Distributed Systems
2022
High-Performance Distributed Cache
Custom distributed caching solution with advanced consistency models and performance optimizations for high-traffic applications.
Go
Raft Consensus
gRPC
LevelDB
Docker
Kubernetes
Problem Statement
Traditional caching solutions struggle with consistency, performance, and scalability in distributed environments.
Solution Approach
Implemented a distributed cache with tunable consistency, automatic sharding, and intelligent data placement algorithms.
System Architecture
Gossip protocol-based cluster management, consistent hashing for data distribution, and multi-level caching hierarchy.
Technical Challenges & Solutions
Key Challenges
- Maintaining consistency in distributed environments
- Optimizing for both read and write performance
- Handling network partitions gracefully
- Implementing efficient data replication strategies
Outcomes Achieved
- 10x improvement in cache hit rates
- Sub-millisecond response times at scale
- Successfully deployed in production serving 1M+ requests/second
Performance Metrics
< 1ms
Response Time
95%
Hit Rate
1M RPS
Throughput
Lessons Learned
- The trade-offs between consistency and performance
- The importance of monitoring and observability in distributed systems
- Building systems that can evolve with changing requirements
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