Distributed

Flow-control mechanism: downstream signals upstream to slow producers rather than overwhelm consumers; bounded queues vs unbounded; backpressure vs load shedding (internal vs boundary); credit-based flow control; pull-based streams; anti-patterns (unbounded queues, retries defeating backpressure)

best-effort, reliable (eager/gossip), total order broadcast; consensus requirement; relationship to CRDTs and replication

HTTP caching (Cache-Control, ETag, fresh/stale, immutable static resources); reverse proxies; application-layer: side vs inline cache, LRU eviction, TTL, local vs external cache, thundering herd, cascading failure; 80% hit rate as scalability threshold

CAP theorem and PACELC extension; Kleppmann's critique ("best avoided"); timeliness vs integrity distinction

Raft, Paxos, Zab; FLP result; ZooKeeper/etcd; equivalence theorem (linearizable CAS = total order broadcast = locks = uniqueness)

Full spectrum: linearizability, sequential, causal, strong eventual, eventual; COPS causal+ implementation; isolation levels; linearizability ≠ serializability; timeliness vs integrity; safety vs liveness

CDN overlay network; BGP limitations; global DNS LB; IXP placement; edge+intermediary caching layers; DDoS shielding

data plane (on critical path, availability), control plane (off-path, consistency); static stability; scale imbalance solutions (file store buffer, push deltas, hybrid); control theory feedback loop

Conflict-free Replicated Data Types; semilattice + LUB merge; strong eventual consistency; LWW/MV registers; CALM theorem (application-level consistency, not linearizability)

ACID, 2PL, OCC, MVCC, 2PC, Spanner, Saga, Outbox; XA limitations; coordination-avoiding correctness; Newman's "just say no" to 2PC during migration

Hierarchical resolution process; TTL trade-offs; DNS as eventually consistent KV store; DNS as SPOF; static stability principle

Timeouts (fundamental limitation), pings vs heartbeats, when to use active detection; imperfect failure detection theorem

The 8 fallacies (Deutsch/Sun 1994): network reliable, latency zero, bandwidth infinite, network secure, topology fixed, one admin, transport free, homogeneous network; stamp coupling; distributed logging/transactions/contracts

HTTP/1.1 vs HTTP/2 vs HTTP/3 (QUIC); multiplexing; HOL blocking; connection management; relationship to REST

Idempotency keys (atomicity requirement, principle of least astonishment), at-least-once delivery, retry safety

Raft state machine (follower/candidate/leader); election terms; CAS+lease practical approach; fencing tokens for mutual exclusion; leader as SPOF

DNS LB, L4 (transport), L7 (application), service discovery, health checks, power of two choices, sidecar as client-side LB; stateless services as prerequisite for scale-out

Physical clock failures (drift, NTP jumps, monotonic); happened-before relation; Lamport clocks (total order); vector clocks (partial order, concurrent detection)

Key range, hash, consistent hashing, secondary indexes (local/global), rebalancing strategies, request routing; cross-partition complexity costs

Little's Law (L=λW), utilisation curves (W=S/(1−ρ)) and hyperbolic response-time growth, tail latency amplification in fan-out designs, percentile arithmetic (averages lie; can't average percentiles; t-digest/HdrHistogram), queues in series, thread pools as queueing systems; practical heuristics for capacity and tuning

Load shedding (503, priority/age ordering), load leveling (async channel + auto-scaling), rate limiting (sliding window buckets, distributed atomic increment, fail-open), constant work pattern (periodic full-state dump, antifragile, self-healing)

State machine replication (Raft), chain replication (head/tail topology, failure modes, data/control plane split), leader-follower, Dynamo-style; replication lag anomalies; multi-leader conflict resolution

definition; replication vs optimization strategies; scale up vs scale out; stateless services requirement; Amdahl's Law; hyperscale; quality attribute trade-offs (performance, availability, security, manageability); architecture evolution pattern

serverless model (pay-per-invocation, managed autoscaling); cold start by runtime; GAE autoscaling parameters; AWS Lambda (freeze/thaw, provisioned/reserved concurrency, burst limits); parameter study methodology; vendor lock-in

Link models (fair-loss/reliable/authenticated), process failure models (Byzantine/crash-recovery/crash-stop), timing models (sync/async/partial sync); default assumptions

TLS encryption (asymmetric key exchange + symmetric data), authentication (certificate chain, root CA), integrity (HMAC), handshake, certificate expiry risk