3 DevOps implementation mistakes to avoid

DevOps is the modern software engineering culture that brings software development and IT business teams together. To deliver projects faster and maintain an efficient pipeline of future update releases, DevOps creates an ecosystem to accelerate and automate software development. It also enables more intensive software testing before releasing it.

A significant improvement seen in companies that adopt DevOps is that operation teams in such companies no longer work in isolation. DevOps engineers work at the intersection of software development and business operation infrastructures.

Given the rise in the adoption of DevOps (its market size exceeded $4 billion in 2019 and is expected to grow by 20% CAGR between 2020 and 2026), it is a promising market for software engineers. However, you have to tread carefully to maximize the benefits of DevOps; you have to avoid some implementation mistakes proactively.

Here are some common mistakes committed by DevOps engineers that you must avoid.

1. Choosing DevOps tools without thorough consideration 

You will find many DevOps tools to help improve your team’s performance. But how do you decide what tools your team requires?

Common mistake companies make when implementing DevOps is to go with the trend. For instance, Docker and Kubernetes are pretty popular in the DevOps community. IBM reports that organizations that use containers experience benefits across industries. In its study, IBM found that 78% of companies noticed improved application quality and reduced defects, 73% reported reduced application downtime, and 74% higher customer satisfaction.

Does it imply that you must implement containers as soon as possible?

No.

Hasty decisions only result in overspending on DevOps tools that teams never use.

It would be best if you focused on creating a suitable DevOps tool kit for your organization. Ask some essential questions like:

• Is your team ready to implement the tool?
• Do you need the DevOps tool?
• How impactful will it be on the way the DevOps teams work?

Remember, the more complex tool you introduce, the more changes will occur and the more time and effort needed to adopt it. Do not adopt tools that can severely complicate workflows and deployment. Look for more straightforward ways to solve the problem.

2. Oversimplification

DevOps is complex on all frontiers. Whether it’s creating DevOps teams, frameworks, or strategies, sophistication is involved. As a DevOps engineer, you must not try to make an isolated team to manage the DevOps strategy. Hiring new engineers and creating a segregated team will unnecessarily add new processes, which are often lengthy and complicated.

Your focus must be on optimizing the existing DevOps teams instead of creating new ones. To create an efficient DevOps environment, processes must be streamlined to leverage the right resources to develop operational products faster. It would help if you managed all aspects related to DevOps, such as resource management, goals, budgeting, and progress tracking.

Implementing DevOps is not easy and demands a cultural overhaul. It is why you must rush or oversimplify the process. The adoption of this methodology must be in a phased and measured transition.

3. Assuming DevOps can’t be measured

Improvements can only be made when they can be measured, and DevOps is no exception. You will fail by implementing DevOps without strategizing what crucial metrics must be calculated. Accurate analysis is mandatory to determine whether or not the DevOps strategy is working for your teams. Simply put, you cannot succeed with DevOps implementation until you pay enough attention to the metrics.

Some critical DevOps metrics to assess the success of the initiatives are change lead time, deployment frequency, and mean time to recovery (MTTR). The deployment frequency is the primary keyword here as it shows how fast the code completes its journey from the organization to the production. It is an indicator that shows how efficient your DevOps teams are. Change lead time measures the lead time for code changes from the start of the deployment cycle until it is released. MTTR is the recovery time measure that shows how much time DevOps teams take on average to restore service, components, or systems after an outage.

The goal of any DevOps team is to reduce the MTTR. By measuring crucial metrics, you are in a better position to evaluate and introduce adjustments that can further improve the efficiency of DevOps teams.

Conclusion 

You will create an efficient production pipeline for frequent software deployment as a DevOps engineer. To deliver, you must overcome the challenges of implementing the DevOps methodology. Above listed common mistakes can be easily avoided as long as you are aware of their existence. Through DevOps, any organization can enjoy greater agility, improved employee morale, and better customer satisfaction.

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