Project Overview
Designed and implemented a globally distributed event streaming platform that handles massive-scale real-time data processing across multiple geographic regions, ensuring data consistency and minimal latency.
Architecture Components
Event Processing System
- Multi-cluster Kafka deployment
- Custom partition management
- Exactly-once delivery
- Dead letter queues
- Schema registry
- Event replay capability
- Real-time monitoring
Data Flow Architecture
- Cross-datacenter replication
- Conflict resolution
- Message transformation
- Stream processing
- Data compaction
- Topic management
- Consumer group balancing
Technical Implementation
Infrastructure
- Kubernetes-based deployment
- Custom operators for automation
- Istio service mesh
- Prometheus monitoring
- Grafana dashboards
- ELK stack for logging
- Multi-region failover
Development
- Go microservices
- Protocol buffers
- gRPC communication
- Custom serialization
- Rate limiting
- Circuit breakers
- Distributed tracing
Performance Optimizations
- Message batching
- Compression algorithms
- Memory management
- Network optimization
- Disk I/O tuning
- Cache strategies
- Thread pool management
Security Measures
- End-to-end encryption
- SASL authentication
- ACL management
- Audit logging
- Network isolation
- Secret management
- Security scanning
Business Impact
- 1M+ events/second throughput
- 99.999% availability
- < 10ms latency at p95
- 70% cost reduction
- Zero data loss
- 5x performance improvement
- 24/7 global availability
- 40% resource optimization