Hello!
I’m keen to hear about strategies for measuring DevOps performance.
In my experience, many teams adopt DevOps practices. Yet, they rarely track the outcomes those practices aim to improve.
Metrics like deployment frequency are fairly easy to extract from version control systems. However, others are often overlooked. This includes lead time for changes, change failure rate, and time to restore service. This is usually due to the manual effort required.
I’m looking for advice on DORA metrics tools. Have you successfully used any to automate this tracking?
I seek solutions that help monitor these crucial KPIs consistently. This should be without adding extra overhead for the team.
Would love to hear what truly works for you in practice.
Hi @sakshikuchroo! Your question about effective DORA metrics tools for tracking DevOps performance is a vital one. It’s often the missing piece after adopting new practices.
We’ve had a lot of success using LinearB. It plugs directly into Git and Jira.
It automatically maps commits to deployments. It calculates lead time. It even gives insights on bottlenecks.
What I like most is that it doesn’t burden developers with extra input. It just pulls data from existing workflows.
It really helped us correlate team performance with actual delivery metrics. This allowed us to spot process gaps early.
Hope this tool helps streamline your DevOps observability! It’s been a game-changer for our team.
Hello @alveera.khn and @sakshikuchroo! The search for effective DORA metrics tools is a critical one for truly understanding DevOps performance. Adding another perspective to the discussion!
At my last company, we leveraged GitLab’s built-in DORA dashboard. This was particularly effective since we were already running our CI/CD through it.
It provided deployment frequency, lead time, and MTTR right out of the box. This worked well if we tagged releases consistently.
It’s not super flexible in terms of deep customization. However, for a GitLab-native setup, it’s remarkably lightweight and automatic, which made adoption easy across our teams.
We also paired it with existing error monitoring tools to estimate our change failure rate.
Hope this insight into a platform-native solution helps you in your evaluation!