Portfolio

Case study: Infrastructure Reliability (SRE)

Industry: High-Traffic E-commerce / AI-Native Platforms
Built for DevOps teams and Product Owners to ensure 24/7 availability and "four-nines" (99.99%) uptime during high-velocity growth.

Problem

  • Manual Scaling Failures: Sudden traffic spikes from marketing campaigns caused frequent "cascading failures" and site crashes.
  • Observability Gap: The team only discovered site outages when customers complained on social media.
  • Slow Recovery (MTTR): Identifying the root cause of an infrastructure failure took an average of 3 hours of manual log-diving.
  • Configuration Drift: Manual changes to servers made the infrastructure impossible to replicate or scale reliably.

Solution

  • Kubernetes Orchestration: Migrated the legacy application to a managed Kubernetes cluster (EKS) with Horizontal Pod Autoscaling (HPA).
  • Infrastructure as Code (IaC): Defined the entire environment using Terraform, ensuring 1:1 parity between Staging and Production.
  • Proactive Observability: Deployed a Prometheus and Grafana stack to monitor "Golden Signals" (Latency, Errors, Traffic, Saturation) in real-time.
  • Automated Incident Response: Configured n8n to trigger automated self-healing scripts and alert on-call engineers via PagerDuty/Telegram.

Tech Stack

  • Platform: Kubernetes (EKS) & Docker.
  • Provisioning: Terraform (Infrastructure as Code).
  • Monitoring: Prometheus, Grafana, and OpenTelemetry.
  • Automation: n8n (Alert routing and auto-remediation).

Results

  • Uptime Milestone: Increased availability from 98.5% to 99.99% over a 6-month period.
  • Detection Speed: Reduced Mean Time to Detect (MTTD) from 45 minutes to under 120 seconds.
  • Scalability: The system now automatically scales from 2 to 50+ nodes during traffic spikes without manual intervention.
  • Deployment Safety: Zero-downtime rolling updates eliminated the "Sunday night maintenance" window.
DevOps & SRE