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@@ -15,8 +15,8 @@ This project is focused on helping you collect and analyze four key high perform
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-**Mean time to restore (MTTR): How quickly restoration of production occurs in an outage or degradation.** When there is a degradation, how quickly can the system auto-heal itself, scale to handle increased load, and/or This one is contraversal, as it's challenging to compare different events that cause degradation.
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-**Change failure rate: After a production deployment, was it successful? Or was a fix or rollback required after the fact?** How often is a change we made 'successful'? This ties in well with deployment frequency and lead time for changes, but is challenging to measure - as it requires a signoff off of success. Not just that the code deployed correctly, but that there weren't adverse effects or degradation of the deployment to the system
(Chart from [page 11 of state of DevOps 2022 report](https://cloud.google.com/devops/state-of-devops))
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A [demo website displaying the metrics can be viewed here](https://devops-prod-eu-web.azurewebsites.net/).
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More information about high performing DevOps metrics can be found in a [blog post here](https://samlearnsazure.blog/2020/04/30/high-performing-devops-metrics/)
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@@ -79,7 +79,7 @@ Dependabot runs daily to check for dependency upgrades.
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## Badges
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The API can generate a URL for static badges, but more work is needed. Some current samples are shown below:
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