Automating Deployment Pipelines with Machine Learning

Three Takeaways:

QA, Testing and deployment verification remains a manual task for dev/ops teams, several hours are added to a typical deployment pipeline (dev > prod)

Metrics, Telemetry, and application events are readily available from run-time, logs, and tools, but are fragmented and require human interpretation

Machine Learning and NLP algorithms can be used to automate QA/testing/verification (the interpretation of time-series metrics and unstructured data)

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