Lesson 1Consistency models: strong, causal, eventual, read-your-writes, monotonic readsDives into distributed consistency types like strong, causal, and eventual, plus read-your-writes and monotonic reads, breaking down what they promise, weird glitches they avoid, and how apps pick ones that fit user needs.
Strong consistency guaranteesEventual consistency and convergenceCausal consistency and orderingRead-your-writes and monotonic readsChoosing models for applicationsLesson 2Distributed consensus algorithms: Paxos, Raft, and practical implementations (etcd, Consul)Introduces Paxos and Raft agreement methods and their jobs in picking leaders, copying logs, and changing setups, linking theory to real tools like etcd and Consul for metadata, locks, and teamwork.
Consensus problem and safety goalsPaxos algorithm core ideasRaft algorithm and log replicationCluster membership and reconfigurationUsing etcd and Consul in practiceLesson 3Sharding and partitioning strategies: range, hash, and directory-basedGoes into sharding and splitting tactics like range, hash, and directory methods, zeroing in on spreading data, dodging busy spots, rebalancing, and directing traffic, plus picking and growing a plan as loads and data expand.
Range-based partitioning designHash-based sharding and hashingDirectory and lookup-based routingRebalancing and resharding methodsAvoiding hotspots and skewed keysLesson 4Replication models: leader-follower, multi-leader, and leaderless patternsLooks at leader-follower, multi-leader, and no-leader copying setups, explaining write and read routes, handling failures, delays, and fixing clashes, and how each hits wait times, speed, toughness, and ops hassle in worldwide setups.
Leader-follower replication flowsMulti-leader replication and conflictsLeaderless quorum-based replicationReplication lag and read consistencyOperational trade-offs of each modelLesson 5CAP theorem and trade-offs between consistency, availability, and partition toleranceUnpacks the CAP theorem and what it means for spread-out databases, making clear how consistency, uptime, and split-handling mix, and how actual systems handle swaps using real designs and service targets.
Formal statement of the CAP theoremConsistency vs availability in practicePartition tolerance in real networksDesigning around CAP with SLAsLesson 6Network partitions, latency, and failure modes across WAN linksChecks out how network splits, delays, and breakdowns show up over wide-area links, covering timeouts, half-failures, and split-brain risks, plus designing spotting, retries, and fallback plans to keep things steady under pressure.
Characteristics of WAN linksDetecting partitions and timeoutsHandling partial and asymmetric failuresSplit-brain risks and mitigationGraceful degradation strategiesLesson 7Idempotency, retries, and at-least-once vs exactly-once semanticsSpells out idempotency and its part in safe retries, sorting at-least-once, at-most-once, and exactly-once meanings, with ways for deduping, tracking requests, and handling messages in shaky spread-out setups.
Defining idempotent operationsDesigning safe retry mechanismsAt-least-once vs at-most-onceExactly-once semantics limitationsDeduplication and request trackingLesson 8Concurrency control: optimistic vs pessimistic, MVCC, conflict resolution techniquesLooks closely at concurrency handling in spread-out databases, pitting hopeful against wary methods, unpacking MVCC workings, and showing clash spotting and fixing tricks that keep things right while allowing lots of parallel work.
Pessimistic locking in distributed systemsOptimistic control and validationMVCC snapshots and version chainsConflict detection and resolutionDeadlocks, timeouts, and retriesLesson 9Physical topology patterns: single region, active-passive, active-active, and hybridOutlines physical setup shapes for spread-out databases like single area, active-passive, active-active, and mixed types, weighing their effects on delays, switchovers, data sameness, and running trouble.
Single-region deployment trade-offsActive-passive failover patternsActive-active multi-region setupsHybrid and tiered topology designsLatency, RPO, and RTO considerations
