
Validation and performance Automation
3 weeks ago
Job Title: Validation and Performance Automation
Location: Pan India
Work Mode: Hybrid
Experience: 8+ years (6 years Relevant)
Job Type: Contract to hire (C2H)
Notice Period: - Immediate joiners.
Mandatory Skills: · pytest, Go, k6 scripting, automation frameworks integration (Sonobuoy, LitmusChaos), CI integration
Additional Skills:
· Design and implement automated, GitOps-compliant pipelines for validation and certification of the GPU cloud stack across hardware, OS, Kubernetes, and platform layers.
· Integrate Sonobuoy for Kubernetes conformance and certification testing.
· Design and orchestrate chaos engineering workflows using LitmusChaos to validate system resilience across failure scenarios.
· Implement performance testing suites using k6 and system-level benchmarks, integrated into CI/CD pipelines.
· Develop and maintain end-to-end test frameworks using pytest and/or Go, focusing on cluster lifecycle events, upgrade paths, and GPU workloads.
· Ensure test coverage and validation across multiple dimensions: conformance, performance, fault injection, and post-upgrade validation.
· Build and maintain dashboards and reporting for automated test results, including traceability, drift detection, and compliance tracking.
· Collaborate with infrastructure, SRE, and platform teams to embed testing and validation early in the deployment lifecycle.
· Own quality assurance gates for all automation-driven deployments.
Required Skills & Experience
· 10+ years of hands-on experience in infrastructure engineering, systems validation, or SRE roles.
· Primary key skills required are pytest, Go, k6 scripting, automation frameworks integration (Sonobuoy, LitmusChaos), CI integration
· Strong experience with:
o Sonobuoy for Kubernetes conformance and diagnostics
o LitmusChaos for fault injection and resilience validation
o k6 for performance/load testing in distributed environments
o pytest or Go-based test frameworks for automation and validation scripting
· Deep understanding of Kubernetes architecture, upgrade patterns, and operational risks.
· Experience validating infrastructure components (GPU drivers, kernel modules, CNI, CRI, etc.) across lifecycle events.
· Proficient in GitOps workflows and integrating tests into declarative, Git-backed pipelines (e.g., with Argo CD, Flux).
· Hands-on experience with CI/CD systems (e.g., GitHub Actions, GitLab CI, Jenkins) to automate test orchestration.
· Solid scripting and automation experience (Python, Bash, or Go).
· Familiarity with GPU-based infrastructure and its performance characteristics is a strong plus.
· Strong debugging, root cause analysis, and incident investigation skills.
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