Consistency
8 engineering logs on Consistency. Newest first.
- R plus W greater than N is the arithmetic that decides your consistency
Why quorum overlap is the whole guarantee, what W equals one actually costs, and why the inequality holding does not save you from concurrent writes that no read can order.
- Two-phase commit is not dead, it is just expensive and you should know the price
What the coordinator actually guarantees, why a participant that has voted yes cannot do anything except wait, and why the blocking window rather than the latency is the reason people abandoned it.
- Local cache plus distributed cache: the coherence bill nobody budgets for
Why adding an in-process cache in front of Redis turns one consistency problem into N, why a pub/sub invalidation that nobody retries is a guarantee you do not have, and why the local TTL is the real bound on how wrong you can be.
- Cache invalidation is a distributed systems problem in a convenience costume
Why deleting a key after a write is a two phase commit you did not design, how the update-then-invalidate ordering produces permanent staleness, and why invalidating rather than updating is the one decision that reliably helps.
- Write-through, write-behind, write-around: picking wrong costs you consistency or throughput
What each write strategy actually guarantees when the process dies mid-operation, why write-behind is the only one that can lose acknowledged data, and why write-around is the right default more often than people expect.
- The replica lag you do not measure is the one serving checkout
Why byte lag reads zero on a broken replica, how read-your-writes breaks the moment you add a read replica, and why routing all reads to replicas is a correctness decision rather than a scaling one.
- Clock synchronization is a nightmare: Why Spanner uses TrueTime and the rest of us suffer
Why relying on system clocks causes silent data corruption and how TrueTime solves it for Spanner.
- Consistency Models in Azure Cosmos DB: From Strong to Eventual
How Azure Cosmos DB's five consistency levels map onto PACELC tradeoffs, what each level guarantees, and how to choose the right consistency for your workload.