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Sleuth

Mean Time to Recovery (MTTR) explained

It's Friday afternoon, and you have mail. Apparently, a user received a 500 error when attempting to sign in. She contacted Customer Service. They didn't know what to do, so they forwarded the email to your engineering team. A close look at the email thread reveals that Customer Service received it... on Tuesday. And they sat on it until today. ‍ Hopefully, it was just this one user. You open your browser, navigate to the web application, and attempt to sign in. You also get a 500 error.

How Sleuth measures Change Lead Time

Change Lead Time can be considered the most insightful of the four DORA metrics. But how do you measure it most accurately? In this video, Don Brown shows you how Sleuth measures Change Lead Time for code changes and how Sleuth breaks down that time into multiple buckets for the most detailed insight on what's slowing your team down. Check out these videos on how Sleuth measures other DORA metrics.

How Sleuth measures Change Failure Rate

Before you can measure the DORA metric for Change Failure Rate, you need to define what failure means. In this video, Sleuth's CTO Don Brown explains how Sleuth defines and measures Change Failure Rate, and how it ties failure back to deployments. Check out these videos on how Sleuth measures other DORA metrics: Give Sleuth a try and see why it's a deploy-based Accelerate / DORA metrics tracker both managers and developers love.

How Sleuth measures Mean Time to Recovery (MTTR)

The DORA metric Mean Time to Recovery (MTTR) tracks how long on average your failure spans are. In this video, Sleuth CTO Don Brown explains how Sleuth calculates this measurement, which gives you insight on how quickly your team can respond to and recover from failure. Check out these videos on how Sleuth measures other DORA metrics: Give Sleuth a try and see why it's a deploy-based Accelerate / DORA metrics tracker both managers and developers love.

Change Failure Rate explained

This post is the third in a series of deeper dive articles discussing DORA metrics. In previous articles, we looked at: The third metric we’ll examine, Change Failure Rate, is a lagging indicator that helps teams and organizations understand the quality of software that has been shipped, providing guidance on what the team can do to improve in the future.