
Developed and delivered an automated Self Node Remediation (SNR) end-to-end weekly testing job for the openshift/release repository, focusing on increasing reliability and reducing manual QA effort in SNR validation. Leveraged CI/CD and DevOps practices to configure a periodic AWS-based test workflow, utilizing Kubernetes and YAML for orchestration and job configuration. Integrated medik8s catalogsource and operator-subscribe steps, enabling automated validation of the SNR workflow through make-based test execution. The solution established a consistent Sunday testing cadence, improved early regression detection, and aligned with existing testing patterns, contributing to a more robust and maintainable SNR testing framework within the project.
June 2026 monthly summary for openshift/release focused on SNR test automation. Key feature delivered: Self Node Remediation (SNR) End-to-End Weekly Testing Job. No major bugs fixed this month. Overall impact: increased reliability and automation of SNR validation, reducing manual QA effort and enabling earlier detection of regressions. Technologies/skills demonstrated: AWS m5.xlarge-based testing environment, medik8s catalogsource and operator-subscribe steps, end-to-end test orchestration using make run-tests with ECO_TEST_FEATURES=snr-operator, pattern reuse from FAR/SBR, Git-based change management (PR #80587, RHWA-1080).
June 2026 monthly summary for openshift/release focused on SNR test automation. Key feature delivered: Self Node Remediation (SNR) End-to-End Weekly Testing Job. No major bugs fixed this month. Overall impact: increased reliability and automation of SNR validation, reducing manual QA effort and enabling earlier detection of regressions. Technologies/skills demonstrated: AWS m5.xlarge-based testing environment, medik8s catalogsource and operator-subscribe steps, end-to-end test orchestration using make run-tests with ECO_TEST_FEATURES=snr-operator, pattern reuse from FAR/SBR, Git-based change management (PR #80587, RHWA-1080).

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