Hi everyone!
I've been working in various companies where they've committed to adopting DevOps practices, but I've noticed a lack of measurement around the metrics that highlight why these practices were put in place originally. It seems part of the issue is the time it takes to calculate these metrics manually. For instance, I know that deployment frequency can be easily tracked through our version control system, but I'm curious about the other important metrics, such as lead time, change failure rate, and average time to restore. How do you manage to track these metrics on a regular basis without too much manual effort?
4 Answers
I see your point about deployment metrics. However, measuring deployment frequency can feel a bit counterproductive, right? It shouldn’t be a race to increase numbers. What’s more important is ensuring that any measurement helps validate the benefits of changes. What alternative metrics would you consider more valuable?
You might already have the tools needed to track these metrics, like Jira or GitHub. The key is automation and following a consistent process. For instance, our deployments are logged as Jira tickets that are automatically generated in our deployment pipeline. This ticket tracks resolved issues and version numbers, making it easy to pull deployment frequency with a simple query in Jira.
On a slightly different note, you could also leverage AI tools like Luna for generating sprint and retrospective reports. Has anyone else tried using Luna for efficiency insights?
If your code is hosted on GitHub, you should check out the OpenTelemetry contrib for a GitHub receiver that helps with gathering metrics.
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