Watch Out for these DevOps Mistakes

The past few years have witnessed the meteoric rise of DevOps in the software development landscape. The conversation is now shifting from “What is DevOps” to “How can I adopt DevOps”. That said, the Puppet’s State of DevOps Report stated that high performing DevOps teams could deploy code 100 times faster, fail three times less and recover 24 times faster than the low performing teams. This suggests that DevOps, like with every other change in the organization, can be beneficial only when done right. In the haste to jump on the DevOps bandwagon, organizations can forget that DevOps is not merely a practice but is a culture change – a culture that breeds success based on collaboration. While DevOps is about collaboration between teams, continuous development, testing and deployment, key mistakes can lead to DevOps failure. Here’s a look at some common DevOps mistakes and how to avoid them.
Watch Out for these 8 DevOps mistakes

  1. Oversimplification:
    DevOps is a complex methodology. In order to implement DevOps, organizations often go on a DevOps Engineer hiring spree or create a new, often isolated, DevOps department to manage the DevOps framework and strategy. This unnecessarily adds new processes, often lengthy and complicated. Instead of creating a separate DevOps department, organizations must focus on optimizing their processes to create operational products leveraging the right set of resources. For successful DevOps implementation, organizations must manage the DevOps frameworks, leveraging operational experts and other resources that will manage DevOps related tasks such as resource management, budgeting, goals and progress tracking.
    DevOps demands a cultural overhaul and organizations should consider a phased and measured transition to DevOps implementation by training and educating employees on these new processes and have the right frameworks in place to enable careful collaboration.
  2. Rigid DevOps processes:
    While compliance with core DevOps tenets is essential for DevOps success, organizations have to proactively make intelligent adjustments in response to enterprise demands. Organizations thus have to ensure that while the main DevOps pillars remain stable during DevOps implementation, they make the internal adjustments that are needed in internal benchmarking of the expected outcomes. Instrumenting codebases in a granular manner and making them more partitioned gives more flexibility and gives DevOps teams the power to backtrack and identify the root cause of diversion in the event of failed outcomes. However, all adjustments have to be made while remaining within the boundaries defined by DevOps.
  3. Not using purposeful automation:
    DevOps needs organizations to adopt purposeful automation – automation that is not done in silos like change management or incident management. For DevOps, you must adopt automation across the complete development lifecycle. This includes continuous delivery, continuous integration, and deployment for velocity and quality outcomes. Purposeful end-to-end automation is essential for DevOps success. Hence organizations must look at complete automation of the CI and CD pipeline. At the same time, organizations need to keep their eyes open to identify opportunities for automation across processes and functions. This helps to reduce the need for manual handoffs for difficult integrations that need additional management and also in multiple format deployments.
  4. Favoring feature-based development over trunk-based development:
    Both feature-based development and trunk-based development are collaborative workflows. However, feature-based development, a development style that provides individual features their isolated sandboxes, adds to DevOps complexity. As DevOps automates many aspects of the code between development and production environments, keeping different conceptual flavors around the codebase makes DevOps more complex. Trunk-based development, on the other hand, allows developers to work in a coherent and single version of the codebase and alleviates this problem by giving developers the capability to manage features through selective deployments instead of through version control.
  5. Poor test environments:
    For DevOps success, organizations have to keep the test and production environments separate from one another. However, test environments must resemble the production infrastructure as close as possible. DevOps means that testing starts early in the development process. This means ensuring that test environments are set up in different hosting and provider accounts than what you use in production. Testing teams also have to simulate the production environment as closely as possible as applications perform differently on local machines and during production.
  6. Incorrect architecture evaluation:
    DevOps needs the right architectural support. The idea of DevOps is to reduce the time spent on deploying applications. Even when automated, if deployment takes longer than usual there is no value in the automation. Thus, DevOps teams have to pay close attention to the architecture. Ensure that the architecture is loosely coupled to give developers the freedom and flexibility to deploy parts of the system independently so that the system does not break.
  7. Incorrect incident management:
    Even in the event of an imperfect process, DevOps teams must have robust incident management processes in place. Incident management has to be a proactive and ongoing process. This means that having a documented incident management process is imperative to define incident responses. For example, a total downtime event will have a different response workflow in comparison to a minor latency blip. The failure to do so can lead to missed timelines and avoidable project delays.
  8. Incorrect metrics to measure project success:
    DevOps brings the promise of faster delivery. However, if that acceleration comes at the cost of quality then the DevOps program is a failure. Organizations looking at deploying DevOps thus must use the right metrics to understand progress and project success. Therefore, it is essential to consider metrics that align velocity with throughput success. Focusing on the right metrics is also important to drive intelligent automation decisions.

To drive, develop, and sustain DevOps success, organizations must focus on not just driving collaboration across teams but also on shifting the teams’ mindset culturally. With a learning mindset, failure is leveraged as an opportunity to learn and further evolve the processes to ensure DevOps success.

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