What Is the Cisco 200-901 DEVASC Exam?

The 200-901 DEVASC exam is the single required exam for the Cisco Certified DevNet Associate credential. It is aimed at candidates who want to demonstrate proficiency across software development, automation, and Cisco platform APIs. Passing it signals to employers that you can work across the intersection of networking and modern software practices — a combination increasingly demanded in DevOps and NetOps roles.

Exam Structure and Enrollment

The exam is delivered through Pearson VUE, either at a testing center or via online proctoring. The time limit is 120 minutes. The question format includes multiple-choice, drag-and-drop, and other item types typical of Cisco associate-level assessments.

The exam blueprint covers the following domain areas (refer to the official Cisco exam topics page for the current weighting, as Cisco periodically updates exam blueprints):

• Software Development and Design — software design patterns, version control, basic algorithms and data structures.
• Understanding and Using APIs — REST, RPC, SOAP concepts; authentication methods such as OAuth and API keys; working with JSON and XML payloads.
• Cisco Platforms and Development — using APIs exposed by Cisco platforms including Meraki, Webex, APIC-EM/DNA Center, and IOS XE.
• Application Deployment and Security — container basics, CI/CD pipeline concepts, secure coding practices, and certificate/credential management.
• Infrastructure and Automation — network programmability, infrastructure-as-code principles, and automation tools such as Ansible and Terraform in the context of Cisco environments.

Recommended Background

Cisco does not enforce formal prerequisites for sitting the 200-901 exam, but candidates will have a much easier preparation experience if they have:

• Basic familiarity with at least one scripting or programming language — Python is the most commonly used in Cisco DevNet learning resources and lab exercises.
• Some exposure to networking fundamentals (the equivalent of CCNA-level knowledge is helpful).
• Hands-on experience, even informal, with REST APIs — for example, calling a public API with curl or the requests library in Python.
• Comfort with Linux command-line basics and Git.

Official Cisco Training Options

Cisco offers the official course “Developing Applications and Automating Workflows using Cisco Core Platforms (DEVASC)” in several delivery formats:

• Instructor-led training (ILT) — Live classroom sessions typically spanning five days of instruction, followed by self-study activities. Best for candidates who learn well in a structured, interactive environment.
• Virtual instructor-led training (vILT) — The same curriculum delivered online with a live instructor. Suitable for remote learners who still want real-time interaction.
• E-learning / self-paced — On-demand video modules and labs accessible through Cisco’s learning platforms. Equivalent in coverage to the instructor-led course and flexible enough to fit around a working schedule.

Cisco also maintains the DevNet Learning Labs (developer.cisco.com/learning), a free collection of guided, browser-based labs that let you practice API calls, automation scripts, and platform integrations without needing your own hardware or sandbox. These labs are a high-value, no-cost supplement regardless of which formal course path you choose.

Supplementary Study Materials

Beyond official courseware, most candidates benefit from a layered preparation approach:

• Cisco Press books — The official certification guide for the DevNet Associate is published by Cisco Press and provides detailed chapter-by-chapter coverage aligned to the exam blueprint.
• Practice exams — Timed practice tests help you identify weak areas and build time-management habits under realistic conditions. Look for practice exams from established publishers that clearly state their question sources and update policies.
• Hands-on lab work — No amount of reading replaces actually writing Python scripts that call Cisco APIs, spinning up Docker containers, or building a simple CI/CD pipeline in a sandbox. Cisco DevNet provides free sandboxes for many of its platforms.
• Community resources — The Cisco Learning Network forums and the DevNet community are active spaces where candidates share study notes, clarify exam objectives, and discuss tricky topics.

A Note on Exam Dumps

You will encounter third-party sites offering “exam dumps” — collections of questions purportedly taken from real exam sittings. Before using such materials, be aware of a few important points:

• Policy risk — Cisco’s candidate agreement prohibits the use of unauthorized brain-dump materials. Using them risks disqualification or revocation of earned credentials.
• Accuracy risk — Questions sourced from memory are frequently inaccurate, outdated, or missing context. Studying incorrect answers can actively harm your preparation.
• Skill gap risk — The DevNet Associate exam tests applied skills, including scenario-based questions. Memorising answers without understanding the underlying concepts is unlikely to produce a passing score on modern Cisco exams, and will leave genuine skills gaps when you start the job.

Legitimate practice-question products from established publishers are different from brain dumps: they are written by subject-matter experts, reference published exam objectives, and do not reproduce live exam content. Prioritise those sources.

DevOps and DevNet Career Outlook

Demand for engineers who can bridge networking infrastructure and software automation has grown steadily as organisations adopt cloud-native architectures and infrastructure-as-code practices. The DevNet Associate credential demonstrates a concrete, vendor-validated skill set that is relevant to roles such as DevOps engineer, network automation engineer, and cloud infrastructure developer. Salary ranges for these roles vary significantly by region, industry, and experience level — consult current data from sources such as the Bureau of Labor Statistics, LinkedIn Salary, or Glassdoor for figures relevant to your location and experience.

Next Steps

• Review the current exam topics on the Cisco certification page for 200-901 DEVASC to confirm the latest blueprint.
• Create a free account on developer.cisco.com to access DevNet Learning Labs and sandbox environments.
• Build a structured study plan that allocates time to each exam domain, with dedicated hours for hands-on lab practice.
• Schedule your exam through Pearson VUE once you are consistently scoring well on timed practice assessments.

The Cisco DevNet Associate certification is a practical entry point into the growing field of network and infrastructure automation. Approached with genuine hands-on practice and well-sourced study materials, the 200-901 exam is an achievable and career-relevant milestone.

Google Cloud Expands Its Certification Portfolio

Google Cloud announced two new certifications aimed at addressing real-world skills gaps in enterprise cloud adoption: the Google Cloud Certified Fellow programme for senior technical leaders, and the Professional Cloud DevOps Engineer certification for practitioners focused on reliability and delivery velocity. Together, the two credentials cover opposite ends of the cloud career ladder — strategic leadership and hands-on engineering.

Google Cloud Certified Fellow: Recognition for Anthos Experts

The Google Cloud Certified Fellow programme is an invitation-only credential designed for technical leaders who have demonstrated deep expertise in designing enterprise solutions on Anthos, Google’s open hybrid and multi-cloud application platform. It is not a self-service exam that anyone can register for; candidates must be nominated and then pass a series of rigorous assessments.

What the Assessment Involves

• Hands-on labs that test practical Anthos skills in realistic scenarios
• A panel interview with Google Cloud product and engineering leadership
• Evaluation of the candidate’s ability to lead organisations through hybrid and multi-cloud adoption

At the time of the announcement, twenty IT leaders had already earned the Certified Fellow designation and were actively applying those skills within their organisations.

What Certified Fellows Gain

• Industry recognition as a proven Anthos and hybrid-cloud expert
• Access to a peer network of other Certified Fellows
• Direct engagement with Google Cloud product and engineering teams
• A platform to contribute knowledge back to the broader cloud community

“The Certified Fellow exam pushed my understanding of Anthos’ capabilities, and the certification provides me with the platform to help educate the community about the latest technology and inspire people to become better engineers.”

— Chris Love, Principal Architect at LionKube and Google Cloud Certified Fellow

“I am proud of the recognition for my skill level from Google Cloud and my clients value the mastery it demonstrates. Having representation in the Certified Fellow Program reinforces Accenture’s commitment to Cloud innovation and to our continued Google Cloud partnership.”

— Zach Snee, Cloud Solutions Architect at Accenture and Google Cloud Certified Fellow

Professional Cloud DevOps Engineer: A Certification for Practitioners

Unlike the Certified Fellow programme, the Professional Cloud DevOps Engineer certification is an open, exam-based credential available to any DevOps professional who wants to validate their skills on Google Cloud. It targets engineers responsible for balancing service reliability with development speed — two tensions at the core of modern site reliability engineering (SRE) and DevOps practice.

Why This Certification Matters

The cloud skills shortage makes it difficult for hiring managers to quickly identify qualified candidates. A vendor-neutral job title like “DevOps Engineer” can encompass vastly different experience levels and tooling backgrounds. A Google Cloud-specific certification gives employers a concrete, verifiable signal that a candidate understands Google Cloud’s operations tooling, CI/CD patterns, and reliability practices.

For engineers, the certification provides a structured learning path and a portable credential that demonstrates expertise in:

• Efficient development operations on Google Cloud
• Service reliability engineering principles
• Delivery speed and deployment pipeline best practices
• Monitoring, logging, and incident response on Google Cloud infrastructure

How the Two Certifications Compare

What This Means for DevOps Teams

For organisations running workloads on Google Cloud — or evaluating a move to Anthos for hybrid or multi-cloud deployments — these certifications provide a practical hiring and talent-development framework. Engineering managers can use the Professional Cloud DevOps Engineer credential as a benchmark when evaluating candidates or building internal training programmes. For individual contributors, it represents a clear and achievable professional development goal with direct market value.

For staff aspiring to architecture or principal engineering roles, understanding the Certified Fellow programme sets a longer-term goal that also provides a deep incentive to master Anthos and enterprise hybrid-cloud design — skills that remain in high demand regardless of which cloud certifications a team pursues.

Further Reading

• Google Cloud Professional Cloud DevOps Engineer certification page
• Google Anthos platform overview

The Definitional Problem at the Heart of DevOps

Ask ten engineers what DevOps is and you will likely get ten different answers. That ambiguity is not a sign of immaturity in the field — according to Viktor Farcic, it is baked into the nature of DevOps itself. Farcic, a long-time DevOps practitioner and author, explores this tension at length in DevOps Paradox, a book structured as a series of candid conversations with practitioners across the industry.

The core irony is pointed: DevOps exists to bring order and collaboration to the chaotic, siloed world of software delivery — yet it cannot agree on what it actually is.

What DevOps Actually Is, According to Farcic

Farcic’s answer to “What is DevOps?” is deliberately minimal:

“Almost everyone gives a different answer to the question ‘What is DevOps?’ — there is a big discrepancy between the idea and the implementation. In my opinion, the main goal of DevOps is to enable self-sufficient, product-oriented teams that are able to take complete control of their products.”

Viktor Farcic, DevOps Paradox

The traditional software delivery model fragments an application’s lifecycle across isolated groups: business analysts define requirements, architects set guidelines, developers write code, testers validate it, and operations teams release it. Each group belongs to a different department with different — and often competing — incentives. Collaboration suffers because teams optimise for their own departmental goals rather than a shared product outcome.

DevOps, in Farcic’s framing, attempts to replace that structure with cross-functional, product-oriented teams that own the entire application lifecycle and report through a single line of accountability. The goal is collective ownership and empathy — not a prescribed workflow.

DevOps Is Neither a Process Nor a Technology Stack

A common misconception is that adopting certain tools — CI/CD pipelines, container orchestration, infrastructure-as-code — makes an organisation “DevOps.” Farcic pushes back on this directly:

“DevOps is neither [a process nor a set of technologies]. There is no prescribed process that has to be followed. Likewise, there is no technology that we can adopt to transform ourselves into ‘DevOps’ teams. It’s just an idea that developers, operators, and everyone else have to work together instead of being isolated in different silos.”

Viktor Farcic, DevOps Paradox

That does not mean tooling is irrelevant. Farcic makes a subtler point: every technology reflects the culture and processes of the team that built it. If an organisation adopts a tool that does not align with its own culture and processes, results will be sub-optimal at best. Teams must either choose technologies that fit their existing culture or use technology deliberately as a lever to shift that culture. Neither element can be ignored in isolation.

Does the “DevOps Engineer” Role Actually Exist?

The job title “DevOps Engineer” has become ubiquitous on job boards and org charts. Farcic is sceptical of what it usually represents:

“I don’t think there is such a thing as a ‘DevOps Engineer.’ The term was invented by people who were unwilling to apply the changes that DevOps leads to. Most of the time, a ‘DevOps Engineer’ is just another name for someone who works in shared services, operations, or infrastructure — in the department that was simply the first to be renamed DevOps.”

Viktor Farcic, DevOps Paradox

This is a provocative but coherent observation. If DevOps is about dissolving silos between development and operations, creating a dedicated “DevOps team” simply adds a new silo — one responsible for automation and pipelines — without changing the underlying organisational dynamics.

Is DevOps Experiencing an Identity Crisis?

Given how widely DevOps is misunderstood and misapplied, it is reasonable to ask whether it is in an identity crisis. Farcic’s answer is that it cannot be, because it never had a fixed identity to begin with:

“No one has defined the process behind DevOps. There are no steps that need to be followed daily or weekly. It’s just an idea that we should work together and not throw things over the walls of the department. The way there is therefore open to interpretation. DevOps never had a clear identity, so there can be no identity crisis.”

Viktor Farcic, DevOps Paradox

Compare this to Agile, which — despite being a set of values and principles — spawned concrete frameworks like Scrum with clearly defined ceremonies, roles, and artefacts. DevOps produced no equivalent. That openness is both its strength (adaptable to many contexts) and its weakness (easy to co-opt or dilute).

The Biggest Challenges Facing DevOps Today

Farcic identifies the core challenges as cultural and organisational rather than technical:

• Cosmetic rebranding: Companies rename existing departments — shared services, infrastructure, operations — as “DevOps teams” without changing how they work. The label changes; the silos do not.
• Middle management resistance: True DevOps reorganisation flattens hierarchies and eliminates some managerial layers. Those whose authority depends on the current structure have strong incentives to resist.
• Expertise and identity threat: Engineers who have spent years specialising in one domain — operations, QA, networking — can feel that a cross-functional model devalues their career path and credentials.

These are not technical problems that can be solved by deploying a new tool. They require deliberate organisational design, executive sponsorship, and a willingness to disrupt existing power structures.

About DevOps Paradox

Farcic conceived DevOps Paradox after noticing that the most valuable conversations at conferences happen informally — in hallways, at dinners, between sessions — rather than in planned talks. He wanted to capture that unstructured, exploratory dialogue and make it accessible to practitioners who cannot attend conferences in person.

“I had no real goals for this book other than talking to people about any subject as long as it was DevOps related. I have not prepared any questions in advance. Instead, I only brought together people I would want to speak to if I met them at a conference.”

Viktor Farcic, DevOps Paradox

The result is a deliberately diverse collection of viewpoints: interviewees from large enterprises and startups, veterans and emerging practitioners, friends and first-time acquaintances. The breadth is intentional — Farcic wanted conflicting opinions, not a unified manifesto.

Key Takeaways for DevOps Practitioners

• DevOps is an idea, not a framework. There is no canonical process to implement. Each organisation must define what collaboration across the software lifecycle looks like for its specific context.
• Tooling follows culture. Adopting DevOps tools without addressing organisational culture produces marginal improvements at best. Culture and process must evolve together with the technology.
• “DevOps team” is often a misnomer. A team called DevOps that sits between development and operations may simply be a rebranded operations team. True DevOps thinking embeds operational responsibility into product teams.
• The hard problems are human. Resistance from middle management and specialists whose identity is tied to the old structure are the primary barriers to DevOps adoption — not tool selection or pipeline design.

Below are four habits that effective DevOps engineers consistently demonstrate.

1. They Strive to Understand Both Sides of the Fence

DevOps sits at the intersection of software development and IT operations. Effective practitioners do not settle for expertise in only one domain — they actively work to understand the other side.

“If you have trouble writing code, focus on it and learn how to code,” Dempers says. “If you have trouble learning about hardware, focus on that. Learn about infrastructure and learn about networking, load-balancing, proxies.”

This cross-discipline fluency has a practical payoff: it enables engineers to build their own tooling — command-line interfaces, automation scripts, monitoring integrations — that bridges the gap between development workflows and operational processes. Rather than depending on others to translate requirements across the dev/ops divide, a well-rounded engineer can navigate it independently.

2. They Invest in Understanding Underlying Foundations

The DevOps ecosystem moves fast. New tools, platforms, and services appear constantly, and there is rarely enough time to thoroughly learn every one of them. Dempers argues that the most durable investment is not learning how to use a technology, but understanding why it works the way it does.

He offers a concrete example: “Instead of just learning how to run a Docker container, you dive into the Linux kernel features that make containerization possible — namespaces, cgroups, and so on. Once you understand those, how Docker works becomes obvious. You can then move on to technologies like Kubernetes, which rely on the same kernel primitives, and understand them far more quickly.”

This foundational knowledge also improves communication across the organization. When you understand how the pieces fit together at a fundamental level, you can explain trade-offs clearly, identify gaps in a proposed architecture, and make better decisions — rather than simply following vendor documentation.

3. They Actively Work to Manage Bias

Every experienced engineer develops opinions about technologies — preferred languages, favorite orchestration platforms, go-to monitoring stacks. That is natural and, in moderation, useful. The problem arises when preference hardens into tunnel vision.

“Bias toward certain technologies is fine, but if you develop tunnel vision around a particular stack, it won’t help you or your team,” Dempers explains. “Knowing and recognizing the strengths and weaknesses of the technologies you work with is a genuine superpower. It helps you make better decisions and strengthens your DevOps career.”

In practice, this means being willing to recommend a tool you personally dislike when it is genuinely the right fit for the problem at hand, and being honest about the limitations of tools you favor. It also means staying curious about technologies outside your comfort zone rather than dismissing them.

4. They Prioritize Simplicity Over Over-Engineering

One of the most persistent failure modes in modern engineering is complexity for its own sake. Cloud providers offer hundreds of services, infrastructure-as-code tools enable elaborate configurations, and there is constant pressure — from vendors, from peers, from the desire to look sophisticated — to reach for complex solutions.

“We live in a world where developers and operations teams are constantly over-engineering,” Dempers says. “Cloud providers make it easy to overspend and over-build.” The antidote, he suggests, is deliberate restraint: stepping back before designing a solution and asking a deceptively simple question — Is this actually the problem I need to solve?

Talking to the right stakeholders early often reveals that the assumed problem is not the real one, or that a far simpler solution already exists. The discipline of challenging problem definitions before investing in solutions is a habit that saves engineering time, reduces operational overhead, and keeps systems maintainable.

Putting It Together

None of these habits require a specific certification or years of experience in a particular platform. They are mindset shifts that compound over time:

• Learn both sides — close the knowledge gap between development and operations so you can work fluidly across the boundary.
• Understand foundations — invest in first-principles knowledge so that learning new tools becomes faster and comparisons become clearer.
• Manage bias — know your preferences but do not let them drive decisions; evaluate each situation on its own merits.
• Keep it simple — resist over-engineering; validate the problem before committing to a complex solution.

The common thread is intellectual honesty — about what you know, what you do not know, and what the situation actually requires. That disposition, more than any particular tool or framework, is what defines an effective DevOps engineer.

Original advice attributed to Marcel Dempers, software engineering specialist, from a public presentation on DevOps career development.

This article breaks down the core responsibilities, required experience, technical skills, and soft skills that define the DevOps Engineer role today.

Where the DevOps Engineer Fits in the Team

The name DevOps describes the discipline’s central purpose: bridging the gap between software Development and IT Operations. Historically, these two groups operated in silos, each optimising for different goals — developers pushing for speed and change, operations teams prioritising stability. The DevOps Engineer acts as the connecting layer between them.

In practice, DevOps Engineers work with a wide range of internal stakeholders: QA personnel, application developers, architects, project managers, and business stakeholders. They rarely interact directly with external end-users, but they maintain a customer-first mindset to serve the needs of their internal clients effectively.

Key team responsibilities include:

• Liaising between development and IT operations teams to align on shared goals and workflows.
• Mentoring software developers and architecture teams on building scalable, deployable software.
• Collaborating with security teams to ensure quality, secure releases.
• Contributing to or overseeing DevSecOps practices where security is embedded into the development pipeline from the start.

While DevOps Engineers frequently work independently on focused tasks, they are expert collaborators by necessity. Their work builds on the output of development and operations colleagues, requiring clear, consistent communication across organisational boundaries.

Experience Required

Most DevOps roles require hands-on experience with integration technology, automation tooling, and cloud platforms. Professionals entering the role commonly come from backgrounds such as Systems Administration, IT Project Management, or Database Administration — though many paths are valid.

Typical job postings ask for at least two to three years of relevant experience. The following competency areas are commonly expected:

• Agile Project Management — understanding iterative delivery and sprint-based workflows.
• Cloud Technology — practical experience with one or more major cloud platforms (AWS, Azure, GCP).
• Container Concepts — working knowledge of Docker, container orchestration, and image management.
• Continuous Integration / Continuous Delivery (CI/CD) — building and maintaining automated build and deployment pipelines.
• Deployment and Infrastructure Automation — using tools such as Ansible, Terraform, Chef, or Puppet to codify and automate infrastructure provisioning.
• Orchestration — managing containerised workloads with tools such as Kubernetes.
• Open Source Operating Systems — solid Linux administration skills are typically expected.
• Source Control — proficiency with Git-based workflows, branching strategies, and code review processes.

Because DevOps Engineers spend much of their time extending and amending existing platforms rather than building new ones from scratch, breadth of knowledge across these areas is often valued as much as depth in any single technology.

Infrastructure Planning, Testing, and Development

Day-to-day, a DevOps Engineer looks at specific functions within a cloud environment and writes code to adapt them to immediate business needs. This might mean adding users or permissions to a cloud platform, modifying workflow processes, spinning up new containers, or adjusting configuration to meet a scaling requirement.

This work involves:

• Rapid, targeted coding — writing small, precise code snippets across multiple languages and configuration formats (e.g., YAML, Bash, Python, HCL).
• Testing in virtual environments — validating changes in staging or sandbox environments before they reach production.
• Documentation — recording configuration decisions, runbooks, and architectural diagrams so teams can maintain and extend the infrastructure.
• Optimisation and support — monitoring performance and reliability, and tuning infrastructure components over time.

Crucially, a strong DevOps Engineer does not lose sight of the bigger picture. Infrastructure planning — understanding how systems integrate across an organisation and where future scaling pressure will emerge — is one of the skills that distinguishes a DevOps Engineer from a narrower infrastructure administrator role.

Security and Automation

DevSecOps: Security as a First-Class Concern

Writing secure code is not optional in modern DevOps — it is a core responsibility. DevOps Engineers are accountable for the security posture of the infrastructure they build and maintain. This means building security controls into software and infrastructure from the earliest stages of development rather than bolting them on afterwards.

This approach is formalised in the DevSecOps model, where security practices are integrated directly into the CI/CD pipeline. A DevSecOps team (which the DevOps Engineer may lead or closely collaborate with) typically:

• Scans code and dependencies for known vulnerabilities as part of automated pipelines.
• Performs continuous monitoring across all platforms for anomalous behaviour.
• Defines and enforces security policies as code (e.g., using tools like Open Policy Agent).
• Educates development and operations colleagues on secure coding and configuration practices.

Automation: The Core Differentiator

Automation expertise is arguably the single most important technical differentiator of the DevOps Engineer role. Where other IT roles may rely on manual processes for provisioning, configuration, testing, and deployment, DevOps Engineers systematically identify those manual steps and replace them with repeatable, auditable automated workflows.

The practical benefits are significant: automated pipelines reduce human error, accelerate deployment frequency, and free engineering time for higher-value work. Staying current with automation tooling — and knowing when a new tool genuinely improves a workflow versus adding complexity — is an ongoing responsibility for anyone in this role.

Important Soft Skills

Technical depth alone is not enough to succeed as a DevOps Engineer. The role sits at the intersection of multiple teams and disciplines, which demands a specific set of interpersonal and organisational skills:

• Communication — DevOps Engineers must translate technical constraints and requirements clearly across audiences: from developers and architects to project managers and business stakeholders. Ambiguity in this role has downstream consequences.
• Liaison and diplomacy — Finding common ground between development teams (focused on shipping features) and operations teams (focused on stability) requires patience and the ability to frame shared goals.
• Anticipating needs — Effective DevOps Engineers develop an intuition for where an organisation’s technology gaps will emerge before they become incidents. Understanding how people, culture, and processes interact is part of diagnosing what tooling or workflow changes will actually help.
• Teaching and mentoring — Because DevOps knowledge is still unevenly distributed across many organisations, DevOps Engineers frequently educate colleagues on topics such as scalability, security, and automation best practices.

The Outlook for DevOps Engineers

Organisations that have successfully adopted DevOps practices report improvements in deployment frequency, lead time for changes, and overall delivery reliability. Beyond the operational metrics, DevOps has had a measurable cultural impact in many companies — shifting responsibility for reliability and quality from a single team to a shared organisational value.

Despite this growth, hiring managers continue to find the role difficult to define precisely. Because DevOps Engineers can come from many different backgrounds and the toolchain changes rapidly, job descriptions vary widely. The consistent signals across strong candidates are:

• Proven experience with deployment automation and CI/CD pipelines.
• Hands-on infrastructure automation skills (infrastructure as code).
• Solid version control and Git workflow knowledge.
• A collaborative, communication-forward working style.

For engineers considering a move into DevOps, the most effective approach is to build practical experience across the technology areas listed above — ideally through real project work — while developing the cross-functional communication skills the role demands.

Original source material: bmc.com

What Is DevOps?

AWS defines DevOps as “the combination of cultural philosophies, practices, and tools that increases an organisation’s ability to deliver applications and services at high velocity.” That definition is a useful starting point, but it only captures part of the picture.

At its core, DevOps is an evolution of agile thinking applied beyond the software team. Atlassian describes it precisely that way. It brings the delivery (development) and operational support communities closer together, using tooling and processes — continuous integration, continuous deployment, test automation, infrastructure-as-code — to accelerate the flow of code into production. Those releases may represent new features, architectural changes, or bug fixes. As Gordon Cullum, CTO at Mastek, puts it: “It’s a combination of keeping the lights on and changing delivery.”

Reinvigorating a Proven Way of Working

The idea of unified delivery and operations is not new. In the 1980s and 1990s, IT departments were responsible for both running systems and shipping changes — there was no hard division between the two. DevOps revives that ethos, but with a critical difference: modern tooling makes the approach far more controlled, measurable, and repeatable than it ever was before.

Tools such as Puppet and Jenkins — along with their modern equivalents — create the robust, automated pipelines that allow fast delivery without the chaos that characterised ad-hoc deployments of earlier decades. The combination of disciplined tooling and a collaborative culture is what makes contemporary DevOps more powerful than the informal approaches of the past.

Why DevOps Has Become Urgent Now

Several converging forces have pushed DevOps from an option to a near-mandatory practice for enterprises:

• Competitive acceleration: Digital markets move fast. Organisations that cannot release code quickly risk being disrupted by competitors who can.
• Cloud infrastructure: Cloud platforms make it straightforward to spin up environments, platforms, and services on demand, enabling componentised, independently scalable architectures.
• Modern architecture patterns: Microservices and serverless architectures are naturally aligned with DevOps. Each service can be released, modified, and scaled independently, accelerating delivery cadence.
• Mature tooling ecosystem: The pipeline tooling available today — CI/CD platforms, container orchestration, observability tools — provides the quality guardrails that make fast delivery safe.

As Cullum summarises: “Bringing all these things together — the rise of cloud, the need to get things out faster but at a high quality, the rise of all the tooling that enables fast pipeline deliveries, changing culture in IT — what you’ve got is DevOps.”

How DevOps Works in the Enterprise: A Practical Framework

There is no single universal blueprint. The right approach depends on the organisation’s current architecture, culture, and strategic goals. What follows is a practical framework derived from enterprise experience.

1. Define Your “Why” Before You Start

The first and most important step is understanding the business problem you are trying to solve. DevOps adoption driven by a C-level mandate without a clear goal almost always fails. Ask:

• Do you need faster, more frequent releases?
• Do you need more repeatable, higher-quality deployments?
• Do you need to reduce the cost of delivery?
• Do you need to modernise a legacy architecture so it can support faster change?

The answer to each of those questions points to a different starting point and a different set of priorities.

2. Assess Your Architecture Honestly

Agile and DevOps practices only work well with an architecture that supports them. A legacy bank running monolithic applications on a mainframe cannot simply train its IT staff in DevOps techniques and expect deployment frequency to improve. Before adopting DevOps practices, legacy organisations often need an architecture enablement programme — decomposing monolithic systems into components that individual delivery teams can own and release independently.

3. Respect the Cultural Dimension

DevOps is as much a cultural shift as a technical one. Key cultural principles include:

• Shared ownership: Development and operations teams share responsibility for both delivery and reliability.
• Blameless learning: Failures are treated as system problems to be fixed, not as individual failures to be punished.
• Continuous improvement: Teams experiment, measure, and iterate rather than waiting for a perfect plan.
• Minimal upfront documentation: Heavy specification documents slow delivery; favour working software and iterative refinement.

4. Approach Risk Proactively

A common failure mode in enterprise DevOps adoption is paralysis in the face of risk. Patrick Callaghan, enterprise architect and strategic business advisor at DataStax, argues that “DevOps innovators are confident in their code because they both test it and make it fail in order to produce reliable apps.” Building resilience through deliberate failure testing — rather than trying to prevent all failures — is a hallmark of mature DevOps practice.

Building and Upskilling a DevOps Workforce

Skills shortages are a consistent challenge in DevOps adoption. The question most organisations face is whether to retrain existing staff or hire new talent. The honest answer is: both, but attitude matters more than either.

Experienced engineers who have spent 15–20 years in waterfall or siloed environments sometimes resist the mindset shift that DevOps requires. In contrast, junior engineers who have not yet been conditioned by older ways of working tend to adopt DevOps practices more readily. Cullum reflects this from Mastek’s own experience: “It’s harder to change attitude than it is to change a technology skill set.”

When hiring for DevOps roles, organisations should look for the following attributes in addition to specific technical skills:

1. Flexibility — willingness to adapt to changing requirements and tooling
2. Security awareness — understanding of DevSecOps principles; security baked into the pipeline, not bolted on afterwards
3. Collaboration — comfort working across team boundaries between development, operations, QA, and security
4. Scripting skills — ability to automate repetitive tasks and contribute to pipeline configuration
5. Decision-making — confidence making pragmatic choices under ambiguity
6. Infrastructure knowledge — understanding of cloud platforms, networking, and containerisation
7. Soft skills — communication, empathy, and the ability to facilitate cross-team problem-solving

DevOps as an Enabler of Digital Transformation

Digital transformation is not a technology programme — it is a wholesale reinvention of how a business operates, culturally and technologically. Any genuine transformation will eventually require large-scale changes to the IT estate, including the decomposition of legacy systems.

As those legacy systems are modernised and replaced with componentised, cloud-native architectures, the need for fast, reliable, automated deployment becomes critical. DevOps is the practice that makes that speed possible without sacrificing stability.

Cullum frames it in terms of pace-layered delivery: “You’re going to put a lot more focus in your systems of differentiation and innovation, and they have to have rapid, relatively robust change going in.” DevOps is what enables that cadence.

Organisations that are not yet practising automated, repeatable deployment pipelines — regardless of what they call it — are not equipped to change at the pace the digital market demands.

Why DevOps Urgency Is Not Overstated

For many industries, DevOps is no longer a differentiator — it is table stakes. Organisations that have not yet started are already behind. Cullum’s warning is direct: “If you aren’t already thinking about it or aren’t already doing it, you’re probably way behind the curve.”

A useful diagnostic for leaders in resistant organisations is to look for internal “guerrilla” DevOps adoption — small teams that have quietly built automated pipelines or adopted agile delivery practices without top-down authorisation. Those pockets of innovation are proof points. The task is to identify them, understand what is working, and create the organisational conditions to scale those practices across the enterprise.

Enterprise Case Study: Netflix and Resilience Testing

Netflix is a widely cited example of DevOps at enterprise scale, particularly in the area of resilience engineering. According to Callaghan, Netflix uses Apache Cassandra for high availability and has built a suite of chaos engineering tools — collectively known as the Simian Army — to validate that availability at scale.

Tools such as Chaos Monkey (which randomly terminates instances), Chaos Kong (which simulates the loss of an entire AWS region), and Chaos Gorilla (which simulates the loss of an availability zone) are used to stress-test Netflix infrastructure continuously. The result is a team that is genuinely confident in the reliability of its systems because they have tested failure modes thoroughly and repeatedly.

This approach — sometimes called chaos engineering — is a natural extension of DevOps principles: if you deploy frequently, automate rigorously, and test failure scenarios in production-like conditions, you build systems that are both fast to change and reliable in operation.

Key Takeaways for Enterprise Leaders

• Start with purpose: Know why you are adopting DevOps before you invest in tooling or training.
• Assess architecture first: DevOps cannot compensate for a monolithic architecture that does not support independent deployment.
• Invest in culture: The hardest part of DevOps adoption is not the tooling — it is changing how people think about responsibility, risk, and collaboration.
• Prioritise attitude in hiring: Technical skills can be taught; a growth mindset and collaborative attitude are harder to develop.
• Treat DevOps as a transformation enabler: Not a standalone initiative, but the operational foundation for everything digital transformation requires.
• Do not wait for perfect conditions: Start with a pilot team, prove value, and scale what works.

Having a strong DevOps culture is like having good taste. Everyone wants it – but is everyone equipped with the skills, instincts, and sheer luck needed to actually have it?

The reality is, building a great DevOps culture is easier said than done. Here are the major challenges facing strong DevOps cultures and how to overcome them.

1. Inability to give and listen to feedback

Teams must learn how to give and receive feedback if they are to improve and take each other forward in the process. Engineers and operators are smart cookies with high IQs, but many need to improve their EQs to collaborate more effectively as a team. Teams with high EQ will always destroy those with low EQ because they can learn and achieve more. 

Feedback is about sharing what is working and what can be improved every single day. It’s important that teams don’t just focus on the good or the bad, but rather keep a sharp focus on feedback and bias.

2. The revolving door problem


Part of the challenge facing DevOps culture is the short tenure of DevOps professionals themselves. The average tenure of a DevOps engineer is less than three years. Engineers often find themselves lured away for the promise of better compensation, better equity, or the “next hot startup company.”

This doesn’t do any favors to the ongoing battle to achieve true alignment between Dev and Ops teams: How they can play together when team members are constantly jumping ship, leaving behind unfinished projects, and forcing new people to join and ramp up quickly? If there were more stability in engineering teams, it might be easier to build the foundations of a stable and durable DevOps culture.

3. Well-meaning but time-wasting acts of heroism

Often you’ll be at a developer conference and an enthusiastic, well-meaning presenter is gushing about the unbelievably complex, bespoke platform that her team has built – one that has nothing to do with their core competency. She demonstrates how they spent six months and $300,000 to create it and the whole room bursts into applause.

The “build it not buy It” mentality is one that truly holds back top-performing engineering teams. In 2018, the platform you need has likely been built – and built extremely well – by a third party. Save your engineering heroics for what your customer actually requires; the rest is a needless waste of time and resources. Be an expert in your business, not the tools business.

4. The term “DevOps” is a problem

If you ask many high-performing engineering teams about DevOps, the response you’ll often get is an eye roll – even if those teams are uncommonly good at DevOps. The word has been beaten down, over-publicized, and over-discussed. (I know, this article doesn’t help that situation.)

If DevOps refers to the cultural alignment of development and operations so that both teams are responsible for the success of production environments, then the term has enormous value. But if the word has been drained of all meaning by a tsunami of think pieces and keynote presentations, then it’s difficult to have a meaningful discussion about it.

Try to remember that the concept has value, even if it’s been beaten down by so many analyses, conversations, and misunderstandings.

5. The right culture isn’t modeled from above

You all know the truth of this statement: There’s no culture unless it’s shown by example, set by the teams above. It takes a superhuman effort for a team to enact its own unique culture within an organization that doesn’t itself value culture or take it seriously.

If you have an organization where the executive and management team isn’t truly facilitating team alignment, including between the developer and operations teams, how can a DevOps team survive and thrive? Culture comes from the top.

6. DevOps goals aren’t aligned to business goals

99.9 percent of companies using DevOps are wielding it as a catalyst to drive business outcomes faster, and a strong DevOps culture is one that truly understands the levers of its business. DevOps is not about having a team of “rock stars” that improves technical KPIs; in fact, measuring availability is pointless unless you can measure and report the real business impact.

 Technical metrics are great, but goals drive behavior – and goals that focus on the needs of the business constitute the foundation of a solid DevOps culture.

How to beat the DevOps barriers

I’ve spent a lot of time describing the barriers that keep DevOps teams from reaching their full potential. But the reality is, there are plenty of positive forces helping DevOps teams build strong cultures. For one, the will to do so is stronger than ever: Companies want strong DevOps organizations to help them achieve business goals. For another, technology is better than ever and can help teams focus on the same shared metrics and set of goals.

Wherever you find the twin enablers of genuine will and solid technology, a strong DevOps culture can’t be too far behind. In addition to will and technology, companies seeking to build that culture must:

• Focus as much on EQ as IQ, making sure engineers and operators really listen to each other while building a DevOps culture from the ground up. This will also help maintain collaboration and stability on Dev and Ops teams, making constant turnover less of a cultural and business problem. (See our related story: 10 things leaders with emotional intelligence never do.)
• Stay in the business you’re in: Allow engineers to focus on what your company was created for, rather than distracting them.
• Have open discussions on what DevOps really means, and what it means to your teams, independent of the hype that the word has taken on in recent years.
• Ensure leadership is taking DevOps seriously by showing, not telling, how to build a collaborative culture – and by linking DevOps goals directly to business goals.

Back when typists were in demand, companies administered tests for secretarial jobs. If you could prove you had the skill to type X number of words per minute without error, you got the job; hence the term, skilled labor. The testing process is similarly straightforward for bus drivers or professional musicians. You take a driving test. You audition for the orchestra.

This practice doesn’t quite work for every occupation. How does a hospital determine the competence of a prospective brain surgeon? Give her a patient and see how it all turns out? Of course not.

For some types of work, a single testing session won’t ensure competence. That’s why employers might require a college degree or certifications from trusted testing authorities.

When it comes to IT and DevOps hiring, we’re relying almost solely on certification. A master’s degree in computer science will get your résumé on the desk of a hiring manager at Big Company Inc. But, if you’re applying for a DevOps position, being a Certified AWS DevOps Engineer Professional will actually get your résumé read.

DevOps, like Agile before it, suffers from an identity problem. Enormous energy goes into debating what DevOps is rather than what DevOps does. Teams cherry-pick appealing practices — configuration management, a new job title, a tweaked incident-management process — and stop there. Calling a sysadmin a DevOps engineer and looping developers into incident calls is a step forward, but it is nowhere near the operational overhaul that sustainable DevOps adoption requires.

What a Real DevOps Adoption Strategy Looks Like

Genuine DevOps adoption reaches beyond tooling and titles. It demands entirely new collaboration models, a developer mindset applied to operations, increased automation, and — critically — alignment with business goals. Tools can accelerate work through parts of a system, but they cannot substitute for the explicit agreements, shared understanding, and consistent behaviors that span every team involved in software delivery, from initial idea through production and back again.

A useful mental model for approaching this challenge comes from Switch: How to Change Things When Change Is Hard by Chip and Dan Heath. The book breaks the challenge of effecting change into three components: direction, motivation, and ease. Understanding which component is missing — and sometimes all three are — points you toward practical interventions. The sections below apply this model to a DevOps adoption strategy.

1. Direct the Change

Teams cannot move toward a destination they cannot see. If high-performing DevOps teams do not yet exist inside your organization, bring external examples to the conversation. The DevOps Enterprise Summit conference series (now known as Enterprise Technology Leadership Summit) is a reliable source: it features practitioners from large, regulated enterprises sharing detailed accounts of real transformation programs across industries.

Internally, work with each team to honestly assess their current state, articulate where they want to be, and then build an incremental improvement roadmap. A clear roadmap prevents two failure modes: paralysis from trying to change too much at once, and complacency from never setting a concrete direction. Incremental steps keep momentum visible and measurable.

2. Motivate Your Team and Build Lasting Habits

Even with a clear direction, teams may lack a compelling personal reason to work differently. Motivation must match what the team actually cares about — and that varies. Some engineers respond to competitive advantage or business outcomes. Others respond more strongly to:

• A visible sense of daily progress
• Eliminating unplanned, reactive work that interrupts meaningful tasks
• Career growth and the acquisition of in-demand skills

Motivational appeals that miss the mark stall adoption just as surely as a missing roadmap. Take the time to understand what drives each group of stakeholders before choosing your messaging.

3. Identify and Remove Obstacles

Even well-directed and well-motivated teams hit friction. DevOps adoption obstacles typically fall into four categories.

Business and Compliance Constraints

Compliance requirements are often cited as blockers, but they are rarely immovable. Engineering and risk teams usually share the same underlying goal — protecting the organization — and misalignment is more often about communication than about irreconcilable rules. When teams understand each other’s needs at a deeper level, it becomes possible to design workflows that satisfy regulatory intent without sacrificing delivery speed. The most effective organizations involve security and risk stakeholders from the start rather than treating compliance as an afterthought.

Organizational Misalignment

Conflicting team goals are a serious obstacle. If one team is rewarded for stability and another for release frequency, friction is structural, not personal. The starting point is to get the affected stakeholders talking — not through an escalation, but through a facilitated conversation about shared business goals. High-performing organizations continuously reorganize around the real flow of work rather than preserving legacy org-chart boundaries.

Architectural Limitations

Some technical constraints genuinely impede agility. Frameworks that resist automated testing, tightly coupled monoliths that cannot be deployed independently, and fragile infrastructure managed through manual change processes all slow delivery regardless of how motivated the team is. Addressing architectural debt is a long process. The key is ensuring that leadership understands the need to budget time for sustainable engineering health and that this work appears in planning at every level — not just in a backlog that never gets prioritized.

Poorly Configured or Fragmented Tooling

Different roles naturally view the delivery system through different lenses, but effective DevOps requires a single integrated toolchain with a clearly defined flow of work that is visible to everyone involved. Toolchains should be tuned through deliberate experimentation, not accumulated by accident. When scaling across multiple teams, establish a foundational, flexible tooling layer that provides consistency without forcing every team into an identical workflow. The goal is balance: enough standardization to collaborate effectively, enough flexibility to meet the specific needs of each team.

Bringing It All Together

If your organization has fallen short on DevOps adoption, it is worth diagnosing why before prescribing a remedy. Apply the three-part framework deliberately:

• Unclear direction? Provide concrete examples of high-performing teams and build an incremental roadmap.
• Lack of motivation? Match your appeals to what teams genuinely value — career growth, reduced toil, or visible progress.
• Too hard to change? Systematically identify and reduce friction from compliance rules, organizational silos, architectural debt, and toolchain complexity.

DevOps transformation is not a project with a completion date. It is an ongoing convergence of behavior, culture, and technical practice. Organizations that treat it as a shallow rebranding exercise will continue to generate the familiar complaint: “Our DevOps team doesn’t work with the development team.” Those that commit to a genuine operational overhaul will find that the benefits — faster delivery, greater reliability, and improved team morale — compound over time.

Despite the wealth of courses, certifications, and books now available, some of the most valuable DevOps lessons cannot be taught in a classroom. They come from lived experience — from projects that stalled, rollouts that backfired, and cultural battles that nobody anticipated. The following lessons were shared by DevOps veterans as advice they would give to their earlier selves. Whether you are just starting out or trying to mature an existing DevOps practice, these insights are worth taking seriously.

1. Beware of the “Them and Us” Mentality

Fin Goulding, international CIO, Aviva: “Without a shadow of a doubt, I underestimated the cultural challenges of implementing DevOps. The fusion of two ‘tribes’ into one sounds easy on paper: But the reality is very different and it takes quite some time to remove the ‘them and us’ mentality in order to have developers and engineers working side by side delivering value. I wish I had spent more time coaching individuals rather than just implementing the model across all the technical teams at once. In fact, it would have been best to start in a small way with a ‘lighthouse’ implementation before going for full roll-out.”

Goulding’s experience reflects one of the most consistent findings across DevOps transformations: tooling and process changes are relatively straightforward compared to the human side. Development and operations teams often carry years of entrenched habits, different incentive structures, and mutual mistrust. Forcing them into a shared workflow without adequate coaching frequently produces friction rather than collaboration.

A practical takeaway: before scaling DevOps organization-wide, identify a willing cross-functional team and run a pilot — a “lighthouse” — that can demonstrate value and surface cultural issues at a manageable scale. Use what you learn there to inform the broader rollout.

2. C-Suite Alignment Is Not Optional

Ben Grinnell, managing director, North Highland: “I would have liked to have understood the breadth of the changes needed to have a sustainable impact and the impact required across many of the typical C-suite functional areas. When we started out we were typically working with IT leaders (CIOs, CTOs or CDOs) trying to improve flow, feedback, and continuous improvement between development and operations functions. Often that solution wasn’t sustainable and didn’t deliver the benefits anticipated due to the problems elsewhere in the value stream, which gradually pulled the transformed Dev and Ops functions back to working in the old way.”

“This type of change is easily attacked by the corporate antibodies that destroy anything foreign. In order to stop this effect, you need to change the DNA of the organization.”

Ben Grinnell, North Highland

Grinnell goes on to explain that isolated DevOps improvements — even impressive ones — can be undone when the rest of the organization continues to operate under incompatible financial governance, procurement cycles, security review processes, and audit requirements. Without broader organizational alignment, improved Dev and Ops teams are essentially swimming against the current.

His advice: start small and learn, but invest early in building executive alignment that extends beyond the CIO or CTO. Procurement, finance, security, and audit all touch the software delivery value stream. Getting CEO-level sponsorship, in his experience, can accelerate progress significantly compared to trying to influence individual C-suite members one at a time.

3. When in Doubt, Have a Mitigation Plan

Eran Kinsbruner, director, author, and lead software evangelist, Perfecto: “Looking back, I wish I knew the importance of planning the DevOps pipeline to accommodate for changes. Along each iteration, changes are constantly being introduced, whether it’s a change to requirements, a change in backlog features, or other interruptions around quality (escaped defects, customer reported issues, etc.). Having a mitigation plan ahead of the end of journey can make the difference between business success and failure.”

Kinsbruner points out that mitigation planning is not simply a matter of writing a risk register. It requires strategic decisions about tooling, clear quality guidelines, and — critically — management buy-in to enforce those guidelines when schedule pressure tempts teams to cut corners.

He illustrates the stakes with a concrete example: enterprises that failed to incorporate new device environments into their continuous integration pipelines early enough struggled to ship quality software when major platform updates arrived. The lesson is that a CI pipeline that only reflects today’s environment is not truly continuous — it is already out of date. Regularly expanding test coverage to include emerging platforms, devices, and dependencies is part of maintaining a resilient pipeline.

Practical steps that follow from this lesson:

• Treat market and platform changes (new OS versions, new device form factors, dependency updates) as predictable sources of disruption, not surprises.
• Build explicit checkpoints into each iteration to evaluate whether the pipeline still reflects the real target environment.
• Define escalation paths and rollback procedures before a release, not during an incident.
• Make sure management understands that mitigation planning is not pessimism — it is what separates teams that ship reliably from teams that scramble.

4. Outcomes Define Success — Not the Tools

Mirco Hering, APAC DevOps and agile lead, Accenture: “I wish I’d have known from the beginning that technology is not the only solution; success is defined by the outcome, not the way to get there. I, like so many, was initially focused on ‘how to become DevOps’ rather than using the ever-increasing tool belt of DevOps practices and tools to achieve business outcomes. As technologists, we are sometimes too focused on the next shiny object. If I had learned this lesson earlier in my career I think I would have avoided some of the more spectacular failures of projects that implemented a technology but still did not achieve success.”

Hering’s observation addresses one of the most persistent failure modes in DevOps adoption: treating DevOps as a destination defined by a particular tool stack rather than as a means to a business end. Teams can adopt containers, implement CI/CD pipelines, instrument their services with monitoring, and still fail to deliver meaningful value if none of those choices are tied to a clear understanding of what success looks like for the business.

The antidote is to start every initiative with a clear statement of the business outcome it is meant to improve — deployment frequency, lead time, customer satisfaction, incident recovery time — and then work backwards to the practices and tools that best support that outcome. When a new tool or practice is proposed, the first question should be: “Which of our target outcomes does this improve, and how will we measure that?”

Common Threads Across All Four Lessons

Reading these four perspectives together, several themes emerge that are worth naming explicitly:

• Culture precedes tooling. Every practitioner touched on the human dimension — tribal mentalities, organizational antibodies, management buy-in. Tooling choices matter, but they are secondary to getting people aligned.
• Start small, but plan for scale. Lighthouse implementations and small pilots reduce risk, but they need to be designed with an eye toward how the lessons will propagate across the organization.
• Executive support changes the physics. Without alignment at the leadership level, even successful local improvements tend to regress as the surrounding organization exerts pressure to return to familiar ways of working.
• Define success before you start. Agreeing on measurable outcomes at the outset keeps teams honest about whether their choices are actually delivering value or just generating activity.

These lessons are not new — they recur in DevOps literature, conference talks, and post-mortems year after year. The reason they keep appearing is that they are genuinely hard to internalize until you have experienced the consequences of ignoring them. Treat them as warnings worth heeding before you learn them the hard way.

Original quotes sourced from enterprisersproject.com. Attribution has been preserved as it appeared in the original article.

1. Make Everyone Accountable to Shared Goals

Steve Burton, CD and DevOps Evangelist, Harness

Assigning people a “DevOps Engineer” title does not automatically shorten release cycles. Real progress comes from making every team member aware of the business objectives that their work supports and giving them genuine accountability for shared outcomes.

• Developers should be responsible for how their code behaves in production — not just in a test environment.
• Operations engineers should be freed from manually overseeing every release so they can focus on higher-value work.
• Compensation and incentives for both groups should be aligned to business outcomes, not individual task completion.

As Burton puts it, hiring a hundred people with “DevOps Engineer” in their title without shared goals and accountability is like putting a hundred tires on a car and expecting it to go faster. The structure must change, not just the org chart.

2. Cut the Jargon

Fin Goulding, International CIO, Aviva

Technical language creates invisible walls between IT teams and the business stakeholders whose support you need to scale DevOps. Goulding recommends leading conversations with business outcomes rather than acronyms. When pitching DevOps expansion to senior leadership or seeking additional investment, explain what will be delivered faster and more reliably — not the mechanics of CI/CD pipelines.

Goulding prefers the term Flow Teams over labels like “DevOps 2.0,” arguing that holistic, cross-functional teams focused on flow are the model that will define the most successful workplaces going forward. Whatever terminology you choose, prioritize clarity over technical precision when speaking to a mixed audience.

3. Measure Wisely and Choose the Middle Path

Mirco Hering, APAC DevOps and Agile Lead, Accenture

Before you can demonstrate progress, you need to define what success looks like and how it will be measured. Hering warns against two common traps: chasing the promises of over-eager vendors, and losing sight of practical, incremental improvement.

His “middle path” guidance:

• Do not look so far into the future that short-term wins become invisible.
• Do not be so short-sighted that you fail to build toward a longer transformation.
• Challenge the status quo, but do not demand ideological purity at the expense of pragmatic progress.
• Use technology to support your transformation, but do not place all your trust in any single tool or platform.

4. Move from a Project to a Product Mindset

Carmen DeArdo, DevOps Leader, Nationwide

The goal of a mature DevOps practice is to reduce lead time and deliver software more frequently so the business can respond quickly to change. That goal cannot be achieved when IT operates as a cost center that executes discrete projects on behalf of the business.

DeArdo advocates for a product-centric model in which IT is a full partner — not a vendor — working alongside the business to accelerate the flow of value across end-to-end product streams. This shift changes how teams are funded, how they are organized, and how their success is measured. Projects have end dates; products have ongoing owners who are continuously responsible for outcomes.

5. Balance Soft and Technical Skills on DevOps Teams

Robert Reeves, CTO, Datical

DevOps leaders need to build teams that combine human and technical capabilities. Neither alone is sufficient.

Soft Skills

• Communication: DevOps engineers accumulate knowledge that must be documented and shared effectively. Internal wikis, issue trackers, and informal knowledge-sharing sessions help ensure insights are not siloed with individuals.
• Collaboration: Effective collaboration in a DevOps context often involves tooling — for example, using chat platforms to surface alerts and outages, and running structured retrospectives to uncover process failures.
• Customer-first mindset: Even in a non-customer-facing role, DevOps engineers serve internal customers: developers, QA, project management, and business leadership. Empathy, transparency, and the ability to prioritize competing requests are essential.

Technical Skills

• System administration and engineering: A working knowledge of Linux and Windows server administration, networking fundamentals, and common infrastructure layers is foundational for DevOps engineers who need to diagnose and resolve production issues.
• Scripting and automation: Languages such as Python, Ruby, Bash, and Shell enable engineers to automate repetitive tasks, reduce human error, and free up time for higher-value work.
• Configuration management: Tools in this category allow teams to manage many servers and environments consistently — handling kernel updates, network settings, SSH key management, and tool provisioning across data centers and cloud providers.
• Identity and access governance: Controlling who can access which systems and data is both a security requirement and a productivity enabler. Familiarity with SSH keys, LDAP, and remote desktop protocols is part of a well-rounded DevOps skill set.

6. Don’t Let Alignment Goals Delay DevOps Progress

Ben Grinnell, Managing Director, North Highland

Waiting for full senior-leadership alignment before starting your DevOps implementation is a common and costly mistake. Full consensus at the executive level rarely arrives before it is too late to matter.

Grinnell recommends starting on the ground and building alignment in parallel by over-communicating early wins. The examples you share with leadership should be:

1. Easy for senior leaders to understand without a technical background.
2. Significant enough to register as meaningful progress.
3. Relevant enough that leaders can visualize the same pattern applied to a much larger part of the business.

Define a clear direction — a North Star — but avoid getting locked in prolonged debates about a precise destination and timeline. Getting the organization moving with shared direction is more valuable than a perfect plan that never launches.

7. Tap Into the Energy of the Organization

Jonathan Smart, Head of Ways of Working, Barclays

Smart introduces the concept of Aiki — using the organization’s existing energy and momentum to drive the transformation rather than fighting against inertia. In practice, this means:

• Identifying and starting with natural champions — people who are already enthusiastic about better ways of working.
• Rewriting internal standards and processes to embed DevOps principles rather than treating them as exceptions.
• Treating internal audits as allies rather than obstacles, since a well-structured audit process can reinforce accountability and continuous improvement.

8. Beware of Isolated Innovation Teams

Anders Wallgren, CTO, Electric Cloud

Creating a dedicated “innovation team” to pilot DevOps practices can backfire. Isolated groups often become disconnected from the rest of the organization and produce limited transferable value. Wallgren argues that the people most willing and able to adapt to change are the ones who create transformation others can follow — and they are spread across the organization, not concentrated in a single team.

His recommendations for DevOps leaders:

1. Design your organization so that product, development, and IT operations teams share ownership of the software delivery pipeline and treat it as a product.
2. Create an environment where teams can easily collect data on delivery performance metrics and KPIs, capture workflow bottlenecks, and focus on the value and quality of what they ship.
3. Continuously require teams to scrutinize their value streams and set short-term goals to address the biggest bottlenecks first.
4. Build a culture across the entire organization anchored in one mindset: continuously disrupting your own processes before a competitor does it for you.

9. Remember That “Continuous” Is the Keyword

Eran Kinsbruner, Director and Lead Software Evangelist, Perfecto

DevOps, at its core, means having a fully automated workflow for delivering software — and that cannot happen without mature automation. Kinsbruner emphasizes the importance of the three Cs working in harmony:

• Continuous Integration (CI): Developers integrate code changes frequently, with each change verified by an automated build and test sequence.
• Continuous Testing (CT): Automated testing is not a gate at the end of a pipeline but a layer woven throughout it, validating quality at every stage.
• Continuous Delivery (CD): Every code change that passes CI and CT is in a deployable state and can be released to production reliably and repeatedly.

The key to success is a mature Continuous Testing practice that acts as the connective tissue between CI and CD — running automatically for every code change, every day. Without it, the pipeline stalls and the promise of fast, reliable delivery goes unmet.

Putting It All Together

These nine tips share a common thread: lasting DevOps transformation is a leadership and cultural challenge as much as a technical one. Shared accountability, clear communication, measured progress, product thinking, balanced skills, pragmatic momentum, organizational energy, inclusive change, and relentless automation all reinforce each other. Strong DevOps leaders address all of these dimensions simultaneously rather than treating any single one as the silver bullet.

Original insights sourced from the Enterprisers Project.

Discussions about a “post-DevOps” world have been circulating since at least 2014. But has that moment actually arrived? And if so, what replaces DevOps — or evolves from it? These are important questions for engineering leaders, platform teams, and anyone shaping the direction of software delivery in their organization.

DevOps Has Reached Maturity

The DevOps movement is well over a decade old. What started as a counter-cultural push to break down silos between development and operations teams has become the dominant model for software delivery at companies of all sizes. “DevOps engineer” is now a standard job title. Continuous integration, continuous delivery, and infrastructure-as-code are expected capabilities, not differentiators.

That level of mainstream adoption signals something important: DevOps is no longer a disruptive idea. It is the establishment. And when a methodology becomes the default, it is natural to ask what comes next — whether through evolution or reaction.

Two distinct possibilities seem most likely.

Possibility 1: A Reaction Against DevOps

The first possibility is a backlash. Criticism of DevOps has existed for years, mostly at the margins. Critics have argued that DevOps can blur accountability, overload individual contributors who are expected to own both code and infrastructure, or introduce cultural complexity that smaller teams are ill-equipped to manage.

As DevOps adoption reaches saturation, more organizations will have enough experience to judge whether it has actually solved their specific problems. Some will conclude it hasn’t. In those cases, a partial or full retreat to earlier working models becomes plausible — reintroducing dedicated operations teams, clearer role boundaries, or more formal change management processes.

This scenario does not mean DevOps disappears entirely. It means the industry moves toward a more pragmatic, hybrid state where teams selectively apply DevOps principles alongside practices from earlier eras. The result would be a more heterogeneous landscape: some organizations running fully automated, cross-functional delivery pipelines, others operating with deliberate separation of duties for compliance, security, or operational stability reasons.

Key indicators that this scenario is taking hold would include:

• Growing demand for dedicated, specialized operations roles rather than generalist “you build it, you run it” engineers
• Renewed interest in ITIL-style change management frameworks at regulated organizations
• Public post-mortems attributing incidents to insufficient separation of concerns in DevOps pipelines

Possibility 2: DevOps Expands Across the Whole Organization

The second possibility is the opposite of a backlash: instead of pulling back from DevOps, organizations push it further — extending its core principles of collaboration, automation, continuous feedback, and shared ownership into business units well beyond development and operations.

This trend is already underway in specific domains. DevSecOps integrates security teams and security tooling directly into the CI/CD pipeline, shifting vulnerability detection left rather than treating security as a gate at the end of the delivery process. DevQAOps (sometimes just called continuous testing) embeds quality assurance into every stage of delivery rather than treating QA as a separate phase.

But the extension could go further. Consider what it would mean to bring DevOps thinking to:

• Legal and compliance teams — integrating policy-as-code and automated compliance checks into pipelines, so legal review is not a manual bottleneck but a continuously validated constraint
• Finance and procurement — applying feedback loops and observability to cloud spend, enabling engineering teams to respond to cost signals in near real time
• Marketing and communications (PR) — coordinating feature releases with go-to-market activities through shared tooling and shared delivery cadences
• Customer success and support — giving support teams direct visibility into deployment state and error rates, reducing the gap between a reported incident and an engineering response

In this scenario, the post-DevOps era is not a replacement of DevOps but a deepening of it. Organizations that have successfully applied DevOps principles to dev and ops look for the next leverage point and find it by dissolving more organizational silos. The software delivery pipeline becomes a shared nervous system that a much wider set of business stakeholders can observe, influence, and contribute to.

Few organizations have attempted this level of organizational integration to date. Doing so requires more than tooling — it demands shared vocabulary, shared metrics, and genuine executive sponsorship. But for organizations willing to invest, total DevOps-ification of the business could represent a significant competitive advantage.

Which Path Is More Likely?

In practice, both scenarios are likely to play out simultaneously across different segments of the market. Highly regulated industries — financial services, healthcare, government — may pull back toward more structured, role-separated models. Cloud-native product companies and startups are more likely to push DevOps thinking further into the business.

What seems clear is that DevOps as a static concept is losing its novelty. The organizations that thrive in the next phase will be those that treat DevOps not as a destination but as a foundation — either refining it to fit their operational reality or building on top of it to eliminate friction across the entire business.

The question worth asking inside your own organization is not “are we doing DevOps?” but “where is our next biggest bottleneck, and what would it look like to apply continuous improvement thinking there?”

1. Flexibility and Adaptability

Software development is never static. Requirements shift, dependencies are updated, and deployment targets evolve. A DevOps engineer must be comfortable moving fluidly between integration, testing, release management, and deployment—sometimes within a single working day.

Continuous Integration (CI) is a practical example of where adaptability is non-negotiable. CI pipelines surface merge conflicts and broken builds quickly, and the engineer responsible must triage and resolve those issues without disrupting the broader team’s workflow. The ability to context-switch efficiently and absorb new tooling or practices without significant ramp-up time is a strong indicator of long-term performance.

2. Security Skills (DevSecOps Mindset)

Faster release cycles introduce security risk if security is treated as an afterthought. When code moves from commit to production in hours rather than weeks, a vulnerability can reach a live environment before a traditional security review would even be scheduled.

DevOps engineers must understand how to write secure code and how to embed security checks into automated pipelines—practices often grouped under the term DevSecOps. Practically, this means:

• Running static application security testing (SAST) tools as part of the CI pipeline
• Scanning container images and dependencies for known vulnerabilities before deployment
• Applying the principle of least privilege to infrastructure access and service accounts
• Storing secrets in dedicated vaults (e.g., HashiCorp Vault, AWS Secrets Manager) rather than in source code

Security built in from the start is significantly cheaper and more effective than security retrofitted after an incident.

3. Collaboration and Cross-Functional Communication

DevOps is, at its core, a cultural practice before it is a technical one. The entire discipline is predicated on removing silos between development, operations, QA, and security teams. An engineer who works in isolation—regardless of their technical ability—actively undermines the model.

Strong collaborators contribute to shared on-call rotations, participate in blameless post-mortems, write runbooks that others can follow, and give useful code reviews. They treat infrastructure and tooling decisions as team decisions rather than individual preferences, which leads to more maintainable systems and less tribal knowledge.

4. Scripting and Coding Proficiency

A DevOps engineer who cannot write code is limited to clicking through GUIs—a ceiling that quickly becomes a bottleneck at scale. Scripting is the mechanism by which manual, error-prone operational tasks get automated and made repeatable.

Common languages used in DevOps workflows include:

• Python – widely used for automation scripts, tooling, and cloud SDK interactions
• Bash / Shell – essential for pipeline steps, system administration tasks, and bootstrapping
• Go – increasingly popular for writing custom CLI tools and cloud-native utilities
• Ruby – historically associated with Chef and Vagrant-based workflows
• JavaScript / TypeScript – relevant for teams using Node.js-based tooling or Infrastructure as Code frameworks like Pulumi

Beyond general scripting, fluency in Infrastructure as Code (IaC) tools—Terraform, AWS CloudFormation, or Pulumi—is increasingly a baseline expectation rather than a bonus skill.

5. Sound Decision-Making Under Pressure

Production incidents do not wait for committee meetings. When a deployment introduces a regression, or a pipeline fails mid-release, a DevOps engineer must assess the situation quickly and choose a course of action: roll back, roll forward, or apply a targeted fix. Indecision in those moments extends downtime and erodes organizational trust.

Good decision-making in DevOps is supported by strong observability practices—comprehensive logging, metrics dashboards, and distributed tracing—that give engineers the data they need to diagnose problems accurately rather than guessing. Engineers who invest time in building that visibility make faster, more confident decisions when it counts.

6. Infrastructure and Cloud Knowledge

Modern applications run on complex infrastructure stacks that span on-premises data centres, public clouds, and hybrid environments. A DevOps engineer needs a working understanding of how these layers fit together:

• Networking fundamentals – DNS, load balancing, firewalls, VPCs, and TLS termination
• Compute platforms – virtual machines, containers (Docker), and container orchestration (Kubernetes)
• Cloud services – managed databases, object storage, serverless functions, and identity and access management (IAM) on platforms such as AWS, Azure, or Google Cloud
• Configuration management – tools like Ansible, Puppet, or Chef for maintaining consistent system state at scale

An engineer who understands infrastructure can design deployment architectures that are resilient, cost-effective, and easy to operate—rather than simply running whatever the application team hands over.

7. Soft Skills: Empathy, Communication, and Continuous Learning

Technical skills get a candidate hired; soft skills determine long-term impact. DevOps culture depends on psychological safety—team members must feel comfortable flagging problems, asking questions, and proposing changes without fear of blame. Engineers who communicate clearly and listen actively contribute to that environment.

Practically, strong soft skills in a DevOps context look like:

• Writing clear incident reports and post-mortems that focus on systemic causes rather than individual blame
• Documenting processes and decisions so that knowledge is shared across the team
• Giving and receiving constructive feedback in code reviews and retrospectives
• Staying current with a fast-moving ecosystem through self-directed learning, community involvement, and experimentation

The last point deserves emphasis: DevOps tooling evolves rapidly. An engineer who stops learning quickly falls behind. Curiosity and a growth mindset are arguably the most durable skills on this list.

Putting It Together

No candidate will arrive fully formed in all seven areas, and that is fine—the list also serves as a development roadmap for engineers at any stage of their career. When building a job description or evaluating candidates, weight the skills relative to your team’s current gaps. A team already strong on security might prioritize infrastructure knowledge; a team scaling rapidly might value collaboration and communication above all else.

What the list makes clear is that effective DevOps engineering is neither purely technical nor purely interpersonal—it sits deliberately at the intersection of both.

The Rise of DevOps Engineering

Demand for DevOps engineers has grown substantially over the past decade. The role sits at the intersection of software development and IT operations, helping organizations ship higher-quality software faster and at lower cost. Companies across every industry now treat DevOps capability as a strategic asset rather than a nice-to-have, making it one of the more durable career paths in the technology sector.

Whether you are just entering the field or looking to sharpen your existing skill set, mastering the following five areas will give you a strong foundation for a productive DevOps career.

1. Core DevOps Concepts and Vocabulary

Every discipline has its own language, and DevOps is no exception. Before you can work effectively across development and operations teams, you need to be fluent in the foundational concepts that shape daily conversations and tool choices.

• Continuous Integration (CI): The practice of merging code changes frequently and running automated builds and tests after each merge.
• Continuous Delivery/Deployment (CD): Extending CI so that software is always in a releasable state, and deployments can be triggered automatically or on demand.
• Configuration Management: Defining and maintaining the desired state of infrastructure through code, so environments are reproducible and auditable.
• Orchestration: Coordinating the automated deployment, scaling, and management of containerized or distributed workloads.
• Black-Box Testing: Testing a system’s behavior from the outside, without knowledge of its internal implementation.
• Infrastructure as Code (IaC): Managing and provisioning infrastructure through machine-readable definition files rather than manual processes.

Building a solid conceptual vocabulary lets you read documentation, evaluate tools, and communicate requirements clearly across teams — all critical day-to-day activities for a DevOps engineer.

2. Soft Skills and Cross-Team Collaboration

DevOps is fundamentally a cultural practice built on trust and communication. Technical skills alone are insufficient if an engineer cannot bridge the gap between development, operations, security, and business stakeholders.

Key interpersonal competencies include:

• Active listening: Understanding the needs and constraints of both developers and operations staff before proposing solutions.
• Negotiation: Balancing competing priorities — release velocity versus stability, cost versus resilience — to reach workable compromises.
• Problem-solving: Diagnosing root causes rather than treating symptoms, especially during incidents.
• Team building: Fostering a blameless culture where post-mortems focus on systemic improvements rather than individual fault.
• Clear written communication: Documenting runbooks, architecture decisions, and on-call procedures so knowledge is shared rather than siloed.

When developers and operations staff communicate effectively, the result is faster time-to-market, lower defect rates, and reduced operational costs — the core promise of the DevOps model.

3. Scripting and Programming Proficiency

A DevOps engineer does not need to be a full-stack application developer, but a working knowledge of at least one scripting or general-purpose programming language is non-negotiable. Automation is the engine of DevOps, and automation requires code.

Languages commonly used in DevOps workflows include:

• Python: Widely regarded as the most accessible language for DevOps automation. Extensive library support for cloud APIs, data processing, and tooling integration makes it a practical first choice.
• Bash/Shell scripting: Essential for Linux system administration, pipeline scripting, and quick automation on any Unix-like system.
• Ruby: Historically significant in configuration management tools such as Chef and in the early DevOps tooling ecosystem.
• Go: Increasingly common in cloud-native tooling (Docker, Kubernetes, Terraform are all written in Go), making familiarity valuable.
• Java or Groovy: Relevant when working with Jenkins pipelines, where Jenkinsfile declarative and scripted syntax draw on Groovy.

Once you have a primary language, invest time in understanding how to interact with third-party APIs, parse structured data formats such as JSON and YAML, and write maintainable, testable scripts rather than one-off hacks.

4. Continuous Integration and Continuous Delivery

CI/CD pipelines are the backbone of modern software delivery. Understanding how to design, build, and maintain these pipelines is one of the most in-demand DevOps skills on the market.

Continuous Integration automates the process of merging code changes, running unit and integration tests, and producing build artifacts. The goal is to surface integration problems as early as possible, when they are cheapest to fix.

Continuous Delivery extends CI by ensuring every passing build is packaged and staged in a way that makes it ready for production deployment with minimal manual intervention. Continuous Deployment takes that further by automatically promoting successful builds all the way to production.

Widely used CI/CD platforms include:

• Jenkins: An open-source automation server with a large plugin ecosystem, suitable for complex, customized pipelines.
• GitHub Actions: Tightly integrated with GitHub repositories; popular for projects already hosted on GitHub.
• GitLab CI/CD: A built-in CI/CD system within the GitLab platform, favored in self-hosted and enterprise environments.
• CircleCI, TeamCity, Azure DevOps Pipelines: Commercial alternatives with varying strengths in cloud integration and enterprise features.

Aim to understand pipeline-as-code principles — defining your build, test, and deployment stages in version-controlled files — so pipelines are auditable and reproducible, not just configured through a UI.

5. DevOps Toolchain Familiarity

No single tool solves every problem, and different organizations make different choices. A strong DevOps engineer understands the categories of tooling available and can evaluate trade-offs, rather than being locked into a single vendor’s ecosystem.

A practical starting toolchain might look like this:

When selecting or recommending tools for a team, consider integration compatibility with existing systems, community support, licensing costs, and the learning curve for your team. Mismatched or poorly integrated tools introduce friction and can negate the efficiency gains DevOps is meant to deliver.

Putting It All Together

Mastering DevOps is an ongoing process rather than a destination. The tooling landscape evolves rapidly, but the underlying principles — automation, collaboration, continuous feedback, and shared responsibility — remain consistent. Engineers who invest in building a strong conceptual foundation, solid scripting ability, and genuine cross-team communication skills will find themselves well-positioned regardless of which specific tools rise or fall in popularity.

Start by deepening your knowledge in one area — perhaps CI/CD pipelines or infrastructure as code — and work outward from there. Hands-on practice with real projects, even personal or open-source ones, accelerates learning far more quickly than reading alone.

“While there are a raft of technical skills that may be required for any given environment, the reality of DevOps engineering is one of frequent change,” said Matthew Boeckman, developer advocate at DevOps startup VictorOps. “Whether in deployment pipelines, systems architecture, or incident management, a DevOps engineer will be constantly challenged by new technology, complex problems, or dynamic roles.”

Below are ten skills that practitioners and engineering leaders consistently identify as essential for DevOps success.

1. Soft Skills

DevOps is fundamentally about breaking down the silos between development and operations teams. That makes interpersonal ability one of the most underrated — and most important — skills in the discipline.

“A DevOps engineer would be required to be a bridge between the silos and bring different teams together to work towards a common goal,” said Karthiga Sadasivan, director and head of DevOps at Happiest Minds Technologies.

Alan Zucker, founding principal of Project Management Essentials, noted that software engineers often default to tools rather than people and processes. “Great DevOps engineers start by understanding the people, the culture, and how the organization runs,” Zucker said. “They then build a strategy that focuses on simplifying the overall operating environment to achieve the goal of continuous delivery.”

Alex Robbio, president and cofounder of Belatrix Software, echoed this view: “Soft skills are incredibly important — not just for the individual engineer, but also in making the organizational cultural shift to implementing and then standardizing DevOps.”

2. Broad Understanding of Tools and Technologies

The DevOps toolchain is wide and ever-evolving. A capable DevOps engineer does not need to be an expert in every tool, but should be familiar with categories across the entire delivery pipeline. Key areas include:

• Source Control: Git, Bitbucket, SVN, Azure DevOps (formerly VSTS)
• Continuous Integration: Jenkins, Bamboo, Azure DevOps
• Infrastructure Automation: Puppet, Chef, Ansible
• Deployment Automation & Orchestration: Jenkins, Octopus Deploy, Azure DevOps
• Containerization: Docker, LXD
• Container Orchestration: Kubernetes, Apache Mesos, Docker Swarm
• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform, OpenStack

“A great DevOps engineer is always curious,” said Ron Gidron, technology evangelist at Automic Software. Constant learning — asking questions, listening, generating new ideas, and welcoming new challenges — is what keeps a DevOps engineer effective as the landscape shifts.

3. Security Awareness and Training

Faster release cycles are a core benefit of DevOps, but they also mean that security vulnerabilities can be introduced and propagated more quickly. DevOps engineers must understand secure coding practices and be aware of common attack vectors.

“The faster cycle means that vulnerabilities can be introduced into code much faster than previously,” noted Ryan O’Leary, vice president of the Threat Research Center at WhiteHat Security. DevOps engineers need to be able to write secure code and defend against common cybersecurity weaknesses, he said.

The trend toward DevSecOps — integrating security directly into the DevOps workflow — makes this even more critical. “Perform security activities during the requirements phase of the DevOps journey,” said Meera Subbarao, senior principal consultant for the Synopsys Software Integrity Group. “The earlier in the journey security is addressed, the cheaper it is to fix problems. DevOps professionals, even though they don’t need to be expert security professionals, will benefit tremendously from having software security training.”

4. Experience with Infrastructure Automation Tools

Automation is at the core of DevOps value. Many tasks that were once performed manually by system administrators — provisioning servers, configuring environments, deploying packages — can and should be automated using scripting languages and infrastructure-as-code tools.

Scripting languages commonly used include Python, Ruby, Bash, Shell, and Node.js. Infrastructure-as-code tools like Terraform, Chef, and PowerShell enable repeatable, version-controlled environment configuration. “Infrastructure needs to be provisioned and configured with code, or you will drown in support,” said Adam Kadzban, lead DevOps engineer at kCura.

James Giles IV, a DevOps engineer at Datical, added that automation “will ensure consistent performance of manual tasks by removing the human component and allowing teams to spend the saved time on more of the broader goals of the team and company.”

Familiarity with both on-premises hypervisors (VMware, Hyper-V) and cloud providers (AWS, Azure) is a significant advantage. Kadzban also recommended automating the connection between infrastructure and monitoring tools from the outset.

5. Testing Skills

Automated deployment pipelines are only as reliable as the tests that validate them. Without strong testing practices, continuous delivery becomes continuous risk.

“The idea of automating code or feature deployments can be unsettling, especially when you consider the effect on end users when something breaks,” said Andrae Raymond, programmer and consultant at Software Stewards. “When proper tests are in place you can rest assured that each function is doing what it was written to do. From all stages from development to deployment we can run tests to make sure the entire system is intact with new features.”

A DevOps engineer should understand unit testing, integration testing, end-to-end testing, and how to wire these into a CI/CD pipeline so failures are caught before they reach production.

6. Customer-First Mindset

DevOps engineers may not face external customers directly, but they serve a broad set of internal stakeholders: developers, QA engineers, product managers, and business leaders. Treating these groups as customers — prioritizing their needs, communicating clearly, and demonstrating empathy — is essential.

“When juggling requests from operations, development, and product teams the ability to empathize, prioritize, and be transparent are key to successful relationships,” said Giles.

Omri Gazitt, chief product officer at Puppet, framed this more broadly: “A great DevOps engineer always cares about delivering value to customers and wants to understand and measure how their work is moving the needle. By caring about the outcome as opposed to their part of the supply chain, they will have the right instincts around how to best optimize for end-to-end success.”

7. Collaboration

DevOps is a team sport. Engineers who hoard knowledge, work in isolation, or create bottlenecks undermine the very goals the practice is designed to achieve.

“Any problem is everyone’s problem, and a great engineer always makes those around them better,” said Gazitt. Working in small batches — keeping changes reviewable, writing acceptance tests, unblocking colleagues — allows the entire team to move faster. “The key is to have empathy towards others so that the entire team can move more quickly,” he added.

Strong collaboration also means proactively identifying and relieving bottlenecks, not waiting for someone else to escalate the problem.

8. Flexibility and Adaptability

The DevOps landscape changes rapidly: new tools emerge, organizational priorities shift, and incidents demand immediate context-switching. Engineers who are rigid in their workflows or attached to specific technologies will struggle.

“There are no sacred cows — all of this is a risk/reward exercise,” said Dan Simoes, senior director of operations for tCell.

Multitasking under pressure is a practical reality. “As a resource that works on mission-critical systems at the heart of processes for different teams, a DevOps engineer gets requests from many different people at once,” said Anastasia Grinman, DevOps engineer at JFrog. “Frequently, everything is important and everything is urgent. DevOps engineers find themselves putting out fires, so the ability to work on multiple tasks at the same time is critical.”

9. Network Awareness

Applications don’t run in a vacuum — they depend on network infrastructure to reach end users. DevOps engineers who ignore networking concerns often discover problems late in the delivery cycle, when they are most expensive to fix.

“The end objective of any DevOps project is to successfully deliver an application to the end user who will consume it. That involves the network,” said Jim Frey, vice president of strategic alliances at Kentik. “My advice for DevOps engineers is to ignore the network at your peril. A good DevOps engineer will recognize that you have to account for the network in your design, your planning and your testing.”

Basic network knowledge — DNS, load balancing, firewalls, latency, CDN behavior — allows engineers to design systems that perform reliably at scale and to debug issues more effectively when they arise.

10. Big-Picture Thinking

Technical depth is valuable, but engineers who focus exclusively on their slice of the pipeline can inadvertently create constraints that ripple across projects and teams. Understanding how individual decisions connect to organizational goals is a differentiating quality in senior DevOps engineers.

“While many DevOps engineers are excellent software engineers, they sometimes lack the ability to look at the big picture and identify what makes sense for the client,” Zucker said.

Gidron emphasized this is especially important in large organizations: “A successful DevOps engineer can’t lose sight of the big picture for DevOps and digital transformation at the enterprise level. This helps avoid creating contention points and constraints that carry from one project to the next.”

Putting It Together

The DevOps engineer role is one of the most cross-functional positions in modern software organizations. Success requires fluency across automation, security, networking, and testing — but also the communication skills, customer orientation, and strategic thinking to align those technical capabilities with real business outcomes. Engineers who cultivate all ten of these areas position themselves to lead meaningful change in any organization adopting DevOps or scaling it beyond its early stages.