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To learn distributed systems by breaking them, start with a specific guarantee, run operations that test it, inject failures, and check the resulting history against the guarantee. For example: if a client receives confirmation that a write succeeded, should that write still be visible after one node crashes? That is an illustrative test question, not a universal promise—each system’s documented guarantees determine what counts as correct.
Diagrams help explain components and message paths. Failure testing shows what an implementation actually does when those paths or components stop behaving as expected.
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What does a failure test actually test?
A distributed-systems test compares observed behavior with an explicit property. Jepsen describes a process that characterizes a system’s design and claims, generates operations, introduces faults, and checks the resulting operation history against a model. Jepsen’s analyses show how this approach is applied to real systems.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minute- Choose a guarantee. State what must remain true, such as whether acknowledged writes may disappear or whether reads may return stale data. Use the system’s documented semantics to define the boundary.
- Run a workload. Have clients perform meaningful operations, such as reads and writes, while recording their calls, responses, and timing.
- Inject a fault. Disrupt a process, network path, clock, or storage device while operations are in progress.
- Check the history. Evaluate the recorded operations against the chosen property or model. A system may reject, delay, or fail operations during an outage; whether that is acceptable depends on the guarantee being tested.
A cluster that starts successfully and answers requests under normal conditions demonstrates basic operation, not resilience. The test becomes useful when its workload and checker address a concrete claim.
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Which failures should you try first?
Failures are not limited to a server switching off. Jepsen’s methods include network partitions and latency, process pauses and crashes, clock errors, power loss, and disk errors. Published analyses also illustrate how failure conditions can be evaluated in specific system tests.
1. Crash a process
Stop a node while clients are issuing operations, then observe both the immediate responses and the history after the system recovers. Ask whether confirmed operations remain present and whether the surviving nodes continue to serve requests. Treat data safety and availability as separate questions: a system can preserve data while refusing requests, or keep serving requests while violating a data guarantee.
2. Partition the network
Cut communication between nodes and clients, or divide the nodes into groups that cannot reach each other. A useful question is whether one side continues accepting writes, whether the other side rejects or delays them, and what happens when communication resumes. The expected result depends on the system’s consistency and availability promises; a partition alone does not define a failure.
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3. Skew clocks
Introduce clock errors and check properties that depend on ordering or time. Record which clocks are affected and by how much. A test of clock behavior should not be treated as evidence about other clock ranges or configurations that were not exercised.
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4. Combine faults
After testing individual failure modes, try overlapping conditions—for example, a node crash during a partition, or a process pause while requests continue. Compound failures can expose interactions that a single-fault test misses, but they also make results harder to interpret. Keep the injected conditions and operation history precise enough to identify what happened.
How do you interpret what the system does?
Separate the observations into safety, availability, and recovery rather than treating “it survived” as one verdict.
- Safety: Did the recorded operations preserve the stated invariant? Look for outcomes such as data loss, stale reads, replica divergence, or conflicting operations when those are relevant to the guarantee.
- Availability: Which operations completed, failed, or remained pending during the fault? A safety-preserving system may stop accepting some requests; evaluate that behavior against its stated service goals.
- Recovery: After the fault ends, do nodes converge and can clients continue operating? Recovery behavior is an observation in its own right, not proof that every possible recovery path is safe.
Keep the conclusion tied to the tested build, configuration, workload, fault, and environment. Jepsen’s Capela analysis, for instance, describes tests on three-to-five-node Debian clusters and specifies the versions and failure conditions examined. That report is evidence about its documented scope, not every release or deployment of the system.
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A passing run is evidence that the tested implementation behaved as expected for the operations, faults, schedules, and environment exercised. It does not prove correctness across every possible execution. Jepsen describes its opaque-box tests as nondeterministic: they can find errors but cannot prove correctness. Its ethics page also discusses bounded search and possible harness errors. Jepsen’s testing ethics explains these limitations.
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Testing real binaries reveals implementation behavior that a model alone may not capture. Formal methods can reason about broader classes of behavior, while empirical tests explore selected executions of a real system. These approaches answer different questions and can complement one another; neither a diagram nor a passing test substitutes for a clearly stated guarantee.
How to make the exercise useful
- Write down the property before running the test; avoid deciding after the fact what should count as success.
- Use operations that can expose violations of that property, and retain their complete history.
- Record the system version, topology, configuration, workload, and exact fault conditions.
- Report failures and passes within that scope. Do not generalize a result to untested versions, deployments, or fault combinations.
Jepsen says its aim is to teach people to analyze their own systems and encourage software resilient to common failure modes. Its project materials include analysis work, technical talks, training, and consulting.
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