Databricks Webhook Listener

Databricks Webhook Listener

Quick Reference

Why This Skill Exists

We need this skill because Databricks workflows degrade when unverified events can trigger unsafe downstream actions. This specific skill turns Databricks Webhook Listener into a deterministic, auth-checked workflow for captures, verifies, and routes databricks webhook events..

Trigger Checklist

• The task explicitly requires Databricks Webhook Listener rather than generic brainstorming.
• The provider tenant, workspace, or environment is known before execution begins.
• Credential reuse has been checked before asking for new secrets.
• Success criteria, side effects, and handoff owner are clear.
• If the run mutates provider state, the relevant approval gates are available.

Auth & Access Profile

Inputs (contract)

Outputs (contract)

Step-by-Step Implementation Guide

1. Define the accepted event types, replay window, and downstream side effects for Databricks Webhook Listener, then register the signing-secret policy for Databricks.
2. Validate credential reuse for the listener and verify that signature, timestamp, and dedupe stores are all healthy before accepting events.
3. Implement captures, verifies, and routes databricks webhook events. so that every payload is verified, normalized, and either routed or quarantined deterministically.
4. Preserve accepted event IDs, quarantine references, and downstream trigger artifacts for every dispatch decision.
5. Run simulation and regression suites that cover invalid signatures, replay attacks, duplicate deliveries, and routing-policy violations.
6. Publish an event-intake log with accepted IDs, quarantined deliveries, and any replay guidance needed for downstream operators.

Operational Runbook

Preflight

• Validate the signing secret, replay window, and dedupe cache before accepting live events.
• Confirm the routing rules and downstream side effects that each event type may trigger.

Execution

• Verify signatures and timestamps before deserializing the payload.
• Route verified events through a dedupe check and quarantine anything that violates policy.

Recovery

• Pause live acceptance when signature verification or replay detection regresses.
• Replay only from the quarantine queue after the root cause is corrected.

Handoff

• Return accepted event IDs, quarantined deliveries, and downstream trigger references.
• Document the active replay window and any signature policy overrides used during recovery.

Validation Gates & Test Matrix

• Required validation suites: unit, integration, simulation, regression-baseline

Failure Modes & Recovery Playbook

Tool Call Implementation

• Reuse existing credentials first. Check environment variables, secure stores, and active sessions before prompting.
• Start with the smallest authenticated read or validation call that proves identity and scope.
• Preserve request, response, and approval traces in databricks-event-intake-log so downstream owners do not need to rediscover context.
• If any auth, contract, or approval gate fails, halt execution and attach remediation guidance instead of guessing.

Credential Reuse Policy

• Reuse valid provider credentials by default and prefer tenant-scoped sessions over newly created secrets.
• Prompt for credentials only when they are missing, invalid, expired, or point at the wrong environment.
• For webhook flows, validate the signing secret against a known sample before accepting live traffic.

Guardrails

• safety: Reject unsigned or replayed events before any downstream side effects are triggered. (signature-check+replay-window)
• reliability: Persist a quarantine queue for every event that cannot be safely dispatched. (quarantine-queue)
• compliance: Route policy-violating payloads to manual review instead of auto-retrying. (handler-policy-review)

Acceptance Checklist

• Credential preflight and scope validation completed successfully.
• Required validation suites ran and all fail-closed gates passed.
• databricks-event-intake-log, scorecard, and handoff packet were produced.
• Any mutations, approvals, or rollbacks are reflected in the artifact bundle.

Anti-Patterns

• Do not ask for new credentials before checking reusable auth context.
• Do not skip the read-only or dry-run validation step for mutating work.
• Do not proceed when approval gates, signing secrets, or rollback checkpoints are missing.
• Do not hand off partial or ambiguous provider state as complete.

Handoff Contract

• Produces: databricks-event-intake-log, execution scorecard, approval trace, and next actions.
• Consumes: signed event payload, secret reference, routing rules.
• Readiness rule: release only after auth, contract, approval, and reliability gates all pass.
• Downstream hint: route to databricks:webhook-listener consumers with approval and credential context attached.

Observability & Continuous Improvement

• SLO: >=99.9% successful runs per 7-day window
• Error budget: <=0.1% critical failures per 7-day window
• Alert triggers:
• credential validation failures exceed baseline
• schema or contract regressions persist for two consecutive runs
• critical posture or rollback events exceed tolerance
• Primary outcome metric: signature verification pass rate
• Secondary metrics: event processing latency, duplicate suppression accuracy
• Review cadence: daily