Runtime adapter

How it works (high level)

• Control logic operates on a stable model of inputs/outputs (points/signals)
• Adapters translate that model into protocol reads/writes and external calls
• Health and errors are exposed as first-class operational signals

Design constraints

• Adapters keep protocols and variability out of timing-critical logic
• Explicit degradation beats implicit partial failure
• Adapter health must be observable like runtime health

Architecture at a glance

• Define a stable artifact boundary (what you deploy) and a stable signal boundary (what you observe)
• Treat changes as versioned, testable, rollbackable units
• Use health + telemetry gates to scale safely

Typical workflow

• Define scope and success criteria (what should change, what must stay stable)
• Create or update a snapshot, then validate against a canary environment/site
• Deploy progressively with health/telemetry gates and explicit rollback criteria
• Confirm acceptance tests and operational dashboards before expanding

System boundary

Treat Runtime adapter as a repeatable interface between engineering intent (design) and runtime reality (deployments + signals). Keep site-specific details configurable so the same design scales across sites.

Example artifact

topic: Runtime adapter
plan: define -> snapshot -> canary -> expand
signals: health + telemetry + events tied to version
rollback: select known-good snapshot

Engineering outcomes

• Adapters keep protocols and variability out of timing-critical logic
• Explicit degradation beats implicit partial failure
• Adapter health must be observable like runtime health

Quick acceptance checks

• Keep protocol/IO calls out of hot control paths (avoid blocking)
• Define explicit error handling and degradation modes per adapter

Common failure modes

• Drift between desired and actual running configuration
• Changes without clear rollback criteria
• Insufficient monitoring for acceptance after rollout

Acceptance tests

• Verify the deployed snapshot/version matches intent (no drift)
• Run a canary validation: behavior, health, and telemetry align with expectations
• Verify rollback works and restores known-good behavior

Design constraints

• Bounded latency and predictable timing (avoid blocking the control loop)
• Clear ownership of writes (prevent competing controllers)
• Graceful degradation when some integrations fail

Common failure modes

• Blocking I/O in the wrong place causing timing jitter
• Ambiguous mapping (wrong units/scaling) leading to “correct looking” but wrong behavior
• Integration failures that cascade instead of isolating cleanly

Implementation checklist

• Keep protocol/IO calls out of hot control paths (avoid blocking)
• Define explicit error handling and degradation modes per adapter
• Validate mapping contracts (types/units) between adapters and logic
• Expose adapter health as first-class operational signals

Rollout guidance

• Start with a canary site that matches real conditions
• Use health + telemetry gates; stop expansion on regressions
• Keep rollback to a known-good snapshot fast and rehearsed

Acceptance tests

• Verify the deployed snapshot/version matches intent (no drift)
• Run a canary validation: behavior, health, and telemetry align with expectations
• Verify rollback works and restores known-good behavior