Consensus Algorithms in Replicated Systems
Consensus algorithms ensure that all replicas in a distributed system agree on a common state, even in the presence of failures. They are critical for maintaining consistency and reliability in replicated systems.
- Paxos: A family of protocols for achieving consensus in a network of unreliable processors. Proven to be fault-tolerant and highly reliable. Distributed databases, coordination services (e.g., Google Chubby).
- Raft: A consensus algorithm designed to be easier to understand than Paxos, with a strong leader approach. Simplicity and ease of implementation while maintaining reliability. Distributed storage systems, configuration management (e.g., etcd, Consul).
- ZAB (Zookeeper Atomic Broadcast): The protocol used by Apache Zookeeper to ensure consistency across a distributed system. Guarantees total order broadcast, which is essential for coordination tasks. Coordination services, naming services.
Replication in System Design
Replication in system design involves creating multiple copies of components or data to ensure reliability, availability, and fault tolerance in a system. By duplicating critical parts, systems can continue functioning even if some components fail. This concept is crucial in fields like cloud computing, databases, and distributed systems, where uptime and data integrity are very important. Replication enhances performance by balancing load across copies and allows for quick recovery from failures.
Important Topics for Replication in System Design
- What is Replication?
- Importance of Replication
- Replication Patterns
- Data Replication Techniques
- Consistency Models in Replicated Systems
- Replication Topologies
- Consensus Algorithms in Replicated Systems