distributed-systems
SolidDistributed systems patterns for locking, resilience, idempotency, and rate limiting. Use when implementing distributed locks, circuit breakers, retry policies, idempotency keys, token bucket rate limiters, or fault tolerance patterns.
Install
Quality Score: 86/100
Skill Content
Details
- Author
- yonatangross
- Repository
- yonatangross/orchestkit
- Created
- 5 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
nw-sd-patterns
Core distributed systems patterns - load balancing, caching, sharding, consistent hashing, message queues, rate limiting, CDN, Bloom filters, ID generation, replication, conflict resolution, CAP theorem
principle-distributed-systems
Distributed systems principles — CAP, PACELC, consistency models (linearizable, causal, eventual, read-your-writes), consensus (Paxos, Raft), quorum, leader election, split-brain, replication, partitioning, gossip, logical clocks (Lamport, vector, hybrid), clock skew, delivery semantics (at-most-once, at-least-once, exactly-once effects), idempotency across nodes, two-generals problem, fallacies of distributed computing. Auto-load when reasoning about CAP/PACELC trade-offs, choosing a consistency model, designing consensus or leader election, sizing quorums, ordering events with logical clocks, distinguishing exactly-once delivery from exactly-once effects, designing replication or partitioning strategy, or assessing distributed failure modes.
lamport-distributed-systems
Design distributed systems using Leslie Lamport's rigorous approach. Emphasizes formal reasoning, logical time, consensus protocols, and state machine replication. Use when building systems where correctness under concurrency and partial failure is critical.
designing-distributed-systems
When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
cloud-design-patterns
Choose and compare cloud design patterns for distributed systems. Use when reviewing architecture, selecting workload patterns, or mapping reliability, performance, messaging, security, and migration concerns to concrete design options.