Why DevOps Is So Hard to Define

Few terms in the software industry generate as much nodding agreement and genuine confusion as DevOps. Ask ten practitioners to define it and you will get ten different answers, all of which are technically correct and collectively incomplete. The Wikipedia definition—widely quoted—doesn’t help much:

DevOps is a set of software development practices that combine software development (Dev) and information technology operations (Ops) to shorten the systems development life cycle while delivering features, fixes, and updates frequently in close alignment with business objectives.

That definition is accurate. It is also almost entirely useless if you are trying to understand what DevOps looks like day-to-day. To get a more grounded explanation, veteran software developer and Linux Journal Deputy Editor Bryan Lunduke put the question directly to four practitioners with real-world DevOps experience. What follows is a condensed, edited version of those conversations.

A Brief Note on the Author’s Background

Context matters when evaluating a definition, so it is worth knowing where Lunduke is coming from. His career in software spans roles across the full engineering hierarchy:

• Software Test Engineer – finds bugs before software ships and reports them to developers.
• Automation Engineer – writes code that automates the testing process.
• Software Development Engineer in Test (SDET) – builds tools that testers use.
• Software Development Engineer – writes production code.
• Dev Lead – manages a small group of engineers while still writing code.
• Dev Manager – manages engineers with less hands-on coding.
• Director of Engineering – manages engineering managers.
• Vice President of Technology/Engineering – accountable for technical strategy and delivery timelines.

Along the way he also managed SysOps engineers, System Administrators and Project Managers. In short, he has touched every part of the software delivery pipeline that DevOps is supposed to integrate. Which makes his confusion all the more illuminating.

The Conversation: Asking “Ted” to Explain DevOps Without Buzzwords

Lunduke posed a simple challenge to his practitioner contacts: “Explain to me what DevOps means. Bonus points for not using any buzzwords.” Their combined answer is represented below by the composite expert “Ted”.

The Core Idea

Lunduke: Okay, Ted. What actually is DevOps?

Ted: At its simplest: take the developers and the operations people—the sysadmins, the infrastructure team—and integrate them together. That is the core idea.

Lunduke: When you say “operations”, you don’t mean the Chief Operating Officer and supply-chain management?

Ted: No—System Operations. SysAdmin work. The people who keep servers running, manage deployments, configure networks and handle the IT infrastructure a software product depends on. Add QA and testers into that group as well. Everyone involved in the software delivery lifecycle working together, rather than in isolated silos.

How DevOps Differs from Agile

Lunduke: That sounds exactly like Agile.

For reference, the Wikipedia definition of Agile Software Development is:

Agile software development is an approach to software development under which requirements and solutions evolve through the collaborative effort of self-organizing and cross-functional teams and their customer(s)/end user(s). It advocates adaptive planning, evolutionary development, early delivery, and continual improvement, and it encourages rapid and flexible response to change.

Ted: There are real similarities, but the focus is different. Agile is primarily about improving collaboration between engineering teams, project managers and customers. DevOps is specifically about integrating the engineering team with the people who own the IT infrastructure—sysadmins, platform engineers, cloud operations staff. The overlap exists, but so does a meaningful distinction in emphasis.

Lunduke: So is DevOps just “sysadmins and engineers should talk to each other”? That idea is older than the personal computer.

Ted: That really is the foundational idea, yes. What DevOps adds on top is a body of best practices—tools, workflows, cultural norms and automated pipelines—that make that collaboration work reliably at scale. Sometimes the integration goes so far that Dev and Ops roles merge completely, with engineers owning both code and the infrastructure it runs on.

DevOps vs. Waterfall

Ted: One concrete best practice is releasing small, incremental changes frequently rather than large, infrequent releases. This is in direct contrast to the Waterfall model:

The waterfall model is a breakdown of project activities into linear sequential phases, where each phase depends on the deliverables of the previous one and corresponds to a specialisation of tasks. Progress flows in largely one direction through the phases of conception, initiation, analysis, design, construction, testing, deployment and maintenance.

In a Waterfall process, a team might work for months before anything reaches production. A DevOps-oriented team aims to deploy continuously—sometimes multiple times per day—keeping each individual change small and therefore less risky.

Key DevOps Concepts Defined

Several terms came up repeatedly in the conversations. Here is what they mean in plain language:

Continuous Integration (CI)

Developers merge their code changes into a shared repository frequently—often multiple times a day. Automated builds and tests run immediately after each merge to catch integration problems early, before they compound.

Continuous Delivery / Continuous Deployment (CD)

Every change that passes automated tests is automatically prepared for release (Continuous Delivery) or automatically released to production (Continuous Deployment). The distinction matters: Continuous Delivery still involves a human approval step; Continuous Deployment does not.

Agile Sprint

A sprint is the basic unit of work in the Scrum framework, commonly associated with Agile development. Sprints are time-boxed—typically one to four weeks—during which the team commits to delivering a defined set of features or fixes. DevOps teams often operate at cadences much shorter than a traditional sprint, releasing to production continuously rather than at sprint boundaries.

Infrastructure as Code (IaC)

Server configuration, network rules and deployment environments are defined in version-controlled code files rather than configured manually. This makes infrastructure reproducible, auditable and testable—treating servers the same way developers treat application source code.

So What Is DevOps, Really?

After all the conversation, a practical working definition emerges:

DevOps is a cultural and technical movement that breaks down the wall between software development and IT operations teams. It is supported by automation tools and shared practices—continuous integration, continuous delivery, infrastructure as code, automated testing—that together allow organisations to ship software faster, more reliably and with less manual overhead.

The core idea is genuinely old. Small shops and solo developers have always worn both the developer and sysadmin hat. What DevOps contributes is a shared vocabulary, a set of proven practices and a growing ecosystem of tooling—pipelines, container orchestration, configuration management, observability platforms—that make the integration of Dev and Ops tractable at enterprise scale.

DevOps and Linux

The DevOps toolchain has strong roots in the Linux ecosystem. Container runtimes, CI/CD servers, configuration management tools, scripting environments and cloud infrastructure APIs are predominantly Linux-native or Linux-first. The majority of production workloads running under a DevOps model run on Linux servers. That is not a coincidence: the open-source culture that produced Linux also produced much of the tooling—Git, Docker, Kubernetes, Ansible, Terraform, Jenkins, Prometheus—that makes modern DevOps practice possible.

The Honest Takeaway

DevOps resists a single clean definition because it is simultaneously a philosophy, a set of practices and a job title—and different organisations emphasise different aspects. If you encounter the term and feel confused, you are in good company. The useful question is not “what is DevOps?” in the abstract, but rather: what specific practices is this team or tool trying to enable? Focus on those concrete answers and the buzzword becomes much less mysterious.

Original reporting by Bryan Lunduke for Linux Journal.

Why Soft Skills Matter in DevOps

Most DevOps conversations gravitate toward toolchains: CI/CD pipelines, containerization, infrastructure-as-code, and observability platforms. These are all important, but they miss a critical variable—the people using them. DevOps is fundamentally a cultural and organizational shift, and culture is shaped by human behavior, not by YAML files. Collaboration, communication, trust, and psychological safety are the soft skills that determine whether a DevOps initiative thrives or stalls.

Whether you are building a DevOps team from scratch or improving the efficiency of an existing one, assessing and developing these human skills is as important as hiring for technical expertise.

Step One: Assess Your People Honestly

Before investing in tools or restructuring workflows, take stock of what you already have. Evaluate your team across three dimensions:

• Technical skills: Coding, scripting, infrastructure management, security, monitoring.
• Process skills: Understanding of Agile, Lean, and continuous delivery principles.
• People skills: Communication, empathy, conflict resolution, and cross-functional collaboration.

Skills gaps should not automatically trigger an external hire. A team member in another part of the business may be a strong fit. An existing team member may need targeted training rather than replacement. An app development partner or specialist consultant may be the right solution for a critical phase rather than a permanent addition. The goal is a thoughtful, phased plan that covers near-term, medium-term, and long-term needs.

Create Model Behaviors, Not Just Mandates

Telling people to “communicate better” accomplishes little. What actually changes behavior is designing environments and incentives that make collaboration the natural outcome. Here are three practical strategies:

Make Collaboration Count in KPIs

If collaboration is genuinely important to your organization, embed it in how you measure success. Tie team metrics to business outcomes—such as deployment frequency, mean time to recovery (MTTR), and customer satisfaction scores—rather than individual output. When people are measured on shared outcomes, siloed thinking becomes counterproductive to their own goals.

Start Small and Cross-Functional

If your organization is new to DevOps, resist the urge to transform everything simultaneously. Pick a small, well-scoped project and staff it with a cross-functional team. Small teams are forced to collaborate to succeed—they don’t have the luxury of throwing problems over a wall to another department. Early, visible wins build the confidence and momentum needed for larger rollouts.

Normalize Knowledge Sharing

Practical steps—like maintaining shared, standard libraries accessible to all teams—signal that knowledge hoarding is not the culture you are building. Internal wikis, shared runbooks, documented post-mortems, and open code repositories all reinforce a culture where sharing is expected, not exceptional.

Seek Outside Help Strategically

External expertise can accelerate a DevOps initiative, particularly in its early stages. An experienced external partner can help a team achieve “lift-off”—establishing working pipelines, practices, and patterns that internal staff can then own and evolve. Crucially, a well-chosen partner also acts as an on-the-job training resource for the existing team.

Options range widely in cost and scope: independent consultants, specialist DevOps agencies, digital transformation firms, and large global systems integrators. The right choice depends on your budget, the complexity of your environment, and how much internal capability you want to build versus buy over time. Be specific about what you need before engaging any external resource—vague briefs lead to vague outcomes.

Focus on Quick Wins to Build Momentum

Success is the most effective team motivator. When starting a DevOps transformation, identify initiatives that can deliver measurable value quickly:

• Continuous automation: Shift from automating tasks within a single team’s silo to automating across the entire delivery pipeline. This reduces manual handoffs, speeds up delivery, and surfaces bottlenecks.
• CI/CD implementation: Establishing even a basic continuous integration and delivery pipeline gives teams fast feedback on code quality and integration issues.
• Containerization: Packaging applications in containers simplifies environment consistency and accelerates both testing and deployment.
• Release and configuration management: Improving how you track and deploy configuration changes reduces the risk of environment drift and production incidents.

None of these require a complete organizational overhaul to begin. Pick the one that delivers the most immediate value in your context, execute it well, and use that success as a proof point for broader adoption.

Build a Culture of Trust, Not Blame

DevOps projects rarely succeed or fail in absolute terms. More often, a project partially meets its goals, surfaces unexpected problems, and teaches the team something valuable—if the culture allows people to learn from failure rather than hide it.

Many enterprise cultures instinctively respond to failure by adding process gates, extended review cycles, and accountability escalations. These responses feel safe but actively undermine a DevOps culture, where rapid iteration and learning from mistakes are core to the model. Trust is not naïve—it is a deliberate leadership choice that creates the psychological safety teams need to take calculated risks.

Practically, this means:

• Run blameless retrospectives: Give equal weight to what went well and what needs improvement. Document findings, create action items, and then move forward. Do not let retrospectives become forums for blame, tacit or explicit.
• Act on retrospective findings: If a team consistently struggles with the CI/CD pipeline, invest in specific training or tooling improvements (such as Jenkins, GitHub Actions, or GitLab CI). If metrics and observability are weak, address that directly. Identify the precise bottleneck and resource it appropriately.
• Celebrate learning: Publicly recognizing a team that identified a risk early—even if the project still faced challenges—signals that transparency is valued more than the appearance of perfection.

Putting It Together: The Human Side of DevOps Transformation

DevOps has become a strategic priority for software-driven organizations because it enables faster, more reliable delivery of software. But the organizations that sustain DevOps success over time are those that invest as much in their people as in their pipelines. Collaboration, communication, psychological safety, and trust are not soft topics to address after the technical work is done—they are prerequisites for the technical work to succeed at all.

A pragmatic approach looks like this:

1. Assess your team’s technical, process, and people skills honestly.
2. Identify gaps and fill them creatively—not always by hiring.
3. Design incentives and behaviors that reward collaboration over individual heroics.
4. Start small, win visibly, and scale what works.
5. Use external expertise as an accelerant and learning resource, not a crutch.
6. Foster trust by treating failure as data, not evidence of incompetence.

Technical expertise will always matter in DevOps. But the teams that go furthest are those where soft skills are treated with the same rigor and intentionality as their deployment pipelines.