DevOps (Development and Operations) is a set of practices that automates the processes between software development and IT teams. It helps create, test & release software faster and more reliably. DevOps is all about building a culture of collaboration between teams that historically functioned in relative siloes.
DevOps improves and accelerates software development and helps drive companies’ digital transformation. However, DevOps success is not easy to measure, considering it is not a formal framework. DevOps is more of a culture and a set of practices. There are limited guidelines available to ensure whether we are doing it correctly or to measure success and failure.
Nevertheless, despite the vague definition of what a DevOps organization looks like, there are a few vital key performance indicators (KPIs) that should be common to all DevOps environments:
Change Lead Time
Mean Time to Detection
Mean Time to Recovery
Change Failure Rate
Deployment Frequency The code deployment frequency provides a picture of how rapidly new features and capabilities roll out in an organization. It should remain stable or trend upward over time. A decrease could indicate a bottleneck somewhere within the DevOps team structure. The capacity to make code changes quickly, and effortlessly is a critical competitive advantage for a company that needs to deliver new features speedily to customers.
Deployment Speed The deployment speed shows how long it takes for a specific deployment to move from commit to code, which is successfully running in production. Businesses with better deployment speed can increase revenue by using that extra time to develop more value-added services
Change Lead Time The change lead time is the time it takes a change, e.g., a bug fix or new feature to move from inception to production. The lengthy lead times means inefficient processes that inhibit change implementations.
Mean Time to Detection The average time between deployment and discovering the first failure in a production environment. A low change failure rate is not good enough if it takes too long to detect a problem. If MTTD is decreasing over time, then it's a healthy sign and shows that an organization’s DevOps processes are mature.
Mean Time to Recovery The average time between an environment's crash and recovery in production. DevOps businesses follow the principle that frequent, incremental changes are easier to deploy and fix when something goes wrong. The potential to recover swiftly can make a huge difference to business results.
Change Failure Rate Changes must roll out without a hitch. DevOps keeps the failure rate for changes deployed into production applications as low as possible. The cost of critical application failure could be in millions per hour & failed deployments can take services down, consequently lost revenue and frustrated customers.
Service Availability Application uptime is crucial for every IT organization. Service-level agreements (SLAs) require that the infrastructure, services & supporting applications meet a high goal of availability. Services should be available with an uptime goal as high as 99.99%.
Application Performance Storage blockage, CPU spikes, high memory consumption & network latency are the side effects of a surge in application usage. It is important to monitor these standard performance aspects of the servers that support an application. If the performance declines without additional user requests, then it could be due to bugs or inefficient changes from development and release that are bogging down the app.
Continuous software delivery
Less complexity to manage
Faster resolution of problems
More productive teams
Faster delivery of features
More stable operating environments
Improved communication and collaboration
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