How we know a router performance result is real

Apollo’s GraphOS team describes how its Runtime Testing Framework evaluates whether new router releases produce genuine performance changes rather than ordinary benchmark noise, using isolated Kubernetes environments, deterministic mocked subgraphs, separate load-generator nodes, and five repeated runs per configuration. For version 2.18.0, it tested 10 graphs across five router configurations, assessing latency distributions, router p99, client latency, memory use, and HTTP and GraphQL error rates through three sequential gates: validating that each run reached stable target load without resource constraints, confirming that repeated measurements agreed, and determining whether observed changes exceeded predefined meaningful-change zones. Of 500 runs, 404 fully passed initial validity checks, while resource limitations and insufficient warm-up periods exposed improvements needed in the testing environment; repeatability checks also showed that metrics such as p99 required more samples to judge reliably. The analysis found no regressions in any comparable metric, with pooled median and p95 client latency within 2% of version 2.17.0, although many individual comparisons remained inconclusive rather than being treated as evidence of no change. The team subsequently strengthened its methodology with longer warmups, finer latency histograms, stricter thresholds, and plans for historical cross-release comparisons, reduced infrastructure noise, and guidance for customers tuning routers under load.

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