> For the complete documentation index, see [llms.txt](https://docs.akamas.io/akamas-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.akamas.io/akamas-docs/3.5.0/integrating/integrating-value-stream-delivery.md).

# Integrating with pipelines

Akamas can integrate virtually with any pipeline tools to support the ability to optimize systems as part of a Continous Integration / Continous Delivery (CI/CD) process.

<figure><img src="https://3774185011-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJSNpKvJ3IYa5Vo69I0ed%2Fuploads%2Fgit-blob-224dc60a20307b4bf78b7c4118fb1cc95d59dfb8%2FScreenshot%202023-01-17%20at%2015.31.16.png?alt=media" alt=""><figcaption></figcaption></figure>

When integrated into a CI/CD process, the Akamas optimization becomes an additional step that can ensure a new version that is being released will not cause incidents due to bad configurations pushed to production that nobody has time to look at and that can require adjustments to make the new release perform best.

By integrating Akamas in the CI/CD pipeline, it is possible to also ensure the new release is not only passing functional and security tests but also that:

* performance regressions with respect to previous builds are avoided, such as regressions with respect to some key performance indicators (or SLOs) such as service response time or resource consumption;

<figure><img src="https://3774185011-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJSNpKvJ3IYa5Vo69I0ed%2Fuploads%2Fgit-blob-6f7bd46382739b41d5e47627b0fc9cb55030f0fe%2FScreenshot%202023-01-17%20at%2015.27.30.png?alt=media" alt=""><figcaption><p>Reactive optimization: in-the-pipe remediation (optimization task is triggered by quality gate)</p></figcaption></figure>

* configuration settings are properly tailored for the new release, thus avoiding configuration bottlenecks (e.g. wrong JVM settings or smaller Kubernetes pod resources for the new release) and decreasing the risk of performance or availability incidents.

<figure><img src="https://3774185011-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJSNpKvJ3IYa5Vo69I0ed%2Fuploads%2Fgit-blob-127bbacda37e34505c27a0728c245d384f0c2f32%2FScreenshot%202023-01-17%20at%2015.27.35.png?alt=media" alt=""><figcaption><p>Proactive optimization in-the-pipe</p></figcaption></figure>


---

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