Distributed System Patterns

The Distributed System Patterns section will cover essential patterns used to design scalable, resilient distributed systems, all implemented using Golang. It will begin with Data Replication, focusing on algorithms like Raft, Paxos, and election algorithms for achieving consensus and ensuring data availability. Next, it will address Data Partitioning, explaining techniques such as fixed partitioning for efficient data distribution across nodes. The section will also explore Consistency, covering models like strong and eventual consistency, followed by Distributed Time, where synchronization strategies such as Lamport timestamps will be demonstrated. Cluster Management will cover node management, including scaling and fault detection, and Communication Between Nodes will illustrate methods like gRPC and REST for reliable service interactions. The section will then discuss Agreement Algorithms such as Two-Phase Commit, Raft, and Paxos for achieving consensus on state changes, along with Fault Tolerance and Resilience, focusing on mechanisms like retries and circuit breakers to handle failures. Coordination Systems will explore leader election and distributed locking, while Security will cover encryption and authentication to secure inter-node communication. The Distributed Ledger part will introduce blockchain concepts and basic ledger implementation, followed by Distributed Knowledge Management and Distributed Data Management to handle large-scale data coordination and retrieval. Lastly, Distributed Shared Memory will explain how to provide a unified memory view across nodes. Each pattern will be illustrated with Golang implementations, providing practical insights into building distributed systems.

Every Code of any Pattern You Will Find It Here: https://github.com/EncrypteDL