My Projects
Explore my portfolio of backend systems, cloud infrastructure, and DevOps projects. Each project demonstrates system design principles, scalability considerations, and production-ready implementation patterns.
🛡️ Kavach - Enterprise-Grade Secret Management Platform
A comprehensive, enterprise-grade secrets management platform providing secure, scalable, and auditable secret management with multi-cloud provider integration.
Technologies Used
Key Features
- Enterprise Architecture: Clean architecture with layered design, PostgreSQL with SQLC, and comprehensive RBAC using Casbin
- Multi-Cloud Integration: GitHub, Google Cloud Platform Secret Manager, and Azure Key Vault synchronization
- Security & Compliance: End-to-end encryption, OAuth 2.0 authentication, JWT tokens, and comprehensive audit trails
- CLI Tool: Cross-platform command-line interface with multi-cloud provider integration and version control workflow
- Documentation: Professional-grade docs at docs.kavach.gkem.cloud built with Docusaurus and React
- Identity & Access Management: Fine-grained RBAC with owner, admin, editor, and viewer roles
- Secrets Management: Versioned storage with Git-like workflow, environment-based organization, and AES-256 encryption
- DevOps Excellence: Docker, Terraform, GitHub Actions CI/CD, and comprehensive testing with Testify
- Performance & Scalability: Database connection pooling, optimized queries, and horizontal scaling capabilities
TaskPilot - Production-Grade Backend System
A clean, modular, and production-grade backend system designed for managing tasks and projects, built with Go, PostgreSQL, JWT Authentication, and REST APIs.
Technologies Used
Key Features
- Secure JWT Auth: Access + refresh token rotation with context-based auth middleware
- Per-IP + Route-Based Rate Limiting: Prevent abuse using github.com/ulule/limiter/v3
- Prometheus Metrics: Per-route request counts, error tracking & latency histograms
- Clean Hexagonal Architecture: Domain-specific handlers, services, and types
- Typed DB Access with sqlc: Go code is generated from raw SQL queries, scoped per domain
- One-Command Docker Compose: Boots app, migrations, Prometheus, and PostgreSQL
- Auto Swagger Docs: Try-it-out UI + Bearer auth support
- Layered Unit Testing: Service logic and HTTP handlers tested with mocks & assertions
- Async Import/Export with RabbitMQ: Background job workers for Excel import/export
- Pluggable Cloud/Local File Storage: Unified interface to support GCP and local processing
- GitHub Actions CI: Automated test and build pipeline
Microservices Converter golang GRPC
A Go-based microservices system for media conversion with gRPC, Gin frontend, Cloud Storage, PostgreSQL, Redis, and integrated observability.
Technologies Used
Key Features
- Microservices Architecture: Built with Go (Golang), this system includes independent services for media conversion tasks such as text-to-speech, video-to-audio, and image-to-PDF.
- Frontend Service: Uses the Gin framework to provide a user-friendly interface for users to interact with the services, supporting Google Sign-In for seamless authentication.
- gRPC Communication: Backend services communicate via gRPC, ensuring fast and efficient handling of media conversion tasks and file uploads to Google Cloud Storage.
- Observability: Each service is designed to be independent, scalable, and easy to maintain, with integrated OpenTelemetry for tracing, Zipkin for visualization, and Prometheus and Grafana for monitoring. The EFK stack (Elasticsearch, Fluentd, Kibana) handles logging and visualization.
- Storage: Using Cloud Storage to store output files and storing transactional data in PostgreSQL and storing user-sessions in Redis database
Vikraya Ecommerce Microservice
A simple ecommerce deployed in multiple GKE clusters and served through Multi-Cluster-Gateway
Technologies Used
Key Features
- Orchestrated an e-commerce platform across multiple GKE clusters with a multi-cluster gateway for seamless service delivery across Global users.
- Implemented microservices architecture including frontend, authentication, cart, catalog, and order services, deployed as Kubernetes deployments and services.
- Ensured efficient and scalable session management with Redis Memorystore, while utilizing Cloud Firestore for robust data storage of user, catalog, and order information.
- Incorporated logging with Python library, Prometheus metrics for monitoring, and API gateway backed by Cloud Run for enhanced vector search capabilities.
🚀 Serverless Microservices Deployment in Azure
A comprehensive serverless microservices architecture deployed on Azure, featuring text-to-speech, PDF-to-DOCX, and video-to-audio conversion services with secure file access and enterprise-grade infrastructure.
Technologies Used
Key Features
- Frontend Service: Seamless user interface that interacts with various backend services for operations and result display
- Text-to-Speech Service: Converts user text to speech, uploads to Azure Blob Storage, and generates secure Shared Access Signatures (SAS) for time-limited access
- PDF-to-DOCX Service: Handles PDF to DOCX conversion with secure file storage and SAS-based download access
- Video-to-Audio Service: Transforms video files to audio format with secure storage and time-limited access
- Dapr Integration: Facilitates service discovery and invocation, abstracting away infrastructure complexities for simplified microservices development
- Azure File Shares: Ensures persistent and accessible file storage across all microservices for enhanced distributed storage
- Azure PostgreSQL Flexible Server: Manages transactional data including usage statistics and signed URL records for insights and performance monitoring
- Secure Authentication: Google Sign-In integration ensuring only authorized users can access the services
- Azure Container Apps: Serverless deployment environment simplifying containerized application scaling and management
- Azure Blob Storage: Secure file storage with SAS URL generation for controlled, time-limited file access
Interested in Collaborating?
Let's work together on your next cloud project or discuss potential opportunities.