1. Lower Infrastructure and Server Costs

Traditional on-premises infrastructure requires significant upfront capital expenditure. Organizations must purchase servers, networking hardware, and licenses sized for peak load — meaning that capacity often sits idle during off-peak periods, wasting money.

Cloud computing flips this model. Most providers operate on a pay-as-you-go or subscription basis, so you pay only for the resources you consume. This shift from capital expenditure (CapEx) to operational expenditure (OpEx) makes budgeting more predictable and eliminates the cost of over-provisioning. Organizations can also reduce their physical data center footprint, lowering costs related to server hardware, on-site software licensing, power, cooling, and dedicated IT staff.

2. Improved Security Posture

Security is frequently cited as a concern about cloud adoption, but major cloud providers invest heavily in security controls that many individual organizations cannot replicate on their own. These typically include:

• Encryption of data in transit and at rest
• Role-based access controls (RBAC) and identity management
• Physical security at data centers (biometric access, 24/7 monitoring)
• Compliance certifications such as SOC 2, ISO 27001, and PCI DSS
• Automated threat detection and logging

That said, cloud security operates on a shared responsibility model. The provider secures the underlying infrastructure, but customers remain responsible for securing their applications, access credentials, and data configurations. Teams that understand this boundary and configure their environments correctly can achieve a significantly stronger security posture than a typical self-managed data center.

3. Automatic Software Updates and Patch Management

Keeping software patched and up to date is one of the most time-consuming and risk-prone responsibilities in IT operations. Missed patches are a leading cause of security breaches, yet applying them requires careful scheduling, testing, and coordination.

Cloud providers handle infrastructure-level patching — operating systems, hypervisors, and managed service runtimes — automatically and continuously. For Software-as-a-Service (SaaS) products, application updates are rolled out by the vendor without requiring any action from customers. This reduces the maintenance burden on internal teams and ensures that environments stay current with security fixes and feature improvements without scheduled downtime windows.

4. Data Insights and Built-in Analytics

Modern cloud platforms provide integrated analytics, monitoring, and observability tooling that makes it easier to extract actionable insights from your data. Services such as managed data warehouses, streaming analytics pipelines, and dashboarding tools are available as first-class offerings on major cloud platforms.

For engineering and operations teams, this means:

• Centralized logging and metrics across distributed services
• Custom dashboards and alerting without maintaining your own monitoring stack
• Usage and cost analytics to optimize resource allocation
• Business intelligence tools that connect directly to cloud data stores

The ability to analyze data at scale — without provisioning and maintaining your own analytics infrastructure — is a meaningful operational advantage, particularly for teams practicing data-driven decision making.

5. Enhanced Team Collaboration

Cloud-hosted tools and shared storage make real-time collaboration straightforward regardless of where team members are located. Engineers can work on shared codebases, pipelines, and documentation without VPN-dependent access to on-premises file servers.

For DevOps teams specifically, cloud-native CI/CD platforms, shared artifact registries, and infrastructure-as-code repositories hosted in the cloud make it easier to standardize workflows across distributed or remote teams. Changes are visible, version-controlled, and accessible to all authorized collaborators immediately.

6. Access to the Latest Software and Features

Cloud providers and SaaS vendors continuously roll out new features, performance improvements, and integrations. Because updates are delivered centrally, all customers gain access to new capabilities at the same time — without requiring in-house upgrade projects or compatibility testing against aging infrastructure.

This continuous delivery model keeps teams competitive and reduces the risk of running software versions that are no longer supported. For operations teams, it also means access to new automation, security, and cost-optimization features as soon as they become available.

7. Reliable Disaster Recovery and Business Continuity

Data loss or prolonged downtime — whether caused by hardware failure, human error, ransomware, or a natural disaster — can have severe consequences for any business. Building a robust disaster recovery (DR) solution on-premises has historically required significant investment in redundant hardware, off-site backup facilities, and complex failover procedures.

Cloud computing dramatically lowers the barrier to effective DR:

• Geo-redundant storage automatically replicates data across multiple physical locations
• Managed backup services provide point-in-time recovery with configurable retention policies
• Multi-region deployments allow workloads to failover to a healthy region with minimal manual intervention
• Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO) that would be expensive to achieve on-premises become practical in the cloud

The result is a more resilient architecture that can recover quickly from a wide range of failure scenarios, often with lower cost and complexity than equivalent on-premises DR setups.

Additional Environmental Benefits

Beyond the direct operational benefits, cloud computing can contribute to an organization’s sustainability goals. Shared multi-tenant infrastructure allows providers to achieve higher server utilization rates than most individual data centers, improving overall energy efficiency. Consolidating workloads into well-run hyperscale facilities also reduces the total hardware footprint and associated electronic waste. Organizations reducing or eliminating their own data centers further cut energy consumption and associated emissions.

Conclusion

The case for cloud computing is well established, but the advantages are not automatic. Realizing the cost, security, and resilience benefits described above requires deliberate architecture decisions, proper access configuration, and ongoing governance. Teams that invest in understanding the shared responsibility model, optimize resource usage to avoid cloud sprawl, and treat cloud infrastructure as code will see the strongest returns. For most organizations, the question is no longer whether to adopt cloud computing, but how to do so effectively.

DevOps has come a long way since it got underway in full force nearly ten years ago.  As was recently made clear at this year’s DevOps Enterprise Summit (DOES) in Las Vegas, DevOps organizations have been successful when it comes to knocking down organizational silos, optimizing the delivery of software services and functionality, and shortening the time it takes to deliver digital value to customers. DevOps organizations are delivering better business outcomes.

However, one area where there’s still much more work to do remains the stubborn area of software security.

Based on the presentations I attended and my discussions with DevOps practitioners at DOES, it’s clear that most mid-sized and large organizations are running multi-cloud and on-premises environments, and they’re all in when it comes to virtualization, containerization, and microservices.

While all of this is helping to speed the delivery of software services, it is also increasing management and security complexity in some ways.

Organizations are taking steps to help better secure their systems. In one talk I attended, DevOps for the Enterprise: 2018 Trends and Insights, Wesley Pullen, chief strategy officer at Electric Cloud said that they are seeing enterprises embrace artificial intelligence and machine learning as ways to identify patterns using in-depth statistical analysis, predict future risk using previous patterns, and to provide recommendations to reduce risk, Pullen said.

The conversations at the summit reminded me of the findings from this year’s Sonotype report, DevSecOps Realities and Opportunities, released this spring. “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,” Jay Lyman, principal analyst at 451 Research said when the report was published. “In many cases, security testing is not being integrated often or early enough in the process for organizations to fully benefit from reduced risk and rework headaches,” he said.

The report is based on the survey results of 350 decision makers from large enterprises across numerous industries.

The study found half of CI/CD pipelines are equipped with application security testing. It’s not as if respondents don’t know better, in the survey they themselves stated the importance of application security.

What are some of the holdbacks to successful DevSecOps? The DevSecOps Realities and Opportunities report found lack of automation and consistency to be big drivers. That’s no surprise, and security automation is a subject we’ve been pounding on here for some time. See our previous posts on this here and here. The TL;DR takeaway from those posts is the only way to keep up with the required software tests is to automate as many tests and processes as can be reasonable automated.

When it comes to moving testing into continuous delivery, another common challenge that has been known to be a bugaboo in security forever: false positives. When teams move automated testing tools earlier into the software development cycle, they often get plagued with false positives. The key here is to get developers trained in application security and to have application security experts embedded early in the design process. Having testing directly in the integrated development environment can also help developers to spot flaws early. It may make sense to also play triage to an extent, so that low level and easily fixable defects move forward so they can be remediated later.

The Sonotype’s DevSecOps survey confirmed that false positives are a serious challenge with 46 percent of respondents. The report stated that “the noise of false positives can drown out the benefits of security scanning and other elements in CI/CD processes. We believe organizations can help address this issue by choosing security software and services that specialize in effectively reducing false positives and the noise that comes with them.” The report authors cited static application security testing be tuned to every organization’s unique environment to reduce false positives.

Another interesting area that the DevSecOps Realities and Opportunities report found that known at-risk open source software components being installed is a critical application security challenge in continuous pipelines. Surprisingly, 40 percent of organizations either don’t look for vulnerable open source software or they think they aren’t using any open source components. The latter is highly unlikely as the vast majority of software utilize open source and this is especially so in CI/CD environments.

What was also interesting from the conference in talking with various organizations is that DevOps may have a foothold in organizations, it’s not evenly distributed — even if the benefits of DevOps have been realized. This, too, was reflected in the DevSecOps Realities and Opportunities report. Of its survey respondents, “36 percent reported developer/administrator teams were focused on continuous integration. Another 35 percent of respondents stated teams focused on continuous delivery, and 35 percent also reported a DevOps focus, although DevOps was ranked lowest in most industries, including traditional retail, SaaS and healthcare.”

Fortunately, the survey also found that one of the big drivers of DevSecOps and the integration of good security practices and testing into CI/CD processes. The survey found that that software quality was ranked highest at 75 percent of firms indicating its importance. Software quality even beat out compliance and regulatory requirements, which ranked 68 percent. Interesting, risk avoidance over ranked at 64 percent while 48 percent believed that application security testing can slow down the release process.

The challenges reflected in the survey have been reflected in related surveys. Enterprises know the benefits of DevOps, they understand that security needs to be integrated into their processes, and they have yet to properly do so. This was also what was largely reflected in my discussions this year at the DevOps Enterprise Summit, as well. Some may find this state of affairs disheartening, especially after a focus on the importance of web application security for nearly 20 years. But I don’t.

Still, I see hope. I think organizations are on the right path to achieving healthy states of DevSecOps. They’re learning how to deploy the right tools and processes to maintain the right balance between the speed of software delivery and the level of security that software needs to be compliant and resilient form attack.

The answer is not simply to hire more people — it is to make the people you have dramatically more effective. Organizations that embed security thinking across their engineering and operations teams multiply the impact of every security hire. Below are five concrete tips that help you do exactly that.

1. Get Your DevOps Team On Board With SecOps

If your development and operations teams are already working in a DevOps model, the next logical step is to extend that collaboration to security — commonly called DevSecOps or SecOps. Train the people who write and deploy code to treat security as part of their everyday responsibility, not as someone else’s problem to clean up later.

This cultural shift must be driven from leadership. When security metrics appear on the same dashboards as deployment frequency and uptime, engineers begin to internalize security as a first-class concern. Reinforce that expectation in code-review checklists, sprint retrospectives, and performance evaluations.

2. Bring Security Alerts Into DevOps Workflows

Asking developers to log into a dedicated security console they rarely visit almost guarantees that alerts will be ignored or actioned too slowly. Instead, deliver security signals where engineers already spend their time.

ChatOps platforms such as Slack, Microsoft Teams, or Mattermost are an effective bridge. Routing security alerts into a dedicated channel — or even into team-specific channels — means engineers see relevant alerts in context, can discuss them immediately, and can escalate or dismiss without context-switching to an unfamiliar tool.

The lower the friction, the more consistently your team will respond to alerts in a timely and repeatable way. Enrich alerts with contextual metadata — the host, the process, the user account involved — so the people reviewing them can triage quickly without needing deep security expertise.

3. Extend Security Visibility Across the Whole Organization

Do not stop at the engineering team. When security awareness tools and channels are accessible to everyone — product managers, support staff, finance — you gain a much larger set of eyes watching for anomalies.

Practical ideas include:

• A company-wide #security Slack channel where anyone can flag suspicious emails, unusual login prompts, or strange behavior.
• Automated alerts that ping the individual user whose action triggered a security event, asking them to confirm or deny — this dramatically speeds up triage.
• Regular, short security digests that keep the broader team informed about active threat patterns without overwhelming them.

Building this culture of openness and shared responsibility makes your organization a harder target and reduces the burden on your dedicated security staff to investigate every false positive alone.

4. Educate and Train the Entire Team

Workflow integration only goes so far if people do not understand what they are looking at. Basic security training for every employee — not just engineers — is a high-leverage investment. Key topics to cover include:

• Phishing and social engineering: How to recognize suspicious emails, links, and requests, and what to do when you spot them.
• Authentication hygiene: How to use multi-factor authentication (MFA), password managers, and single sign-on (SSO) tools correctly.
• Network safety: Which networks are safe to use, when to use a VPN, and how to stay secure while traveling for work.
• Physical security basics: Locking screens when stepping away, never plugging in unfamiliar USB devices, and following a clean-desk policy.

The goal is to raise the organization’s collective security IQ to a level that makes you an unappealing target. A well-trained team generates fewer incidents, which directly reduces the workload on your security staff.

5. Choose Comprehensive, Integrated Security Tools

Tool sprawl is a silent productivity killer for security teams. When alerts come from a dozen disconnected systems, analysts spend more time correlating data than actually responding to threats. Aim for a single-pane-of-glass approach: one platform — or a tightly integrated set of platforms — that gives your security team a unified view of your network, infrastructure, and application layer.

When evaluating security platforms, look for native integrations with the tools your teams already rely on, such as:

• Incident management tools (e.g., PagerDuty, VictorOps / Splunk On-Call)
• Chat and collaboration platforms (e.g., Slack, Microsoft Teams)
• Cloud provider consoles and APIs (e.g., AWS Security Hub, Azure Defender, GCP Security Command Center)
• CI/CD pipelines, so that security scanning happens automatically at build time

A unified toolset enables proactive vulnerability management: your team can identify and remediate weaknesses before they are exploited, rather than scrambling to contain a breach after the fact. Over time, it also builds an institutional knowledge base about your security posture and how your systems and users behave under normal conditions — making anomalies far easier to spot.

Putting It All Together

Security talent will continue to be expensive and difficult to hire for the foreseeable future. Rather than waiting for the market to change, forward-thinking organizations are restructuring how security work gets done — distributing ownership across development, operations, and the entire business, and equipping everyone with the tools and knowledge they need to contribute.

By embedding security into existing DevOps workflows, training your full team, and consolidating your tooling, you give your dedicated security professionals the leverage they need to operate strategically rather than reactively. The result is a more resilient organization and a security team that can actually scale with the business.

Originally sourced from business2community.com.

The DevSecOps Debate: Two Seemingly Contradictory Principles

The RSA Conference — one of the major annual enterprise security events — has increasingly devoted track time to security in the software development process. Among the topics gaining traction is the convergence of security and DevOps, variously branded as SecDevOps or DevSecOps. Strip away the buzzwords, though, and there are two foundational principles worth examining carefully:

1. Security is a process, not a product.
2. Security is about behavior, not process.

At first glance, these sound contradictory. But read them end to end — behavior first, then process — and they form a coherent philosophy:

Security is about behavior, not process. Security is a process, not a product.

Behavior is the foundation. Process is what you build on top of it. Products and tools come last — not first.

Why Security Teams Can’t Scale Through Process Alone

A widely cited observation in security circles is that most organizations have roughly 1.6 security professionals for every 100 developers. Whether or not that exact figure holds universally, the underlying point is undeniable: security teams are dramatically outnumbered.

This ratio makes one thing clear — a security team cannot audit, review, and remediate its way to secure software by acting as a gate at the end of the pipeline. There simply aren’t enough people. The only scalable approach is to change the security culture within the development team itself: to create a security mindset rather than a security checkpoint.

This is the behavioral dimension. Until developers understand why security matters — not just that it’s required — any process imposed on them will be treated as friction rather than value.

Building a Security Culture: Start With the Why

Training in foundational security concepts is a practical starting point. When developers understand the real-world consequences of common vulnerabilities — SQL injection, insecure deserialization, broken authentication — they are far more likely to internalize secure coding practices rather than treating security reviews as a bureaucratic hurdle.

Effective approaches to building a security culture include:

• Secure coding training tailored to the languages and frameworks the team actually uses.
• Threat modeling workshops that involve developers early in the design phase, not after code is already written.
• Security champions programs — embedding a security-aware developer within each team who serves as a local resource and advocate.
• Blameless post-mortems on security incidents, treating them as learning opportunities rather than occasions for punishment.
• Making security visible in sprint reviews and team metrics, so it isn’t invisible until something goes wrong.

Establishing a Security Process: The How Follows the Why

Once a team has the cultural foundation — once developers genuinely care about building secure software — you can define a repeatable security process. A well-known reference point is Microsoft’s Security Development Lifecycle (SDL), which structures security activities across each phase of development: requirements, design, implementation, verification, and release.

The key principle when establishing a process is to start simple. A minimal, consistently followed process beats an elaborate one that gets bypassed under delivery pressure. Typical components of a pragmatic DevSecOps process include:

• Threat modeling during design to identify risks before a line of code is written.
• Peer code review with a security lens, using defined criteria for what reviewers should look for.
• Static Application Security Testing (SAST) integrated into the CI pipeline to catch common vulnerabilities automatically.
• Software Composition Analysis (SCA) to identify known vulnerabilities in open-source dependencies.
• Dynamic testing (DAST) against running services as part of integration or staging pipelines.
• Security sign-off criteria as part of the definition of done, not as a separate post-development gate.

Tools Are an Amplifier, Not a Substitute

A common failure pattern in DevSecOps adoption is jumping straight to tooling. The thinking goes: “If we deploy a SAST scanner, our code will be secure.” It won’t be — at least not without the cultural and process foundations in place first.

A telling example: a static analysis tool deployed at one organization surfaced thousands of issues. Management was satisfied with the dashboards. Developers, having no security process or culture to anchor the findings to, ignored the output entirely. The tool generated noise, not improvement.

Tools work when:

• Developers already understand what the findings mean and why they matter.
• There is a defined process for triaging, prioritizing, and remediating findings.
• The tool output is actionable — low false-positive rates, clear remediation guidance, and integration with the existing workflow (e.g., tickets filed automatically in the team’s issue tracker).
• Teams have the time and support to act on findings, not just generate them.

In short: tools amplify an existing process. They cannot replace one that doesn’t exist.

The Open Source Dimension

For teams building open-source software, the challenge is compounded. Contributions come not only from employees but from a globally distributed community of external contributors, each with varying security awareness and backgrounds.

The fundamentals, however, remain identical. The goal is community buy-in — making the importance of security a shared value that contributors understand and embrace, rather than a set of rules imposed by maintainers. Practical measures for open-source projects include:

• A clearly documented security policy (commonly a SECURITY.md file) covering responsible disclosure, supported versions, and how to report vulnerabilities.
• Automated security checks on pull requests, so every contribution is screened consistently regardless of who submits it.
• A contributor guide that includes security expectations alongside code style and testing requirements.
• A private channel for reporting security issues, so vulnerabilities are not disclosed publicly before a fix is available.

The Sequence That Works

To summarize the approach in the order that it actually has to happen in practice:

1. Build behavioral change first. Invest in training, champions, and culture so developers care about security outcomes.
2. Define a simple, repeatable process. Identify where in the SDLC security activities belong and make them part of normal workflow.
3. Select tools that reinforce the process. Choose tooling that integrates with your CI/CD pipeline and produces actionable, low-noise output.
4. Iterate and mature. Start simple, measure outcomes, and gradually expand coverage as the team’s security capability grows.

Security products are everywhere. Security behavior is rare — and it is behavior, not a purchase order, that actually reduces risk.

The Scale of the Problem

Software development has never moved faster—and neither has the attack surface that comes with it. According to the 2017 Application Security Report, approximately 111 billion new lines of software code were projected to be written in 2017 alone. Each line introduces the possibility of a defect, and a meaningful subset of those defects are exploitable security vulnerabilities.

The report was blunt about the state of application security at the time: “Applications have become inviting targets for malicious actors, but securing those programs has proven to be challenging to both security teams and developers. Too often, key vulnerabilities get buried in a blizzard of information created by tools unable to prioritize defects in software.”

That signal-to-noise problem—where developers are overwhelmed by vulnerability reports they cannot prioritize—remains one of the central challenges in AppSec today.

Why Application Security Is a Distinct Discipline

A common misconception is that cybersecurity is primarily a network-layer problem—firewalls, intrusion detection, endpoint protection. Application security operates at a different layer entirely: the code itself.

Anita D’Amico, then CEO of Code Dx, framed the human side of the challenge clearly: “In general terms, it means getting the workforce to comply with security processes. With respect to application security, it means getting the software developers and testers to recognize the need to find and fix application vulnerabilities early in the SDLC.”

Shifting security left—catching vulnerabilities during development rather than after deployment—reduces remediation cost, risk, and time to market for secure software. This principle was well established by 2017 and remains foundational to DevSecOps practice.

The Recommended Approach: SAST + DAST + RASP

The report advocated for a hybrid testing model that combines three complementary techniques:

• Static Application Security Testing (SAST): Analyzes source code, bytecode, or binaries without executing the application. SAST tools can be integrated directly into the IDE or CI pipeline, giving developers immediate feedback on vulnerabilities as they write code.
• Dynamic Application Security Testing (DAST): Tests a running application by simulating external attacks. DAST finds vulnerabilities that only manifest at runtime—such as authentication flaws, injection points, and insecure configurations—that static analysis cannot detect.
• Runtime Application Self-Protection (RASP): Embeds security controls directly into an application’s runtime environment. RASP can detect and block attacks in real time, from within the application itself, rather than relying solely on perimeter defenses.

The report noted that RASP’s value extends beyond production protection: “RASP was created to protect applications under attack in real time, but, when combined with dynamic testing, it has proven to be useful in helping developers prioritize vulnerability findings. That not only reduces the risk of an app making it to market with a major security defect but it accelerates the time it takes to put a secure app in a user’s hand.”

Integrating AppSec into the Development Workflow

One of the report’s core arguments was that security testing must become a native part of the development process, not an afterthought or a separate audit gate. D’Amico described the practical implementation:

“Software developers and testers can build security testing directly into their development environment. They can make it a normal part of the development process, not a resource-intensive additional activity. A new breed of AppSec tools, called Application Correlation and Management Systems, embeds the source code testing tools into the integrated development environment, and interfaces with continuous build servers like Jenkins and with issue trackers like JIRA.”

This integration pattern—AppSec tooling connected to the IDE, CI server, and issue tracker—is now a standard expectation in mature DevSecOps pipelines. The report was describing, in 2017, an architecture that many organizations are still working to fully implement.

The Role of Automation

Given the volume of code being produced, manual security review cannot scale. The report highlighted automation as a critical enabler—automated scanning must be embedded in the build pipeline so that every commit is evaluated for security defects without requiring manual intervention for routine checks.

Automation also addresses the prioritization problem. When tools generate thousands of findings, developers lose confidence in the results and begin to ignore them. Modern Application Correlation and Management Systems aim to aggregate results from multiple tools, deduplicate findings, and surface the highest-risk issues first—making the output actionable rather than overwhelming.

Market Context (2017 Projections)

The report projected significant market growth for application security, estimating expansion from approximately US$2.24 billion in 2016 to $6.77 billion by 2021. Steven C. Morgan, founder and editor-in-chief of Cybersecurity Ventures, noted that AppSec was expected to outpace overall cybersecurity market growth:

“While we anticipate 12% to 15% year-over-year growth of the cybersecurity market through 2021, our synthesis of various research has led us to expect the application sector will grow by 16% to 18% during that period.”

These figures are presented as they appeared in the original 2017 report. Actual market outcomes may differ.

Key Takeaways for DevOps and Security Teams

• Volume demands automation: At the scale of hundreds of billions of lines of code annually, manual review is not a viable primary control. Automated SAST and DAST in CI/CD pipelines are baseline requirements.
• Prioritization matters as much as detection: Tools that generate unprioritized lists of thousands of vulnerabilities create alert fatigue. Invest in tooling that ranks findings by exploitability and impact.
• RASP complements preventive testing: Even rigorous pre-deployment testing will miss some vulnerabilities. RASP provides a runtime safety net and can generate telemetry useful for improving testing coverage.
• Security must be a developer workflow concern: Security gates at the end of the SDLC are too slow and too expensive. Embedding security tooling in the IDE and CI server makes it part of normal development rather than an exception process.
• AppSec is not the same as network security: Organizations that focus exclusively on perimeter and network defenses leave application-layer vulnerabilities unaddressed. A mature security posture requires both.

The 2017 Application Security Report was published by Cybersecurity Ventures and sponsored by Code Dx. Original coverage appeared on SD Times.

The Persistent Gap Between Development and Security

Despite years of industry advocacy for “baking in” security from the start, many development teams still treat it as a final-phase activity — something that gets reviewed after the code is written, tested, and nearly ready to ship. The result is predictable: vulnerabilities found late are expensive to fix, disruptive to release schedules, and often negotiated away rather than resolved.

Speaking at the Checkmarx “Shift Left” conference in central London, security researcher Troy Hunt made the case that this pattern is not inevitable — but breaking it requires structural changes to how teams think about, measure, and communicate security.

The Problem with Late-Stage Security Reviews

Hunt pointed out that measuring code security is genuinely difficult. Unlike a failing unit test, a security flaw does not always produce an obvious signal. You can look at code that has already shipped and struggle to determine whether it is safe or subtly broken — until someone exploits it.

What is clear, Hunt argued, is the cost gradient: the later a vulnerability is found, the more expensive it is to address. A flaw caught during design or early development may require a minor code change. The same flaw discovered during a post-release penetration test could require architecture rework, emergency patching, customer notification, and regulatory scrutiny.

Hunt illustrated the problem with a fictional character he called “Vlad” — the security person who arrives at the end of the development cycle bearing bad news about flaws the team no longer has the schedule or budget to properly fix. Vlad is not the villain; Vlad is the symptom of a process that has already failed.

The Standoff Between Developers and Security Teams

A recurring theme in Hunt’s talk was the cultural friction between development and security teams. Security practitioners grow frustrated when developers repeatedly introduce the same classes of vulnerability. Developers feel ambushed when security blocks a release at the last moment. Businesses, caught in the middle, often push for shipping over safety because they do not fully grasp the risk.

Hunt was direct about this: “We have got to be better with the ‘standoffishness’ between developers and security people; we are all trying to achieve the same thing.”

The tension is real, but it is not irresolvable. Both groups share the goal of shipping software that works correctly and does not harm users. The disconnect is usually about process, timing, and communication — not fundamental incompatibility.

What “Shifting Left” Actually Means in Practice

“Shifting left” means moving security activities earlier in the software development lifecycle (SDLC) — ideally starting at the design phase rather than the testing phase. Hunt outlined several concrete practices that support this:

• Developer security training: Developers who understand common vulnerability classes — SQL injection, cross-site scripting, insecure deserialization — are less likely to introduce them in the first place. Training does not need to be deep security expertise; it needs to be enough awareness to recognise dangerous patterns.
• Static code analysis (SAST): Tools that analyse source code without executing it can flag known vulnerability patterns early, ideally integrated directly into the IDE or pull request workflow so feedback is immediate rather than batched into a late-stage report.
• Continuous integration (CI) security gates: Embedding security scans into the CI pipeline means every commit is checked automatically. This normalises security as part of the build process rather than an external audit.
• Dynamic analysis (DAST): Running the application and probing it for vulnerabilities — either through automated scanners or manual testing — catches issues that static analysis misses, such as runtime configuration problems or logic flaws.
• Penetration testing: Hunt was explicit about the value of skilled pentesters. Where automated tools follow known patterns, a good pentester brings creative, adversarial thinking that can surface complex, chained vulnerabilities no scanner would find.

Critically, Hunt framed these not as competing approaches but as complementary layers. No single technique covers everything. Static analysis finds structural flaws; dynamic analysis finds runtime behaviour; penetration testing finds what both miss. Used together, they provide defence in depth for the development process itself.

The Business Reality: Risk, Not Perfection

Hunt acknowledged a practical constraint that security professionals sometimes resist accepting: businesses will ship software that carries some residual risk. The question is not whether to ship imperfect software — it is whether the risks are understood, documented, and mitigated to an acceptable level.

“Businesses don’t understand the nuances of security and want the website to be live, but we know there are vulnerabilities and things may be exploited, so somewhere there has to be compromise,” Hunt said.

This is not a concession to bad practice. It is a recognition that security must operate within business context. The goal of shifting left is not to achieve zero vulnerabilities before any code ships — it is to reduce the attack surface, catch the highest-risk issues early, and establish processes that continuously improve the security posture of a codebase over time.

Key Takeaways for DevOps and Engineering Teams

• Security reviews at the end of the SDLC consistently produce findings that are too late and too expensive to properly remediate.
• Integrating security tooling into CI pipelines (SAST, dependency scanning, secrets detection) is the most scalable way to enforce baseline security hygiene.
• Developer training on secure coding reduces the volume of vulnerabilities introduced, reducing the burden on security teams downstream.
• Dynamic testing and penetration testing remain valuable precisely because they find what automated static analysis cannot.
• The cultural gap between security and development teams is a process problem. Shared metrics, earlier collaboration, and security embedded in definition-of-done criteria all help close it.
• Security involvement should be a continuous activity throughout the development lifecycle, not a gate at the end.

The tools and practices to shift security left exist and are mature. The remaining challenge is predominantly organisational: making security a shared responsibility rather than a specialist’s veto at release time.