CAP theorem, consistency, availability, performance trade-offs.
Performance measures how fast your system handles a single request, while scalability measures how well it maintains that performance as load increases. A perfo
Latency measures how long a single request takes (time per operation), while throughput measures how many requests a system can handle per unit time (operations
Availability means always responding; consistency means all nodes see the same data. Understand this core tradeoff with CAP theorem examples for your system design interview.
CAP theorem says distributed systems can guarantee only 2 of: Consistency, Availability, Partition Tolerance. Learn CP vs AP systems with Cassandra, DynamoDB, and ZooKeeper.
Consistency patterns define how distributed systems guarantee data correctness across replicas, ranging from weak (best-effort) to strong (immediate) guarantees
Weak consistency provides no guarantees that reads will see the latest write—systems operate on a best-effort basis where stale data is acceptable. After an upd
Eventual consistency guarantees that all replicas will converge to the same state given enough time without new updates, but allows temporary divergence for hig
Strong consistency ensures all nodes see the same data immediately after a write. Learn linearizability, how banks enforce it, and the latency cost vs eventual consistency.
Availability patterns are architectural strategies that keep systems operational during failures through redundancy, fail-over, and replication. The core trade-
Fail-over automatically switches traffic from a failed primary system to a standby backup, ensuring continuous service availability. Active-passive uses a hot s
Replication creates multiple copies of data across different servers to improve availability, performance, and disaster recovery. The two primary patterns are m
Availability quantifies system uptime as a percentage, commonly expressed in "nines" (99.9%, 99.99%, etc.). Each additional nine represents 10x less downtime bu
Bloom filters answer 'have I seen this?' using minimal memory with no false negatives. Learn how Cassandra, Redis, and Chrome use them and how to size one correctly.
Consistent hashing is a distributed hashing technique that minimizes data movement when nodes are added or removed from a cluster. Instead of rehashing all keys
Merkle trees are hash-based data structures that enable efficient verification of large datasets by organizing data into a tree where each non-leaf node is a ha
PACELC extends CAP theorem by addressing the reality that distributed systems face trade-offs even when there's no network partition. The theorem states: if the
Quorum consensus ensures data consistency in distributed systems by requiring a minimum number of nodes (a quorum) to agree on read and write operations. The re