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kv-cache

in-memory key-value cache

Redis, Memcached

SystemTechniques · 10Primitives · 50 kv-cache Thread per coreconcurrency · medium: Shard-per-core design: pinned threads, no shared state, message passing between coresDeterministic simulation testingdistributed · medium: Run the whole system in one thread under a seeded scheduler with simulated network, disk and clock, so every failure replays from its seed.›Primary-backup replicationdistributed · medium: One node orders all writes and ships them to standbys; the acknowledgement rule (none, one, all) sets what a crash loses, and an external arbiter decides who takes over.›Coverage-guided fuzzingsecurity · medium: Mutate inputs, run an instrumented target, and keep any input that reaches a new code edge; feedback turns blind guessing into incremental search.›Point-in-time recoverystorage · medium: Periodic base backups plus a continuously archived change log let you rebuild the state as of any instant, then branch from there.›Delta debuggingcompilers · medium: Ddmin minimization of failing inputs or change setsFault injectiondistributed · medium: Inject latency, errors, kills and partitions via proxies, netem or hooksWrite-ahead logstorage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.›Copy on write snapshotsstorage · low: Point-in-time snapshots by sharing pages/extents and copying only on writeLRU and CLOCKsystems · low: LRU evicts the least recently used entry via hash map plus linked list; CLOCK approximates it with a reference bit, so hits take no lock.›S3-FIFOsystems · low: Three FIFO queues (small, main, ghost) that evict one-hit wonders quickly and keep reused objects; low miss ratios with no list moves on hits.›Hdr histogramdata-structures · low: Log-linear bucketed histograms with bounded relative error for latency percentilesHyperLogLogdata-structures · low: Counts distinct elements in kilobytes with about 1 % error by tracking the longest run of leading zero bits in hashed values per bucket.›Incremental rehashingdata-structures · low: Grow a hash table by moving a few buckets per operation to avoid latency spikesSkip listdata-structures · low: Sorted linked list with random express lanes; O(log n) search, simple inserts, and easy lock-free or single-writer concurrent reads.›Swiss tabledata-structures · low: Open-addressing hash table that filters 8-16 slots at once with 1-byte hash tags and SIMD, giving fast lookups at 87.5 % load.›Consistent hashingdistributed · low: Hash nodes and keys onto a ring; each key belongs to the next node clockwise, so membership changes move only about 1/n of keys.›Buffer pools for zero-allocation I/Ohardware-os · low: Preallocate a fixed set of aligned I/O buffers and recycle them through a free list, so the hot path never mallocs, faults or unmaps. The bounded count doubles as back pressure.›Process supervisionhardware-os · low: A parent process starts services, reaps their exits and restarts them under a delay and burst-limit policy, then stops them with SIGTERM before SIGKILL.›epoll event loopnetworking · low: One thread waits on thousands of non-blocking sockets with epoll_wait and handles only ready ones; the core of nginx, Redis and tokio.›Length-prefix framingnetworking · low: Split a byte stream (TCP, TLS, pipes) into messages by writing each message's length before it; O(1) boundary detection with no escaping.›Mutual TLSsecurity · low: TLS where the client also proves a certificate key, so every connection carries a verified, rotatable machine identity.›Graceful drainingsystems · low: On a termination signal, stop taking new work, finish in-flight work until a deadline, tell clients to reconnect elsewhere, then exit; clients resume from a token.›+ 3 more techniques+ 34 more primitives

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