--- title: Building a Test Matrix Pipeline for Couchbase Autonomous... description: A software engineering intern at Couchbase describes the design and implementation of a Test Matrix Pipeline for the Couchbase Autonomous Operator (CAO). The... canonical: https://daily.dev/posts/building-a-test-matrix-pipeline-for-couchbase-autonomous-operator-0dfefhtnb twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Building a Test Matrix Pipeline for Couchbase Autonomous Operator | daily.dev og:description: A software engineering intern at Couchbase describes the design and implementation of a Test Matrix Pipeline for the Couchbase Autonomous Operator (CAO). The... og:url: https://daily.dev/posts/building-a-test-matrix-pipeline-for-couchbase-autonomous-operator-0dfefhtnb og:image: https://api.daily.dev/og/posts/0dFefHTnb.png og:image:alt: Building a Test Matrix Pipeline for Couchbase Autonomous Operator og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Building a Test Matrix Pipeline for Couchbase Autonomous Operator **[Couchbase](https://daily.dev/sources/couchbase)** · 10 min read · 1 upvotes · 0 comments ## Summary A software engineering intern at Couchbase describes the design and implementation of a Test Matrix Pipeline for the Couchbase Autonomous Operator (CAO). The pipeline continuously validates compatibility across four dimensions: Kubernetes/OpenShift versions, CAO versions, Couchbase Server versions, and cloud providers (EKS, GKE, AKS). Built on Jenkins and orchestrated by three Go programs (dispatch, execute, rerun), the pipeline generates all version combinations when any component changes, filters tests using a YAML-based tagging system (trigger tags, version constraints, subcomponent tags), and handles infrastructure failures with incremental result persistence and a dedicated rerun stage. The post also covers the challenges of parallelizing test execution, including resource contention, varying isolation requirements, and result tracking complexity, proposing a Scenario Aggregator approach to group shared vs. isolated tests. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How do you design a test matrix pipeline to validate compatibility across Kubernetes, an operator, and a database across multiple versions? Use a four-dimensional version matrix covering platform (Kubernetes/OpenShift), operator version, database version, and cloud provider. Whenever a new build of any component appears, that version becomes the fixed trigger while the pipeline generates all combinations across the remaining three dimensions, producing dozens of independent test executions such as up to 27 combinations from three platform, database, and cloud provider versions. _Engineers designing multi-dimensional compatibility test pipelines can find similar architecture writeups curated on daily.dev._ ### How can I avoid running irrelevant tests when only one component in a compatibility matrix changes? Embed trigger tags, minimum/maximum version constraints, and subcomponent tags directly in each test's YAML scenario file so the pipeline only runs tests relevant to the component that changed. For example, RBAC tests run on operator or server builds but are skipped for pure Kubernetes patch updates, since authentication logic is largely independent of platform-level changes. _Anyone tuning CI pipelines to cut wasted test runs can track these tagging patterns on daily.dev._ ### How should a CI pipeline recover from infrastructure failures mid test run without losing progress? Persist results incrementally to a results.json file after every single test completes, then implement a rerun stage that reads a previous build's results, identifies tests never reached, and resumes execution only for incomplete matrix combinations while writing to a separate rerun-results.json to preserve the original run as a source of truth. _Teams building resilient CI infrastructure can follow more resumable pipeline designs via daily.dev._ ## Similar posts on daily.dev - [Agents have made CI the bottleneck. 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