Gagan Gandhi - SRE & DevOps Engineer

About Me

I'm obsessed with building systems that are reliable, scalable, and cost-efficient. The kind of systems that let engineers sleep peacefully and allow companies to scale without fear.

My journey started with a simple question: "How do we make systems that never fail?" Now, as an SRE at FarEye, I'm answering it every single day. I've reduced alert noise by 71% (from 7,000 to 2,000), optimized cloud costs by 60%, and handled load testing for 10,000 concurrent users—all because I believe that reliability isn't a feature, it's a foundation.

Whether it's setting up Kubernetes clusters, designing CDC pipelines, implementing observability stacks, or automating away manual toil—I approach every challenge with one goal: make operations invisible and operations teams heroes. I love taking complex infrastructure problems and turning them into elegant, automated solutions.

When I'm not designing systems, you'll find me exploring new DevOps tools, contributing to open-source, or helping teams understand that SRE isn't just about firefighting—it's about building fire prevention into the foundation.

Professional Experience

Real-world impact: reducing operational chaos, scaling systems, and building tools that make engineers' lives better.

Site Reliability Engineer (SRE)

FarEye • Noida, India

March 2026 – Present

Alert Intelligence: Cut alert volume by 71% (7K→2K) in 3 months by implementing intelligent alerting strategies, eliminating noise-induced alert fatigue
Production Reliability: Resolved critical production issues—pod restarts, pending states, network bottlenecks—reducing MTTR by 40%
Cost Optimization: Implemented Spot Instances in staging/UAT, achieving ~60% infrastructure cost reduction without sacrificing reliability
Developer Experience: Building internal tools to democratize Kubernetes—enabling developers to manage K8s manifests without deep platform expertise
Kubernetes Mastery: Managing production EKS clusters, handling workload optimization, scaling decisions, and security hardening

Cloud Engineer Intern

Mist Avinya • Remote

July 2025 – March 2026

Microservices Architecture: Designed and deployed production-grade banking system with Docker & Kubernetes (EKS), PostgreSQL, and Kafka
Real-time Data Sync: Built Change Data Capture (CDC) pipeline using Debezium & Kafka for live UI updates, ensuring data consistency
Observability Stack: Implemented comprehensive monitoring with Prometheus, Grafana, and custom exporters for full system visibility
Load Testing & Optimization: Stress-tested with 10,000 concurrent requests, identified bottlenecks, and optimized for production readiness
Infrastructure as Code: Designed secure infrastructure with AWS VPC, Jump Hosts, IAM policies, and auto-scaling configurations
AWS Partner Technology: Deep expertise in EC2, EKS, ECR, CloudWatch, RDS, and cost optimization

Featured Projects

Production-grade systems that prove reliability engineering isn't just about theory—it's about building systems that actually work.

🏦 Banking Platform

Production-ready microservices banking system with real-time data synchronization, comprehensive monitoring, and tested for 10K concurrent users.

Kubernetes Docker AWS EKS Kafka CDC

Architecture: Deployed 5+ microservices on EKS with auto-healing and auto-scaling
Data Consistency: Built Debezium CDC pipeline streaming PostgreSQL changes to Kafka → Elasticsearch for live updates
Security: Multi-tier VPC setup with Jump Hosts, Security Groups, and IAM policies
Load Tested: Apache Bench with 10,000 concurrent requests—no drops, no timeouts
Observability: Prometheus + Grafana + custom metrics at service, pod, and container level

📈 Zerodha Trading Platform

Stock trading platform containerized and deployed on AWS with full CI/CD pipeline, monitoring, and infrastructure automation.

Docker AWS GitHub Actions RDS

Containerization: Multi-container setup with proper networking, volume management, and environment isolation
Infrastructure: EC2 instances, RDS database, S3 storage, and Load Balancing
CI/CD: Automated build, test, and deployment using GitHub Actions—from commit to production in minutes
Monitoring: Health checks, log aggregation, and alerting for production readiness
Scaling: Auto-scaling groups and load balancer configurations for traffic spikes

View Source Code →

📋 Project Info Prints

Automation tool that eliminates manual documentation effort and streamlines project onboarding at scale.

Python Automation DevOps

Problem Solved: Reduces hours of manual documentation to minutes—because humans shouldn't copy-paste
Automation: Scans projects, generates comprehensive documentation automatically
Integration: Works seamlessly with CI/CD pipelines for automated reporting on every commit
Scalability: Handles projects of any size—from solo apps to enterprise systems
Impact: Improves onboarding time and knowledge sharing across teams

View Source Code →