.
• Patch management automation: Keeps underlying operating systems and runtimes up to date without requiring manual scheduling.

Running these checks automatically on every pull request or merge means vulnerabilities surface when they are cheapest to fix—before they reach production.

Why Integrated Security Produces a More Resilient Architecture

When security controls are woven into the development lifecycle from the start, the resulting system architecture is inherently more robust. Developers write with security patterns in mind. Infrastructure is provisioned with hardened defaults. Secrets management, network segmentation, and logging are not afterthoughts.

This built-in foundation also makes the system more adaptable to new threats. Because the basic security primitives are already strong and automated, the team can respond to a newly disclosed vulnerability or an emerging attack pattern without rebuilding from scratch. Agility in the development process translates directly into agility in the security response.

The Conclusion: Agility Enables Better Security

The framing of security versus agility is a false dilemma. Organisations that integrate security into their DevOps pipelines discover that moving faster with built-in controls is safer than moving slower with bolted-on reviews. The pipeline itself becomes the enforcement mechanism, and automation removes the human bottlenecks that create both delay and inconsistency.

The transition takes longer than most teams expect and requires real cultural investment alongside tooling changes. But the end state—a DevSecOps practice where speed and security compound each other—is achievable and increasingly the norm among mature engineering organisations.

Original source referenced: securityintelligence.com, citing the DigiCert “Making Security Agile” survey.

Why IT Ops Can No Longer Ignore Security

Secure DevOps — the practice of weaving security disciplines into the continuous delivery pipeline — has so far been driven mainly by collaboration between application developers and security professionals. IT operations has largely been left out of that early conversation. But as the industry pushes security earlier in the software delivery lifecycle (the “shift left” principle), ops teams will need to respond proactively rather than reactively.

The pressure is real. High-profile data breaches have put every department in the spotlight, and business leadership increasingly expects all of IT — not just the security team — to prevent incidents. “Every part of the organization should be thinking about security right now,” said Stephen Sadowski, director and senior architect of core engineering for ICF Olson, a digital services subsidiary of US government contractor ICF. “The task for ops is to see security as a problem they need to help solve.”

Secure DevOps and the Need for Speed

IT security has historically been perceived as an isolated function that hands down policy mandates without engaging day-to-day delivery teams. Developers and security professionals have begun to dismantle that dynamic, and ops teams need to follow their lead.

Waiting for a formal invitation may not be a viable strategy. Jack Fraker, an application security specialist at an East Coast insurance company, took the initiative to collaborate directly with developers at his organization without a management mandate to do so. His advice to ops engineers reflects a skills-broadening imperative: “Your resume has to read differently now. You can’t be a specialist in just one thing.”

This means ops engineers need to develop at least working familiarity with application security concepts — vulnerability classes, threat modeling, secure configuration baselines — so they can participate meaningfully in cross-functional security conversations.

Infrastructure as Code as a Security Bridge

At ICF Olson, the ops team adopted infrastructure-as-code (IaC) practices to make infrastructure changes visible, reviewable, and testable alongside application code. Sadowski’s team uses Terraform and Chef to define and provision infrastructure, enabling security reviews to be applied to infrastructure changes in the same way they are applied to application code during pull requests or CI pipeline checks.

The team also uses Chef InSpec to validate that server configurations match the organization’s security policies. InSpec allows teams to express compliance requirements as code, making it possible to automatically verify that hardening rules and policy baselines are in place before anything reaches production.

The result, according to Sadowski, is a two-way conversation with security rather than a one-way policy mandate: security teams offer concrete guidance on implementation, and ops teams surface infrastructure constraints that security must account for.

New Monitoring Tactics Without Starting From Scratch

Organizational change is difficult, but so is evolving day-to-day operational practice. The good news for ops engineers is that secure DevOps does not necessarily require a wholesale replacement of existing tooling.

At Fraker’s company, the security operations team applies familiar IT monitoring tools to detect risks in infrastructure design and configuration, as well as to watch for malicious network behavior. The toolset itself has not changed dramatically. “Security operations has upgraded some of its monitoring tools a bit, but they already had a good toolset,” Fraker said. “It’s more about how they’ve changed their procedures around using it.”

The practical implication for ops teams: review your existing monitoring stack for security telemetry gaps before assuming you need new tools. Often the gap is procedural — misconfigured alert thresholds, missing log sources, or no defined response runbook — rather than a missing product.

Federal Efforts to Modernize Security Tooling

Kevin Greene, a program manager in the cybersecurity division of the US Department of Homeland Security (DHS), acknowledged at DevSecCon that there is still significant room for improvement in infrastructure monitoring tools for risk management. Greene noted that many commercial offerings lack advanced capabilities needed to address emerging threats — particularly proactive threat modeling that anticipates attacks on infrastructure vulnerabilities, rather than relying solely on static analysis after the fact.

DHS launched two relevant programs to address this gap:

• Static Tool Analysis Modernization Project (STAMP): A framework to assess the strengths and weaknesses of existing security analysis tools and drive a roadmap for modernizing them.
• Application Security Threat Attack Modeling (ASTAM): A program that engaged vendor Secure Decisions to develop an open-source tool designed to strengthen defenses against web application attacks, with an emphasis on dynamic threat modeling.

Greene’s broader message for ops teams: DevOps is changing infrastructure faster than many monitoring solutions can track. “Ops needs a grasp on those changes so they know what to monitor,” he said. As deployment frequency increases and infrastructure becomes more ephemeral, static monitoring configurations will drift out of alignment with the actual environment.

Practical Steps for IT Ops Teams Entering the Secure DevOps Conversation

Based on the practices described in the original reporting, here are concrete starting points for ops teams looking to integrate more deeply into secure DevOps:

1. Adopt infrastructure as code with security gates. Use tools like Terraform, Ansible, or Chef to define infrastructure, and add policy-as-code checks (such as Chef InSpec, Open Policy Agent, or Terraform Sentinel) to validate compliance before changes are applied.
2. Request a seat in security and development planning meetings. Ops teams should not wait for a mandate. Proactively joining sprint planning or threat modeling sessions surfaces infrastructure constraints early.
3. Audit existing monitoring for security blind spots. Before purchasing new tools, map current log sources and alert rules against common infrastructure attack vectors. Identify gaps in coverage and update procedures to address them.
4. Build cross-functional skills. Ops engineers who understand secure configuration baselines, common vulnerability classes (such as those in the OWASP Top 10), and network security fundamentals become far more valuable partners to security teams.
5. Automate compliance checks in the CI/CD pipeline. Shift infrastructure compliance validation left so that policy violations are caught during code review or pipeline execution, not post-deployment.

The Broader Culture Shift

Secure DevOps is not primarily a tooling challenge — it is a cultural one. The traditional separation between development, operations, and security functions created handoff delays and accountability gaps that attackers exploit. Bridging those gaps requires ops engineers who are willing to expand their scope, communicate proactively with security teams, and treat security as a shared responsibility rather than someone else’s problem.

The path forward looks like infrastructure teams that co-own security outcomes, monitor environments with security intent, and can articulate risk in terms that security and business leadership both understand.

Why DevOps Is Harder Than It Looks

The ability to introduce new business services and capabilities — and ship them to customers quickly and effectively — depends on IT and business sides of the enterprise being in genuine alignment. DevOps provides a framework for achieving that alignment by combining development and operations through practices that prioritize collaboration, automation, and continuous feedback.

“It’s a very powerful tool for removing bottlenecks,” says Aater Suleman, co-founder and CEO of Flux7, a consulting firm that specializes in DevOps adoption.

Yet despite the clear benefits, many organizations struggle to move beyond surface-level adoption. Business and IT leaders sometimes lack a clear picture of what DevOps actually is, what it delivers, and how it works in practice. Equally common is a failure to identify key stakeholders early, or to connect the organization’s business agility goals to the specific places where DevOps can make a measurable difference.

Reducing Complexity and Improving Agility

A well-executed DevOps initiative reduces complexity and improves agility across the software delivery lifecycle. Concretely, this means:

• Faster, higher-quality code delivery
• Software that more closely reflects the needs of business units and end customers
• IT infrastructure and capacity that scales to match shifting organizational requirements
• Automation that frees teams from repetitive, error-prone manual tasks

“An organization can gain a level of automation and efficiency that is transformative,” says David Newberry, principal for application services and platforms at Capgemini Consulting.

A clear vision of what DevOps will deliver is paramount. That vision should be anchored in business value: faster application deployment, more reliable services, and better alignment between what development teams build and what the business actually needs. Critically, that vision must be built with input from stakeholders across the organization — not just in IT.

Culture Is the Hard Part

“A point that’s often overlooked is that DevOps is heavily about the culture of the organization,” Newberry emphasizes. “It requires different thinking and different behavior.”

Cultural change is arguably the most difficult aspect of any DevOps transformation. Suleman stresses that a culture of accountability is essential. That means:

• Establishing a governance model with clear KPIs, metrics, and quality gates
• Building shared ownership — teams must understand that the full system is greater than the sum of its individual parts
• Holding development teams accountable beyond the single component they deliver, including code security and downstream interactions with other services, APIs, and systems

“Development teams need to recognize that they are responsible for more than the one piece that they create and toss over to the next group,” Suleman says. “They need to be accountable in a more holistic way.”

Building a Practical DevOps Strategy

Getting DevOps into the mainstream of an organization requires a deliberate, structured approach. Suleman recommends the following progression:

1. Establish a center of excellence. Create an internal team or working group that owns DevOps best practices and drives adoption.
2. Run focused pilot projects. Choose initiatives that will demonstrate clear ROI and attract the attention of leadership.
3. Document outcomes. Record both successes and failures. Learning what doesn’t work is just as valuable as what does.
4. Share knowledge broadly. Once internal experts emerge, use them to help other teams adopt DevOps practices. “You can help other teams get on board and push the concept deeper into the organization,” Suleman explains.

The Tactical Building Blocks

Beyond culture and strategy, a functioning DevOps model requires a set of concrete technical and process capabilities:

• Collaboration and communication tooling: Real-time communication platforms that keep all key stakeholders in sync, regardless of location.
• Automated testing: Tools that check continuously for code quality issues and application security vulnerabilities.
• Cloud and API libraries: Shared, reusable infrastructure and integration components that accelerate delivery.
• Integrated configuration management: A unified approach to managing environment configurations to reduce drift and deployment failures.
• Application monitoring and automated dashboards: Real-time visibility into system performance, team status, and project governance — including continuous and predictive monitoring where appropriate.

Dismantling Silos

One of the most fundamental structural changes DevOps demands is the elimination of IT silos. Traditional software delivery moves code through discrete stages — build, test, deploy — handled by discrete, separated teams. DevOps replaces that model with continuous, cross-functional workflows that are visible to all relevant stakeholders.

“There’s no need for everyone to sit in the same room,” Suleman notes. “With tools and processes that enable communication and define the delivery process, it’s possible to radically redefine the speed and manner in which development takes place. You no longer wind up with developers not knowing what the change was supposed to be and operations making the wrong change.”

DevOps Is a Continuous Improvement Program, Not a Project

When organizations succeed with DevOps, processes that previously took months may take weeks or days. Error rates drop. Agility, flexibility, and delivery performance improve measurably, and the organization’s capacity for innovation expands.

“The most important thing to understand is that DevOps is not a six-month initiative,” Newberry says. “It’s not a close-ended project. It’s a continuous improvement program that ties together your business and IT value chains. Even as technology evolves and customer solutions change, DevOps is able to help an organization deliver faster and better. It provides the framework to grow and change.”

That framing matters. Organizations that treat DevOps as a one-time transformation project tend to plateau. Those that treat it as an ongoing discipline — continuously measuring, learning, and improving — are the ones that realize the deepest and most durable benefits.

This article draws on commentary originally published at baselinemag.com, including insights from David Newberry of Capgemini Consulting and Aater Suleman of Flux7.

Why Legacy AppSec Thinking Leaves You Exposed

There is a well-known principle in military strategy: armies that focus too heavily on the last war they fought are poorly prepared for the next one. The same logic applies directly to application security. When organizations anchor their defense posture to the threats and tools of the past, they leave themselves exposed to the threats taking shape right now.

This problem is compounded by the pace of change in how software is built. The rise of microservices architectures, API-first design patterns, single-page applications, and the broad adoption of DevOps and Agile methodologies means that the attack surface of a typical enterprise has fundamentally shifted. Within a single organization, different teams may be building different classes of applications on different platforms using different development approaches—all at the same time. Traditional, siloed application security processes simply are not designed for this reality.

Security approaches based on known threat signatures and patterns will only ever detect what has already been identified and catalogued. What is needed is the ability to detect signs of attack of any form, across any type of application, in any environment, in real time. Getting there requires a strategic shift around three core pillars: empowerment, flexibility, and rapid response.

Pillar 1: Empowerment

Traditional cybersecurity has been built around complex tooling operated by a small group of highly specialized security engineers. This model creates two critical problems:

• Dependency and friction: Development and DevOps teams must queue up requests to a separate security team, slowing delivery pipelines and creating a gap in what should be a fast, continuous workflow.
• Talent scarcity: Skilled application security engineers are genuinely difficult to hire. Building a security program that cannot function without them is a strategic vulnerability in itself.

The answer is to break down the silos between security, development, and operations, and to equip developers and DevOps engineers with security capabilities they can use autonomously—without needing to escalate every issue to a dedicated security team.

In practical terms, this means integrating security tooling directly into the workflows and platforms developers already use. Surfacing security alerts and remediation guidance inside tools such as Jira, Datadog, PagerDuty, and Slack—rather than in a separate security console that developers never open—dramatically lowers the barrier to acting on security findings quickly.

Empowerment also means giving teams the autonomy to address the threats they actually face today, not just the threat categories that were relevant several years ago. Security ownership must move closer to the teams building and operating the software.

Pillar 2: Flexibility

Modern enterprise environments are heterogeneous by design. Development teams make their own infrastructure and platform decisions based on the requirements of their specific applications. Cloud providers, container orchestration platforms, PaaS offerings, IaaS layers, programming languages, and deployment models vary widely—even within the same organization. Mergers and acquisitions add further variety as acquired teams arrive with established, well-integrated technology stacks of their own.

Attempting to impose a single, standardized security architecture across this landscape has predictable consequences: teams work around the requirement rather than comply with it, and the organization ends up with security blind spots where the mandate was simply not practical to enforce. Mandating a single architecture also locks out legitimate future options—containers and microservices that seem irrelevant to a particular team today may be central to their roadmap in twelve months.

A genuinely flexible application security strategy must be able to cover the full spectrum of platforms without requiring teams to rewrite or restructure their applications. Concretely, this means security technology should be deployable in multiple modes to suit different contexts, including:

• Next-Generation Web Application Firewall (NGWAF): for perimeter-level traffic inspection and blocking.
• Runtime Application Self-Protection (RASP): embedded directly into the application runtime to detect and block attacks from within the executing code.
• Reverse proxy mode: sitting in front of application infrastructure without requiring agent installation.

When security tools can meet teams where they are—rather than demanding that teams reshape their architecture to accommodate the security tool—adoption improves and coverage gaps shrink.

Pillar 3: Rapid Response

Detecting a threat that happened three days ago is not the same as stopping an attack in progress. Traditional application security often relied on point solutions that addressed isolated parts of the threat landscape and produced reports that security teams reviewed on a periodic basis. This cadence is fundamentally incompatible with the speed at which modern attacks are executed.

Effective rapid response requires continuous visibility into live production activity across multiple attack vectors simultaneously. The threat categories a mature AppSec program must account for include, but are not limited to:

• OWASP Top 10 vulnerabilities (injection, broken authentication, XSS, and so on)
• Application-layer DDoS attacks
• Brute force and credential stuffing attacks
• Account takeover attempts
• Malicious bot traffic
• Business logic abuse specific to the application
• Rate-limiting violations

The value of real-time, multi-vector analysis is in the context it provides. An isolated spike in failed login attempts might look like noise; combined with an unusual rate of account-to-payment-instrument associations and deviations from established behavioral baselines for critical application functions, it tells a much clearer story. That contextual picture enables faster, better-informed decisions about how to respond—and prevents the kind of slow, fragmented analysis that allows attackers to achieve their objectives before a defense is mounted.

Building a Forward-Looking AppSec Posture

The application security problems organizations face in 2024 and beyond will not be solved by the tools and processes designed for the threat landscape of a decade ago. The development practices, infrastructure choices, and attack techniques have all changed significantly—and they will continue to change.

A security posture built around empowerment, flexibility, and rapid response is not just a better fit for today’s environment; it is structurally more capable of adapting to whatever comes next. Rather than designing defenses around a fixed set of known threats, it positions organizations to detect and respond to novel attacks as they emerge—because the detection logic is grounded in real-time behavioral analysis rather than historical pattern matching.

The organizations best positioned to defend their applications are those willing to stop refighting the last war and start preparing for the next one.

For many enterprises, migrating to a cloud-delivered model for IT systems is a compelling proposition. Cost efficiency, elastic scaling, and improved business agility are all strong drivers pushing CIOs toward public cloud adoption. Most organizations are either already migrating or actively planning to do so. But the leap from on-premises infrastructure to cloud-hosted platforms is not without significant challenges — including regulatory compliance, data governance, billing complexity, and security risks.

Minimizing migration risk must be a top priority. Traditional security tools designed for perimeter-based, hardware-defined environments often do not translate cleanly to cloud environments. CIOs and CSOs need to address specific risk categories before migration begins — not after.

Key Risks to Address Before You Migrate

1. Regulatory Compliance

Depending on your industry, your organization may be subject to standards such as PCI DSS (payment card data), SOX (financial reporting), or HIPAA (protected health information). Moving to the cloud does not change the underlying compliance requirements — you are still responsible for meeting them — but it often requires different technical approaches to achieve them.

Key controls to implement in a cloud compliance program include:

• Identity and Access Management (IAM): Fine-grained, role-based access controls to limit who can touch what resources.
• Audit logging and anomaly detection: Comprehensive, tamper-evident logs and automated alerting for unusual behavior.
• Incident response and responsible disclosure: Documented runbooks for responding to breaches, including notification obligations under applicable regulations.

2. Data Governance

A well-formed data governance strategy is essential before any data moves to the cloud. This means defining clear data classification policies — knowing which data is sensitive, who is authorized to access it, and under what conditions it can be moved or shared.

Practical controls include:

• Data access policies: Users should not be able to access or move data without explicit authorization. Enforce least-privilege principles.
• Encryption in transit and at rest: Encrypt sensitive data at every stage. Under HIPAA, encryption of PHI at rest is effectively required. Elsewhere, it is best practice.
• Data residency and locality: Cloud providers operate globally. Understand where your data physically resides and whether that satisfies regulatory or contractual requirements for your jurisdiction.

3. Infrastructure and Application Security

One of the most significant architectural shifts in cloud security is the move away from hardware-defined, perimeter-based security models toward software-defined security. In the cloud, there is no true network perimeter — resources are elastic, programmable, and potentially accessible from anywhere.

This has two important implications:

• Continuous configuration monitoring: Because infrastructure can be provisioned and changed programmatically at any time, a misconfiguration can expose critical assets within minutes. Automated change monitoring tools (such as AWS Config, Azure Policy, or open-source alternatives like Cloud Custodian) help ensure configuration drift is caught immediately.
• Continuous application security testing: Security testing should be integrated into your CI/CD pipeline, not treated as a pre-launch gate. Each deployment should trigger relevant security scans — SAST, DAST, dependency checks — to provide ongoing security assurance rather than point-in-time snapshots.

The Three Primary Cloud Migration Approaches

Once your team has addressed the risk factors above, you can move to selecting a migration strategy. The right approach depends on your business objectives, timeline, budget, and the characteristics of the workloads being moved. There are three broad strategies most organizations use:

1. Lift and Shift (Rehosting)

Lift and shift involves mapping your existing on-premises hardware or virtual machines to equivalently sized cloud instances with minimal changes to the application itself. For example, if your application server runs on 4 vCPUs, 64 GB of RAM, and 512 GB of local storage, you select a cloud instance type that matches those specifications as closely as possible and move the workload over.

When it works well: Lift and shift is typically fastest to execute and is well-suited to getting out of a data center on a deadline, or as a first step before further optimization.

Key limitation: On-premises infrastructure is typically over-provisioned to handle peak loads because it lacks elastic auto-scaling. When you lift that workload into the cloud at the same static size, you often pay for that over-provisioning continuously — losing one of cloud’s primary cost advantages. This approach is best treated as temporary unless cost is not a concern.

2. Refactor and Re-architect

This approach treats migration as an opportunity to modernize applications so they can take full advantage of cloud-native features — particularly auto-scaling, managed services, and pay-per-use pricing. Rather than lifting existing application architecture intact, teams invest time in re-architecting services to be more performant, more maintainable, and more cost-efficient at cloud scale.

What this might involve:

• Breaking monolithic applications into independently scalable services.
• Replacing expensive commercial middleware or databases with open-source or cloud-native equivalents.
• Adopting managed services (object storage, managed databases, message queues) to reduce operational burden.
• Building for horizontal scaling rather than vertical scaling.

Trade-off: This approach requires more time and engineering investment upfront but typically yields the best long-term cost, performance, and reliability outcomes.

3. Shelve and Spend (Replace with SaaS)

The third strategy involves retiring an existing on-premises application entirely and replacing it with a SaaS offering. Rather than migrating the workload at all, you buy the capability as a service.

A common example is Human Capital Management (HCM) systems. Many organizations run legacy HCM platforms — often a collection of separate codebases joined together with a relational database — that are expensive to maintain and difficult to extend. Migrating to a purpose-built SaaS HCM platform modernizes the business logic, eliminates the infrastructure operational burden entirely, and shifts responsibility for uptime and security to the SaaS provider.

When to consider it: This approach is most appropriate for non-differentiating business functions where a mature SaaS market exists — HR, payroll, CRM, email, collaboration tools — and where the cost and complexity of running the service yourself exceeds the value of owning it.

Key consideration: SaaS adoption introduces its own vendor dependency, data portability, and integration risks. These should be evaluated carefully before committing, particularly for business-critical functions.

Choosing the Right Approach

In practice, most organizations use a combination of all three strategies across different workloads. A large enterprise migration might lift-and-shift legacy infrastructure to exit a data center lease, re-architect its customer-facing applications for scale and resilience, and simultaneously move internal tools like HR and email to SaaS platforms.

The key is to make deliberate choices based on workload characteristics and business goals — rather than defaulting to lift-and-shift for everything and inheriting its cost and technical debt consequences at cloud scale.

Addressing compliance, data governance, and security architecture before any of these migration strategies begin is what separates organizations that migrate successfully from those that create new problems in the cloud while solving old ones on-premises.

This article walks through the core DevOps philosophy known as The Three Ways, then shows concretely how each principle maps to modern application security practice—producing what the industry now calls DevSecOps.

The Three Ways: DevOps Core Principles

The Three Ways originate from the thinking popularised in The DevOps Handbook and the Phoenix Project novel. They describe the progression of organisational maturity a team must achieve to deliver software reliably and at pace.

The First Way – Flow

Flow describes the smooth, left-to-right movement of work from development through testing and into production. Every obstacle that slows or stops that movement—long environment provisioning times, manual testing cycles, large infrequent deployments—increases risk and delays value delivery.

Practices that increase flow include:

• Infrastructure as code (IaC): Tools such as Ansible, Chef, Terraform, or Docker allow environment definitions to live in source control. Environments become reproducible and disposable, eliminating the risk of manual configuration drift.
• Deployment pipelines: A CI/CD pipeline—implemented with Jenkins, GitLab CI, GitHub Actions, or similar—runs on every commit, building, testing, and deploying to production-like environments automatically.
• Fast automated tests: The pipeline must break on test failure. Automated tests give the team confidence that each change works before it progresses downstream.
• Small batch development: Committing small, focused changes reduces the blast radius of any single deployment. Small change equals small risk.
• One-click or automated production deployments: When IaC, pipelines, and small batches are in place, pushing to production becomes a low-drama event rather than a scheduled outage window.

The Second Way – Feedback

Fast flow without feedback produces velocity in the wrong direction. The Second Way focuses on creating short, amplified feedback loops so that problems surface as close to their origin as possible.

Key feedback mechanisms include:

• Code reviews: Synchronous or asynchronous peer review catches defects and knowledge gaps before code merges.
• A/B testing: Releasing a feature to a subset of users lets the team validate whether the feature actually changes behaviour before a full rollout.
• Production telemetry: Metrics, logs, and distributed traces provide a real-time view of system health and user behaviour, allowing rapid reaction to regressions.
• Business-outcome instrumentation: The most mature teams tie telemetry directly to business KPIs, so they can see whether a code change moved the needle on revenue, engagement, or another strategic goal.

The Third Way – Continual Learning and Experimentation

The Third Way asks organisations to build a culture in which learning is a structured daily activity rather than a post-mortem afterthought. Netflix’s Chaos Engineering programme is a well-known example: deliberately injecting failure into production surfaces weaknesses that would otherwise remain hidden until a real incident.

The cultural prerequisites are:

• Treating failures as information, not blame triggers.
• Running deliberate experiments and measuring outcomes.
• Creating mechanisms—wikis, internal talks, blameless post-mortems—for sharing learnings across teams.

How Application Security Fits the Three Ways

With the Three Ways established, it becomes straightforward to see where security belongs—not at the end of the pipeline as a gate, but embedded throughout as a first-class engineering concern.

Security Flow: Shift Left Without Slowing Down

Security flow means reducing the time between introducing a vulnerability and detecting and fixing it—ideally to zero by preventing vulnerabilities from being introduced in the first place.

Secure infrastructure as code: When server configuration is codified, it can be reviewed, version-controlled, and tested. A forgotten firewall rule or insecure default cannot survive a code review the way it might survive a rushed manual server build.

Reusable secure components: Authentication, authorisation, session management, and input validation should be centralised into shared libraries. Individual feature teams then consume proven, audited implementations rather than re-inventing security controls—and re-introducing the same bugs.

Automated security tests in the pipeline: Functional tests prove the application does what it should. Security tests prove it refuses to do what it should not. Both belong in the same pipeline, running on every commit. Concrete examples include:

• Testing that an unauthenticated request returns 401 Unauthorized.
• Testing that an authenticated but unauthorised request returns 403 Forbidden.
• Testing that CSRF tokens are validated on state-changing endpoints.
• Inspecting HTTP response headers for a valid Content-Security-Policy to prevent clickjacking.

These tests are straightforward to write alongside integration tests and add negligible overhead to a build.

Security-aware code review: Small batch sizes make code reviews faster and more effective for security. Reviewers can use checklists derived from the OWASP Top 10 and the SANS/CWE Top 25 Most Dangerous Software Weaknesses to ensure the highest-risk categories receive deliberate attention at review time.

Security Feedback: Fast, Automated, Actionable

Traditional security reviews—performed once per release cycle by an external team—violate the feedback principle. By the time findings are reported, the code has moved on; fixes require expensive rework, and they often get deferred to protect the deadline. The solution is to make security feedback continuous.

Static Application Security Testing (SAST): SAST tools analyse source code or compiled binaries for patterns associated with known vulnerability classes. They can run as a pipeline stage on every commit. Important caveats: SAST tools produce false positives, different tools yield different results, and no tool replaces human judgement. SAST is a layer in a defence-in-depth strategy, not a complete solution. Commercial SAST tools can also carry significant licensing costs, so evaluate ROI carefully.

Dynamic Application Security Testing (DAST): Where SAST reads the code, DAST attacks the running application in a test environment, attempting to exploit common vulnerabilities such as SQL injection, cross-site scripting, and broken authentication. A DAST tool acts as a tireless automated penetration tester. Findings can be fed automatically into a backlog—raising a ticket in Jira or a similar tracker—so that vulnerabilities are prioritised and resolved alongside other work rather than handled through a separate, opaque process. DAST tends to surface vulnerabilities that static analysis misses because it observes real runtime behaviour.

Continual Security Learning: Adapting to New Threats

The threat landscape evolves constantly. New CVEs are published daily; attack techniques mature; previously safe libraries develop exploitable flaws. A DevSecOps culture treats this as a source of continuous learning rather than a source of paralysis.

Human learning: Developers should maintain awareness of vulnerabilities relevant to the technologies they use. Security-focused Slack channels, threat intelligence feeds, and regular internal knowledge-sharing sessions are practical mechanisms.

Runtime Application Self-Protection (RASP): A RASP tool is instrumented into the application runtime. It monitors execution from the inside—observing function calls, data flows, and HTTP interactions—and can detect and block attacks in progress. When a new vulnerability is disclosed for a technology in your stack, a RASP signature can provide a temporary virtual patch immediately, buying time for a proper code fix to be developed, reviewed, and deployed through the pipeline. OWASP’s AppSensor project is one open framework for implementing this concept.

RASP is not a replacement for secure coding. It is a safety net—most valuable in mature programmes where the foundational practices are already in place.

The Path to DevSecOps: A Practical Roadmap

Attempting to implement every practice simultaneously will overwhelm teams and ensure nothing sticks. A phased approach delivers incremental value and builds internal security expertise over time.

1. Implement automated security tests. Start with the fundamentals: authentication enforcement (401/403 responses), CSRF validation, and missing security headers. These tests are cheap to write and deliver immediate pipeline feedback.
2. Introduce security-aware code review. Equip reviewers with OWASP Top 10 and SANS Top 25 checklists. Focus initial effort on high-risk areas: authentication logic, session management, database query construction, and data serialisation.
3. Harden your infrastructure code. Audit existing IaC definitions for misconfiguration—open ports, default credentials, missing encryption settings—and codify the correct configuration so it is enforced on every environment build.
4. Evaluate and adopt SAST and DAST tools. Once the team has baseline security knowledge, automated scanning tools add an additional detection layer. If budget is constrained, DAST generally offers better value per dollar because it finds runtime vulnerabilities that static analysis misses.
5. Adopt RASP for production protection. This step suits more mature programmes. A well-configured RASP provides a rapid response capability for zero-day and newly disclosed vulnerabilities while permanent fixes move through the pipeline.

Conclusion

DevOps and application security are not in tension—they are natural allies. Both are fundamentally about reducing risk: DevOps reduces the risk of slow, unreliable delivery; security reduces the risk of exploitation and data loss. Applying the principles of Flow, Feedback, and Continual Learning to security transforms it from an end-of-cycle gate into a continuous engineering capability embedded in daily development work.

The result—DevSecOps—produces software that is both delivered faster and more defensible in production than software built under either a pure-speed or a traditional security-gate model.