Skip to content

Cross-Product Interop Matrix

Intent

Test across validators/servers/SDKs continuously to catch ecosystem differences early.

Structure

A cross-product interop matrix is a small harness that runs the same set of artifacts/tests across multiple validators, servers, and SDKs. Structurally it defines targets, execution environments, and a split between smoke and full suites.

  • Target list: named validators/servers/SDKs with minimum supported versions
  • Execution harness: scripted runs (often containerized) so results are comparable
  • Suites: small smoke suite for PRs + larger suite for nightly/pre-release
  • Reporting: normalized reports that show pass/fail by target and scenario
  • Triage taxonomy: labels/owners that quickly route failures to profiling, terminology, or platform variance

Cross-Product Interop Matrix Structure Diagram

Key Components

Matrix targets

  • Choose representative validators/servers/SDKs
  • Define minimum supported versions
  • Separate required vs optional targets
  • Keep the matrix small at first
  • Expand as adoption grows

Docker harness

  • Provide repeatable environments for each target
  • Capture versions in Docker image tags
  • Make runs deterministic and scriptable
  • Store logs and reports as artifacts
  • Allow local developer runs

Smoke vs full suites

  • Keep a smoke suite that runs on every PR
  • Run full suites nightly or before release
  • Track coverage gaps explicitly
  • Avoid flakiness by controlling dependencies
  • Use failures to prioritize fixes

Triage labels

  • Label failures by root cause (terminology, profile, server)
  • Track whether failure is known variance or a bug
  • Assign owners for each area
  • Keep a dashboard of recurring issues
  • Use labels to drive release readiness

Behavior

Detect variance early

Run a small subset early and often; run deeper checks on cadence. Treat variance as data, not as noise.

PR smoke run

  • Run the smallest set of scenarios that catch common incompatibilities.
  • Fail PRs only on agreed critical targets; keep others advisory at first.
  • Record failure fingerprints for faster triage.

Nightly/pre-release

  • Run full suite across all targets.
  • Track trendlines (new failures vs known variance).
  • Feed results back into patterns: add guidance where ecosystem behavior differs.

Benefits

  • Avoid vendor-specific success
  • Build confidence

Trade-offs

  • Maintain environments/credentials

References