Event-Driven Microservices Platform
Scalable event-driven microservices platform built with Node.js, Apache Kafka, and Docker, featuring automated deployment, monitoring, and fault tolerance patterns used in production by 3 enterprise clients.
Overview
Architected and implemented a comprehensive event-driven microservices platform that enables organizations to build scalable, resilient distributed systems. This project combines Brandon's systems architecture expertise with modern cloud-native technologies to create a platform that handles high-throughput event processing while maintaining data consistency and operational simplicity. The platform provides a complete ecosystem for event-driven architecture including event sourcing, CQRS patterns, saga orchestration, and distributed tracing. It emphasizes developer productivity through comprehensive tooling, automated testing, and deployment pipelines, while maintaining production-grade reliability through built-in fault tolerance and monitoring. Currently deployed in production environments processing millions of events daily, the platform has proven its scalability and reliability across diverse use cases from e-commerce to financial services.
Technical Stack
Core Platform
- ▸Node.js
- ▸TypeScript
- ▸Apache Kafka
- ▸Redis
- ▸PostgreSQL
- ▸MongoDB
Container Orchestration
- ▸Docker
- ▸Kubernetes
- ▸Helm
- ▸Istio Service Mesh
- ▸Ambassador Gateway
Monitoring & Observability
- ▸Prometheus
- ▸Grafana
- ▸Jaeger
- ▸ELK Stack
- ▸Sentry
- ▸DataDog
Development & CI/CD
- ▸GitHub Actions
- ▸Terraform
- ▸Pulumi
- ▸Jest
- ▸Cucumber
- ▸SonarQube
Key Features
Event sourcing with automatic snapshot management
CQRS implementation with optimized read/write models
Saga pattern orchestration for distributed transactions
Automatic service discovery and load balancing
Built-in circuit breakers and retry mechanisms
Comprehensive monitoring and alerting system
Blue-green deployment with canary release support
Multi-tenant architecture with resource isolation
Code Examples
Technical Challenges
Maintaining data consistency across distributed services
Implementing efficient event replay and reprocessing mechanisms
Designing fault-tolerant saga orchestration patterns
Optimizing Kafka partition strategies for high throughput
Creating comprehensive integration testing for distributed systems