Source: thenewstack.io
‘Right-Fitting’ Performance Feedback Loops into the PipelineCategory: Software, Kubernetes, Infrastructure, automation, selenium, artificial-intelligence
Effectively implementing automated approaches to feedback loops is all about right-fitting the who/what/when/where aspects. Typically, automated feedback loops live in pipelines and continuous integration (CI).
A few solid reasons: Traditional load testing and performance testing have focused on large, complex end-to-end testing of fully baked pre-release systems.
Is it necessary for this process to inherit flaws, faults, anti-patterns and bad assumptions that we could have addressed earlier? An intelligent approach requires “right-fitting” load and performance testing into automated pipelines, so we get early signals that are actionable (i.e., feedback loops).
A few solid reasons: Traditional load testing and performance testing have focused on large, complex end-to-end testing of fully baked pre-release systems.
Is it necessary for this process to inherit flaws, faults, anti-patterns and bad assumptions that we could have addressed earlier? An intelligent approach requires “right-fitting” load and performance testing into automated pipelines, so we get early signals that are actionable (i.e., feedback loops).
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