When you hear the word "DevOps", you probably think of Kubernetes, Terraform, Azure DevOps, or CI/CD pipelines. Yet reducing the DevOps approach to a set of tools is a common mistake among organizations.

Today, there is a multitude of tools available to address IT’s technical needs. But installing Jenkins or moving to the Cloud is not enough to become "DevOps”. In fact, it is often the opposite. Adopting a fashionable toolchain without changing mindsets is a classic case of "Cargo Cult" : imitating appearances rather than understanding fundamentals.

In this article, we present the anti-patterns we most frequently encounter, as well as the challenges to overcome in order to reduce Time to Market (TTM) and improve the quality of your software products (the original objectives of the DevOps culture). Spoiler: these challenges are primarily organizational.

3 anti-patterns that undermine your transformation

Attempting to adopt a DevOps approach without organizational change often leads to reproducing the same mistakes under new names. In this context, we repeatedly encounter three anti-patterns that transform the original ambition — at best — into a status quo, and — at worst — into a costly failure.

New tools without changing practices

A frequent reflex is to start by changing team tooling. Typical initiatives include setting up CI/CD pipelines and beginning to automate infrastructure. The trap lies in limiting the effort to new tools without evolving practices. If your production releases are still monthly or quarterly events bundling a large backlog of features, your deployments will remain risky — even if they are automated through a CI/CD tool. The complexity of integrating a large number of changes at once remains. So does the likelihood of introducing major regressions. In addition, collecting feedback from users will still happen too late, increasing the risk of developing expensive features that do not meet real user needs.

The “DevOps” role

We regularly see job descriptions for a “DevOps Engineer”. These are generally reduced to a list of tools and are meant to complement each development team. Their responsibilities typically include managing CI/CD and, sometimes, acting as a liaison with Ops teams. The resulting teams are autonomous when it comes to delivering new features, but they still do not own the run. A wall of confusion therefore persists between Dev and Ops, degrading collaboration between teams. This approach also creates a strong dependency on the DevOps engineer, who becomes the sole person responsible for CI/CD.

It is important to reiterate that DevOps is not a role. It is a culture centered on collaboration. Hiring a “DevOps” engineer or adding a mediation team does not solve the issue of shared responsibility — it merely dilutes accountability.

The “DevOps” team

At a larger scale, we often observe the creation of a dedicated “DevOps” team. In this model, the DevOps team becomes a proxy between Dev and Ops teams, responsible for integration and environments. You want access to a new database? Ask the DevOps team. Create an S3 bucket? Ask the DevOps team. Add an environment variable? … You get the idea. The issue with this approach is that development teams are still not autonomous. Even if the DevOps team uses Infrastructure as Code, it centralizes all requests and eventually becomes a bottleneck. There is also the question of being able to validate these requests properly, as discussed in our article The Cloud, Is It Really That Expensive? (Part 2).

The challenge of real autonomy (Team Topologies)

Avoiding these pitfalls requires moving from segregated teams (Dev on one side, Ops on the other) to truly autonomous, cross-functional teams. As detailed in our article The Cloud, Is It Really That Expensive? (Part 2) , this change is the most difficult to implement because it requires evolving behaviors and establishing new habits across the organization. It implies rethinking the organization’s very structure — bringing Dev and Ops together within the same team. Each role grows through exposure to the other, breaking down silos of expertise and ensuring greater collective resilience. The models proposed by Team Topologies are an excellent source of inspiration.

The ultimate goal is to create product teams that deliver in a continuous flow, thereby reducing deployment risks and shortening the feedback loop with users. Teams are sovereign within their scope (you build it, you run it), supported by platform teams. The role of platform teams is no longer to process tickets, but to provide self-service infrastructure products that product teams can use autonomously, with support available when needed. Much like Software as a Service (SaaS), platform teams aim to meet the needs of their customers — here, the product teams.

Measuring success differently

Transitioning from a traditional IT culture to a DevOps culture does not happen overnight. This is why it is essential to understand whether the transformation — and the investments that come with it — are delivering results. How should success be measured?

Forget the number of containers deployed or the functional coverage of your software factory. End users do not care whether you are using Kubernetes or bash scripts. What matters is the value you deliver and the speed at which you deliver it. To ensure that investments produce the expected outcomes, it is crucial to track metrics focused on performance and customer satisfaction rather than purely technical indicators.

The key indicators (golden metrics) to monitor are:

• Deployment frequency How often do you deliver value?
• Lead Time for changes How long does it take for an idea or fix to reach the user?
• Mean Time To Recovery (MTTR) In the event of an incident, how quickly is service restored?
• Change Failure Rate How reliable are your deployments?

By measuring all of these indicators together, you can assess the success of your transformation. The DevOps approach aims to optimize — and strike the right balance between — velocity and reliability.

These metrics also help align team objectives. They are a step toward resolving the historically conflicting goals between Dev and Ops, where the former seek to deliver new features and the latter aim to ensure a stable service at minimal cost.

Conclusion

The real obstacle to a DevOps transformation is not technological — it is human.

Tools are accelerators, but they cannot compensate for a siloed organization or inefficient validation processes. To succeed in your transformation, do not start by choosing your container orchestrator. Start by aligning your teams (Business, Dev, Ops) around shared objectives and conducting a reality check of your teams’ skills. Autonomy and accountability come next — two key challenges for reducing Time to Market and improving the quality of your products… with or without the latest cutting-edge tools.