Deployment Time

How to discover bottlenecks in the deploy process and how to turn that into something actionable

José Caldeira avatar
Written by José Caldeira
Updated over a week ago

In the Deployment view, the Athenian API gathers information on deployment, so you can track your releases depending on which environment they’re deployed to – whether that’s Staging or Production, or any other configuration you have.

Deploy Time = Deploy to Production - Release Event

Release Event = Merge to Branch or Tag Created or API Call

You can use our deployment API to notify us when releases are deployed to specific environments in order to understand the lead time to deploy.

How to use Athenian to improve the deploy process

Deploy Dashboard

The insights section shows you the total number of Pull Requests deployed to your environments, the deployment frequency, and a breakdown of deployments month-by-month for your chosen time frame.

Beneath this you can see a graph charging how the PR Cycle Time to your environments has changed over this time period.

📢 One of the most important metrics here is the Success Ratio, which will help you understand how successful your deployment process is. This metrics is considering the number os successful deploys, as described by our API, over the total number of deploys.

Scroll down further and you can see the same insights for Pull Requests deployed to any environment you decide to track.

🔎 What you to look for?

  • Look for differences in the Deploy Cycle Time between your environments. What might be causing differences in deployment times?

  • Is there a difference in the deployment frequency between environments?

  • Are some items skipping an environment? Why?

  • Are you piling up code in any environment, like Staging?

  • Are team members afraid of deploying to Production?

🚀 Actions to improve

  • If you have a deployment success ratio below 95% to Production, prioritize fixing that. Otherwise you’ll always struggle to decrease your Pull Request Cycle Time, because deployments will always slow you down.

  • Automate deployments to ensure you are able to quickly react to any issues that may emerge.

  • Minimize time between deploying the multiple environments, e.g. between Staging and Production, having code stopped on Staging will most of the times not decrease the risk to deploy to Production.

  • Define deployment risk mitigation strategies, like blue green deployment, to allow you to deploy with more confidence.

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