Introduction

To build a distributed system, you need to understand and make trade-offs between:

• Scalability: How well the system handles increasing load. Use techniques like horizontal scaling, sharding, and load balancing.
• Availability: Ensure the system continues to function even when parts fail. Use redundancy, replication, and failover strategies.
• Consistency: Keep data synchronized across nodes. Apply techniques like consensus protocols (e.g., Raft, Paxos) and distributed transactions.
• Partition Tolerance: Handle network failures that split the system. According to the CAP theorem, a distributed system must sacrifice either consistency or availability in such scenarios.

Other important concepts include:

• Data partitioning and replication
• Service discovery
• Eventual consistency
• Distributed caching
• Rate limiting and backpressure
• Monitoring and observability

Building a distributed system involves designing with failure as a given, optimizing for communication over unreliable networks, and ensuring the system degrades gracefully under stress.

Demo Github