DevOps Engineer | Mumbai, India
Reduction in Deployment Time
Cloud Cost Optimization
Improved Code Reliability
Results-driven DevOps Engineer with 4+ years of experience in automating, optimizing, and managing cloud-native infrastructure on AWS. Specialized in Kubernetes (EKS), Terraform, and CI/CD pipeline engineering. Adept at bridging development and operations to enable faster and more reliable software delivery.
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Live mock representation of system health and EKS cluster metrics.
All Systems Operational
Target: < 200ms
DevOps Engineer | Mumbai, India
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End-to-End Automation
Scalability & Efficiency
Automation & Consistency
How I approach and resolve high-severity production issues.
Simulate my debugging process below.
Action: Check CloudWatch Alarms and Grafana Dashboards.
Finding: CPU on node group `worker-nodes-a` is at 95%. Specific pods for the `payment-service` are maxing out their limits.
Action: Run `kubectl logs` and `kubectl top pods` for the affected service. Temporarily scale up HPA `maxReplicas` to absorb traffic.
Finding: Logs reveal a runaway process loop in the latest deployment. Scaling HPA stabilizes API latency temporarily.
Action: Initiate an immediate ArgoCD rollback to the previous stable Helm chart version. Coordinate with dev team to patch the loop.
Result: System restored to 100% health in < 15 mins. Post-mortem document created to implement stricter SonarQube rules for loop complexity.
Actual configurations demonstrating syntax and best practices.
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