
Performance Tester
1 week ago
Job Description:
Own the performance engineering lifecycle—defining scope and NFRs, designing realistic load models, executing/running tests at scale, and turning results into clear tuning recommendations and capacity insights. Interface with architects, developers, and product owners and establish repeatable baselines and trends across releases.
Key Responsibilities
1) Scope Definition & API Identification
· Partner with architects/POs to shortlist critical user flows and APIs per release; confirm SLAs/SLOs and guardrail error thresholds.
· Create workload profile to mimic the real-time usage of the application
· Create/maintain a release-wise performance backlog with traceability to business flows and data variants.
2) Performance Test Design
· Build realistic load models (peak/avg mix, think times, concurrency, ramp patterns) and test data strategies.
· Define benchmarks and pass/fail criteria for response time, throughput, error rate, and resilience.
· Implement scripts and scenarios in JMeter; parameterize and correlate robustly.
· Design test types: Load (steady-state), Stress (limit), Spike (surge), Soak (endurance); plan warm-up and recovery windows.
3) Test Execution & Monitoring
· Orchestrate distributed execution (on-prem or cloud), containerized load injectors (Docker/K8s) as needed.
· Monitor KPIs and resources via APM/observability (Dynatrace/New Relic/Datadog/CloudWatch), OS metrics, DB metrics, and logs.
· Integrate runs and reports into CI/CD (Azure DevOps/Jenkins/GitHub Actions) with environment health pre-checks.
4) Analysis, Reporting & Optimization
· Perform deep-dive bottleneck analysis and provide high-level observations and recommendations (app, DB, network, GC, thread/connection pools).
· Provide actionable tuning guidance (config changes, indexing, caching, pool sizing, pagination, retries, circuit breakers).
· Produce Performance Summary Reports per cycle: setup, workload, results, findings, risks, and remediation plan.
· Establish baselines & trends across releases; highlight capacity headroom and scalability risks.
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