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Performance Engineer

Performance Engineer

V-Soft Consulting Group, Inc.hyderabad, India
4 days ago
Job description

Performance Engineering :

  • Design and execute comprehensive Load, Stress, Endurance, Spike , and Volume tests using tools like Apache JMeter , LoadRunner , or NeoLoad .
  • Build robust performance test frameworks tailored for microservices hosted on EKS .
  • Conduct end-to-end performance benchmarking across API, database, and UI layers.

AWS Cloud and EKS Focus :

  • Work directly with AWS services such as EKS, EC2, S3, RDS, CloudWatch , and Application Load Balancer (ALB) during test planning and execution.
  • Simulate real-world distributed load in EKS-based environments and evaluate auto-scaling behaviors , node performance , and pod-level resource usage .
  • Collaborate with DevOps to ensure test pods are deployed and scaled properly in Kubernetes clusters.

    • Monitoring & Observability :

  • Use tools like Grafana , CloudWatch , Prometheus , Datadog , and New Relic to monitor performance metrics in real time.
  • Analyze system behavior through dashboards, logs, and alerts to identify performance bottlenecks and degradation.
  • Capture pod-level metrics (CPU, memory, network) from Kubernetes namespaces and workloads under test.

    • CI / CD and Automation Integration :

  • Integrate performance test suites into CI / CD pipelines using tools like Jenkins , GitHub Actions , or AWS CodePipeline .
  • Ensure automated execution of performance tests as part of build validations and release gates.

    • Reliability & Caching Validation :

  • Validate caching layers (Redis, CDN, Memcached) and their impact on response time under high load.
  • Provide recommendations to improve system reliability, latency, and throughput using test results and observability data.

    • Must-Have Skills :

  • 8+ years in Performance Testing & Engineering
  • Strong expertise with JMeter , Neo Load , or similar tools
  • Solid hands-on experience with AWS and especially EKS (pods, nodes, services, auto-scaling)
  • Strong understanding of Kubernetes workloads, Helm charts, and config maps
  • Familiarity with monitoring and logging in cloud-native environments : Grafana, CloudWatch, Datadog, Prometheus
  • Basic scripting in Python , Shell , or Groovy
  • Experience in testing REST APIs, microservices , and containerized applications

    • Nice-to-Have :

  • AWS Certification (Cloud Practitioner, Developer Associate, or DevOps Engineer)
  • Experience with Terraform , Helm , or Kustomize
  • Familiarity with chaos testing or resilience validation

    • Experience with service mesh performance

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