What are engineering metrics?
Engineering metrics are data that teams can use to make informed decisions and operate at maximum efficiency. Some data about your software development process, like story points completed, have proven less than helpful. In this guide, we will describe the data you can use to more insightfully measure your team’s success. These include:
- Pipeline data like tracking success/failure rate, throughput, and mean time to recovery
- Team performance information like confidence level and developer happiness
- Usage optimization numbers like credit spend per job or by workflow
Don’t use CI on your team? Learn why continuous integration is key to increasing deployment frequency.
Finding DevOps success with the right engineering metrics
Finding a way to measure success is key to evaluating your team’s ability to deliver. As the world’s largest standalone CI provider, CircleCI has a unique opportunity to investigate what software delivery looks like quantitatively: across tens of thousands of teams, commit by commit. We’ve seen how teams are building and deploying software in practice, and here we will share the keys to using metrics to improve your team’s performance.
Learn how to measure DevOps success with four key benchmarks for your engineering teams.
Tracking pipeline data to make informed decisions
Need a place to track your pipeline-relevant pipeline data? Monitor and optimize your CI/CD pipeline with the Insights dashboard from CircleCI.
Using aggregate workflow information shows engineering teams how workflows are performing over time — tracking success/failure rate, throughput, and mean time to recovery, as well as duration metrics. Tracking these metrics helps ensure you’re making informed decisions about your pipelines. On the CircleCI Insights dashboard, you can:
- Track status — See which jobs are failing and which workflows have flaky tests. Prioritize efforts for pipeline improvement.
- Monitor duration — Find out which workflows or jobs are taking the longest and identify opportunities where caching, parallelization, and convenience images can help speed things up.
- Optimize consumption — Optimize usage on CircleCI with insight into credit spend per job or by workflow. Predictably plan month-over-month consumption.
Download the 2022 State of Software Delivery report to find out what the most successful teams are doing to build better and faster.
Now that you have a place to track your data points: How do you improve your team’s engineering metrics?
We’ve compiled a few resources that give insight on how to increase team success. Browse through these articles for information that’s relevant to your team:
- Feedback loops: The key to improving mean time to recovery
- What does the change fail rate tell us about high-performance teams?
- How to stop worrying and love failed builds
- Decrease your build times by running jobs in parallel with workflows
- Learn how to leverage job orchestration for workflows
- How we write our CircleCI config at CircleCI
KPIs for engineering teams: continuous integration that achieves both speed and quality
Speed tells only part of the story. The challenge is knowing how to gauge your DevOps team’s performance beyond speed. High velocity is great, but high confidence is even more vital. Taken together, the two qualities create what’s known as high-performance DevOps.
What does a high-performing team actually look like? How do you know if your team members are doing well, compared to other DevOps teams? What does “fast” look like? Learn more about continuous integration’s impact on lead time in this post.
Set DevOps success benchmarks for your team
While there is no universal standard that every team should aspire to, there are reasonable metrics teams can use as goals. Ultimately, your ability to measure your baseline and make incremental improvements on these metrics is more valuable than chasing “ideal” numbers.
Learn how your team measures up to industry engineering metrics with our 2022 data report
Read our 2022 State of Software Delivery report to find out what we’ve learned about best practices for building great software development teams, gleaned from more than 50,000 organizations across software, healthcare, retail, finance, real estate, and media worldwide.