Advanced Topics
Consensus algorithms, distributed transactions
Circuit Breaker Pattern: Building Resilient Distributed Systems
The circuit breaker pattern prevents cascading failures in distributed systems by stopping requests to a failing service. Like an electrical circuit breake...
Consistent Hashing: Scalable Data Distribution
Consistent hashing is a distributed hashing technique that minimizes the number of keys that need to be remapped when the hash table is resized. Traditiona...
Data Synchronization: Conflict Resolution and Offline-First Architectures
Data synchronization is the process of keeping data consistent across multiple replicas, devices, or data centers. In distributed systems, conflicts are in...
Distributed Locks: Coordination in Distributed Systems
Distributed locks provide mutual exclusion across multiple processes or machines. Unlike local locks (mutexes) that work within a single process, distribut...
Distributed Transactions: Saga Pattern, Outbox, and Event-Driven Approaches
Distributed transactions are one of the hardest problems in system design. When a business operation spans multiple services or databases, ensuring atomici...
Gossip Protocol: Decentralized Information Dissemination
Gossip protocols (also called epidemic protocols) are decentralized communication mechanisms where nodes periodically exchange state information with rando...
Idempotency in Distributed Systems: Designing Safe APIs
Idempotency is the property of an operation where performing it multiple times produces the same result as performing it once. In distributed systems where...
Leader Election in Distributed Systems
Leader election is a fundamental problem in distributed computing where a group of nodes must agree on a single node to act as the coordinator or leader. T...
Handling Partial Failures in Distributed Systems
Partial failures are the defining challenge of distributed systems. Unlike single-machine programs where the system either works or crashes completely, dis...
Quorum Systems: Tunable Consistency in Distributed Databases
Quorum systems are the foundation of tunable consistency in distributed databases. A quorum is the minimum number of nodes that must participate in a read ...
Rate Limiting in Distributed Systems: A Complete Guide
Rate limiting is a critical technique for controlling the rate of requests that clients can make to a service. It protects your infrastructure from abuse, ...
Service Discovery in Distributed Systems
Service discovery is the process by which services in a distributed system find and communicate with each other. In a dynamic environment where services sc...
Three-Phase Commit (3PC): Non-Blocking Distributed Transactions
Three-Phase Commit (3PC) is an extension of the Two-Phase Commit (2PC) protocol designed to eliminate the blocking problem. By introducing an additional pr...
Two-Phase Commit (2PC): Distributed Transaction Coordination
Two-Phase Commit (2PC) is a distributed algorithm that ensures all participants in a transaction either commit or abort atomically. It is the classic solut...
Vector Clocks: Tracking Causality in Distributed Systems
Vector clocks are a mechanism for tracking the partial ordering of events in a distributed system. They allow you to determine whether two events are causa...
Bloom Filters: Space-Efficient Probabilistic Data Structures
Bloom filters are probabilistic data structures that test whether an element is a member of a set. They are incredibly space-efficient but allow for false positives...
Merkle Trees: Efficient Data Verification in Distributed Systems
Merkle trees are hash-based data structures that enable efficient and secure verification of data integrity in distributed systems, used in Git, blockchain, and databases...
Distributed Consensus: Paxos, Raft, and Beyond
Distributed consensus algorithms enable multiple nodes to agree on a single value despite failures. Explore Paxos, Raft, and Byzantine fault tolerance...