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[DL.CD.6] Refine delivery pipelines using metrics for continuous improvement

PDFRSS

Category: RECOMMENDED

Use key metrics—whether sourced from this guidance, established frameworks like DORA or SPACE, or custom to your organization—to continually optimize the development lifecycle. Metrics such as deployment frequency, change lead time, failure rate, and time to recover serve as outcome-based lagging indicators. These indicators span many DevOps capabilities to provide insights into the efficiency and reliability of the full delivery process. While individual metrics offer granular insights to optimize specific continuous delivery capabilities, these aggregated metrics present a holistic overview of the end-to-end development lifecycle. Both granular and holistic metrics are important for continuous improvement.

Use observability practices to continuously monitor the development lifecycle, including incorporating monitoring and logging into your delivery pipelines. Use logs to generate metrics, and use these metrics to identify areas for improvement. Make these metrics visible to all team members and use them to drive your continuous improvement efforts.

Putting an emphasis on continually optimizing pipelines using metrics is recommended. When getting started with DevOps adoption, initial efforts should prioritize the establishment of a stable and effective delivery pipeline, with subsequent enhancements to the pipeline being driven by metrics.

Related information:

• Deployment Pipeline Reference Architecture

• AWS Observability Best Practices: Key Performance Indicators

• DevOps Research and Assessment (DORA)

• SPACE