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Lifecycle & Governance

The rule engine is often used in regulated domains where auditability and change control matter. This guide outlines how to manage rule versions from draft to production.

Artefact lifecycle

  1. Draft – rules are authored in feature branches or sandbox environments. Validation runs locally.
  2. Review – lints must pass; peer review focuses on correctness, salience, and metadata quality.
  3. Approval – sign-off from domain owners. Record the approval in rule metadata ("approvedBy", "ticket").
  4. Deployment – rule sets are packaged with application releases or delivered to a rule registry.
  5. Monitoring – track pass rates, shared attributes, and action outcomes. Compare against baselines.
  6. Retirement – mark rules as deprecated, remove actions/hooks, and clean up metadata once retired.

Versioning strategy

  • Use semantic versions on rule sets (1.2.0). Bump:
  • MAJOR when salience ordering or semantics change dramatically.
  • MINOR when adding/removing rules or metadata.
  • PATCH for action/hook tweaks that keep behaviour equivalent.
  • Store previous versions for auditing; RuleSet instances are immutable so you can snapshot them easily.

Audit trails

  • Persist rule JSON and metadata for each deployment (e.g. in object storage or git).
  • Log rule evaluations with rule ID, salience, pass outcome, and shared attributes.
  • Use RuleDebugStageTrace in incident investigations; archive traces only when necessary because they may contain PII.

Change management metadata

Embed governance fields inside metadata:

"metadata": {
  "owner": "payments-risk",
  "approvedBy": "alice@example.com",
  "ticket": "RISK-2042",
  "runbookUrl": "https://wiki/rules/high-value"
}

Make the owning service surface this metadata in dashboards or change logs.

Deployment patterns

  • Config service – store rule sets in a central service; services fetch and cache them. Provide a diff endpoint for tooling.
  • Embedded jar – bundle rules with application code. Rebuild and redeploy to roll out changes; keep release notes comprehensive.
  • Hybrid – embed a baseline ruleset and allow overrides from a registry at runtime. Ensure validation runs on both sources.

Rollback plan

  • Keep the previous RuleSet in memory. If monitoring flags regressions, swap back instantly.
  • Version metadata should include supersedes or previousVersion so tooling can automate rollback selection.

Multitenancy

If you host rules for multiple teams or customers:

  • Namescope rule IDs (tenant.ruleId) and salience ranges per tenant.
  • Consider separate RuleEngine instances or partitions to keep shared attributes isolated.
  • Enforce quotas (number of rules, evaluation latency) per tenant at the orchestration layer.

Governance ensures the rule engine remains predictable, audited, and compliant with organisational policies.