菜单
Guides agents through Unity Catalog governance workflows for Databricks lakehouses. Use when defining catalogs, schemas, external locations, access boundaries, shares, lineage, and cross-workspace governance for governed Delta Lake, ML, analytics, and serving assets.
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基于 SOC 职业分类
Forces replay-safe rollout plans, reconciliation gates, and rollback paths before executing any data backfill or historical reprocessing. Use when running /backfill, rerunning pipelines, repairing publish windows, or any work that risks double-counting or downstream corruption.
Helps agents classify data engineering work, choose the right preset and skill bundle, and pick the safest next command. Use when starting a session, triaging an ambiguous request, or deciding how to proceed.
Guides agents through resiliency testing for data platforms. Use when designing or running failure drills, recovery validation, failover tests, replay-safety checks, dependency outage exercises, or fault injection for pipelines and publishes.
Guides agents through production data incidents. Use when a pipeline fails, publishes bad data, misses an SLA, partially loads, corrupts state, or requires rollback, replay, or stakeholder communication.
Enforces production Kafka guardrails including non-breaking schema evolution, dead-letter queues for poison messages, and acks=all producer durability. Use when designing or changing Kafka topics, producers, consumers, schema registry policies, or streaming recovery paths.
Guides agents to wire Model Context Protocol servers for live data platform observability including Spark execution plans, OOM diagnosis, Kafka consumer lag, and orchestration run state. Use when agents need cluster metrics, streaming lag, or job diagnostics instead of blind code changes.
| name | unity-catalog-and-lakehouse-governance |
| description | Guides agents through Unity Catalog governance workflows for Databricks lakehouses. Use when defining catalogs, schemas, external locations, access boundaries, shares, lineage, and cross-workspace governance for governed Delta Lake, ML, analytics, and serving assets. |
Use this skill when Unity Catalog is the core governance surface for a Databricks platform. It helps agents design governed boundaries across catalogs, schemas, storage locations, shares, and access paths for lakehouse data products.
Unity Catalog hierarchy and ownershipDelta tables, views, volumes, or modelsDo not reduce Unity Catalog to permissions only. It is also a publish, ownership, and operating-boundary decision.
Define the governance hierarchy. Decide:
Define storage and credential boundaries. Cover:
Define access and sharing behavior. Include:
Align governance with lakehouse delivery. Require:
Validate day-2 operations. Review how promotions, new workspaces, external consumers, and object-store boundaries behave under the governance model.
| Rationalization | Reality |
|---|---|
| "We already use Databricks, so Unity Catalog design is obvious." | Poor catalog and location design creates long-term friction in ownership, sharing, and environment boundaries. |
| "We can give broad workspace access and tighten later." | Over-broad access becomes hard to unwind once shared data products are adopted. |
| "Lineage comes for free." | Platform lineage is useful only when publish boundaries and ownership are designed intentionally. |