Distributed Systems Architecture
CAP Theorem
The fundamental theorem stating that in the presence of a network partition (P), a distributed data store must choose between Consistency (C) and Availability (A).
Deep DiveHow CAP Theorem Works in Production
Under-the-hood mechanics and technical implementation details.
Technical Deep DiveDetailed Architecture
Formulated by Eric Brewer, the CAP Theorem proves that a distributed system cannot simultaneously guarantee: Consistency (every read receives the most recent write or an error), Availability (every non-failing node returns a non-error response without guarantee of latest write), and Partition Tolerance (the system continues to operate despite arbitrary message loss or delay). Since network partitions are an inevitable physical reality in distributed networks, systems are classified as either CP (e.g. HBase, CockroachDB, Raft/Paxos clusters) or AP (e.g. Cassandra, DynamoDB with eventual consistency).
Key Architectural Rule / Formula:Network Partition (P) is mandatory in distributed networks; choose CP (strict consistency) or AP (high availability).
Engineering Trade-OffsTrade-Off Dimensions & Analysis
Evaluating advantages and drawbacks during architecture interviews.
Interview ApplicationHow to Frame CAP Theorem in System Design Rounds
Senior-level talking points and related interview problems.
Interview StrategyEvaluating in Loops
Evaluated in every senior system design round when discussing database selection and multi-region replication architectures.
Related ProblemsApplied System Design Scenarios
- Payment Gateway & Financial Ledger
- WhatsApp Real-Time Chat
- Distributed Cache
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