Building resilient, automated cloud infrastructure across AWS, Azure & GCP. Turning complex infrastructure into elegant, scalable systems.
Real-time dashboards using AWS CloudWatch and Grafana. Slack-integrated alerts reduced incident response time by ~40%.
Reusable Terraform modules for EC2, VPC, IAM, and S3. Full IaC versioned in GitHub for reproducible infrastructure.
Production-grade AWS 3-tier setup: EC2 + RDS + S3 with ALB, Auto Scaling, NAT Gateway, and security groups.
Fully serverless API backend using Lambda + API Gateway + DynamoDB — zero server management, auto-scaling.
Multi-stage pipelines for Node.js: code commit → container build → AKS deployment with automated rollback on failure.
Provisioned Azure VMs via ARM Templates with Azure Monitor alerts and Log Analytics Workspace for full observability.
Containerized microservices on GKE with Cloud Load Balancing, horizontal pod autoscaling, and Cloud Logging integrated.
Python Flask API on Cloud Run — auto-scales to zero. Cloud Build triggers automated image builds on every Git push.
End-to-end Jenkins pipeline: Maven build → SonarQube quality gate → Docker container → automated deploy to AWS EC2.
Dockerized app deployed on Kubernetes with rolling updates, liveness probes, and LoadBalancer service exposure.
Ansible playbooks automating server config and app deployment — consistent environments, zero manual config drift.
Unified Grafana dashboard aggregating AWS, Azure & GCP cost metrics for cross-cloud spending visibility and optimization.