Using Distributed Systems

Overview

Correctness-under-partition is an architectural property, not effort. A network will partition, a node will crash mid-write, a message will arrive twice, and a clock will jump backwards — these are not edge cases, they are the operating environment. A distributed system either has a named consistency contract per operation, a written failure model that every other choice traces back to, idempotent effects, bounded queues, and a test strategy that injects the faults it claims to survive — or it has a pile of hopeful assumptions that hold exactly until the first packet drop.

This pack produces a numbered distributed-system/ artifact set governed by a consistency gate. The gate's only job is to make silent, un-named choices impossible: every guarantee must be named, traced to the failure model, priced, and tested. "Mostly consistent", "should be fine", and an un-scoped "we use strong consistency" are gate failures, not answers.

This is architecture, not operations. It tells you what guarantee each channel provides under partition and why — not how to wire a Helm chart or tune a Kafka broker.

When to Use

Use this pack when:

• Your system spans more than one process, machine, or failure domain and a partition or crash must not corrupt state.
• You see the symptoms: split-brain (two leaders), lost writes under partition, duplicate processing, stuck or partially-applied sagas, retry storms amplifying an outage, two writes to two stores drifting apart, or "passes in staging, collapses under real load."
• You are adding a second region, sharding a dataset, introducing cross-service transactions, or putting a queue between two services — any of which changes the failure model.
• A team has invented private meanings for "consistent", "exactly-once", "ordered", or "eventually" and the words do not agree across services.
• You need to decide, honestly, whether to distribute at all.