Redis
Distributed caches introduce consistency problems that single-node caches don't have. When your cache is spread across multiple Redis nodes—or when multiple application instances share a cache—the same key might return different values depending on which node serves the request. Testing these properties requires deliberate setup.
Microservices
Distributed transactions are one of the hardest problems in microservices. Two-phase commit works in theory but fails in practice — it's slow, fragile, and locks resources across service boundaries. The saga pattern solves this with a sequence of local transactions with compensating actions. But testing sagas is just
SRE
Distributed systems fail in ways that single-process systems don't. A network timeout doesn't crash your process — it makes your thread hang. A slow dependency doesn't just slow one request — it can exhaust your connection pool and bring down the whole service. Retries, timeouts,
Testing Strategy
When a test fails in a distributed system, the error message tells you what failed — not where, why, or which of the twelve services involved was responsible. Distributed tracing in your test suite gives you the full execution path for every test run, turning hours of log-digging into a
Temporal.io
Temporal.io solves distributed workflow reliability by making long-running processes durable, resumable, and observable.
Background Jobs
Background job systems fail in complex ways. A job can run twice due to a retry. A downstream service can be slow, causing queue buildup.
Temporal
Temporal workflows coordinate long-running, fault-tolerant business processes.
Temporal
Temporal and AWS Step Functions both orchestrate distributed workflows. But they differ significantly in how easy they are to test.
Conductor
Netflix Conductor is an open-source workflow orchestration engine. Workflows are defined as JSON, tasks are implemented as microservices.
AWS
AWS Step Functions orchestrate Lambda functions, ECS tasks, and other AWS services into durable workflows.