Specifies least privilege, validation, isolation, budgets, retries, cancellation, audit evidence, and safe failure handling for data warehouse analytics connector, so adopters can provide one portable metric-plan adapter contract for governed cloud or on-pr...
Package status: reference context ready for human review. The contract and test scenarios are complete, but no claim is made that an adopting implementation has passed them.
Decision
For Data warehouse analytics connector, implement the interface with independent access and resilience controls so adopters can provide one portable metric-plan adapter contract for governed cloud or on-premise analytical warehouses. The abstraction normalizes safety and result semantics; it does not pretend that vendors have identical SQL, cost, latency, freshness, or cancellation behavior. This is a reference contract: database products, numeric budgets, jurisdictions, retention, organizational defaults, and accountable owners remain explicit adoption choices.
Scope
- The Data warehouse analytics connector actors, inputs, outputs, states, versions, and externally visible outcomes needed to provide one portable metric-plan adapter contract for governed cloud or on-premise analytical warehouses.
- The role-specific focus of this block: implement the interface with independent access and resilience controls, including primary, cached, asynchronous, export, support, and recovery paths where applicable.
- Adoption-specific configuration, ownership, rollout, evidence retention, and review responsibilities needed to use the contract safely.
Outside this block
- The abstraction normalizes safety and result semantics; it does not pretend that vendors have identical SQL, cost, latency, freshness, or cancellation behavior.
- Choosing a universal database, model, renderer, vendor, numeric threshold, retention period, timezone, jurisdiction, or service-level objective.
- Claiming that packaged scenarios ran against a downstream implementation or that this reference grants security, privacy, accessibility, analytical, or legal approval.
Contract
- The implemented Data warehouse analytics connector boundary enforces this rule: Each adapter publishes capabilities for grains, dimensions, functions, precision, dry run, estimated cost, asynchronous jobs, cancellation, paging, snapshots, and freshness.
- The implemented Data warehouse analytics connector boundary enforces this rule: The gateway compiles only supported metric-plan operations against curated versioned views and never forwards model-authored SQL or arbitrary warehouse identifiers.
- The implemented Data warehouse analytics connector boundary enforces this rule: Warehouse credentials are scoped to minimum read access, isolated per environment or policy boundary, rotated outside prompts, and unavailable to the model.
- The implemented Data warehouse analytics connector boundary enforces this rule: Where supported, dry-run or cost estimation occurs before execution; otherwise a conservative declared budget and pre-aggregated path are required.
- The implemented Data warehouse analytics connector boundary enforces this rule: Asynchronous queries use opaque job handles with caller binding, status, expiry, cancellation, terminal errors, and authorization rechecks on retrieval.
- The implemented Data warehouse analytics connector boundary enforces this rule: The portable result contract states exact or approximate precision, sampling, snapshot, watermark, timezone, missing buckets, truncation, and partial status.
- The implemented Data warehouse analytics connector boundary enforces this rule: Adapter-specific errors map to stable semantic categories while safe diagnostic references preserve enough detail for operators.
- The implemented Data warehouse analytics connector boundary enforces this rule: Conformance fixtures prevent a new adapter from claiming compatibility until metric values, policy behavior, budgets, and failure semantics match the gateway contract.
Implementation guidance
- Layer host authentication, gateway authorization, compiler allowlists, connector controls, and database privileges so no single hint grants safety.
- Keep credentials outside prompts and model-visible state, rotate them through the adopting platform, and scope them to curated resources.
- Apply hard limits before external work and propagate deadline, cancellation, correlation, and terminal status through every hop.
- Redact errors and telemetry while retaining safe references that an operator can correlate with backend evidence.
Failure handling and safeguards
- For Data warehouse analytics connector, An unsupported function, dimension, consistency level, cost estimate, or cancellation promise is rejected rather than emulated with different semantics.
- For Data warehouse analytics connector, An over-budget estimate, expired job, revoked identity, partial partition, or stale snapshot reaches a visible bounded result state.
- For Data warehouse analytics connector, If adapter capability metadata is missing or stale, routing stops before execution and names the operator-owned compatibility gap.
Verification and operations
- For the security evidence of Data warehouse analytics connector, run the same frozen metric plans through every supported adapter and compare values, periods, nulls, precision, quality flags, and error classes.
- For the security evidence of Data warehouse analytics connector, test credential scope, row and column policies, job-handle isolation, cancellation, paging, export, and cache reuse under multiple roles.
- For the security evidence of Data warehouse analytics connector, record predicted and actual scan, cost, latency, result size, and freshness so routing budgets can be calibrated from evidence.
Adoption assumptions
- The adopting product has authenticated identity, a versioned authorization policy, owned metric definitions, bounded telemetry, and a controlled path for change.
- Names and values in the example are fictional adoption fixtures, not universal defaults, production credentials, performance promises, or business targets.
- Referenced specifications constrain protocol, security, accessibility, or vendor behavior; the adopting team must confirm current applicability before promotion.
The executable-looking examples in this package are fixtures and acceptance contracts. Run the collection validator to check structure and metadata, then translate and execute the scenarios in the target repository before recording implementation evidence.
References
- Google Cloud BigQuery documentation, Run a query (applies as of 2026-09-12)
- OWASP Authorization Cheat Sheet