fabric-operations

Manage Microsoft Fabric operational excellence across capacity planning, governance, security, cost optimization, and observability. Use when the request involves workspace administration, capacity monitoring, access control, compliance policies, cross-workload operational concerns, or workspace documentation and inventory. Delegates endpoint-specific implementation to specialized skills where available.

Orchestrate end-to-end Microsoft Fabric data engineering workflows that span multiple workloads and personas. Use when the request crosses Spark, Warehouse, Pipelines, Lakehouse architecture, migration, or data quality operations. Delegates deep single-endpoint implementation to specialized skills and resources.

Build full-stack applications on top of Microsoft Fabric using Python, ODBC, XMLA, and REST APIs. Use when the request involves building applications connected to Fabric data. Delegates endpoint-specific implementation to specialized skills.

Check for skills-for-fabric marketplace updates at session start. Compares local version against GitHub releases and shows changelog if updates are available. Use when the user wants to: (1) check for skill updates, (2) see what's new in skills-for-fabric, (3) verify current version. Triggers: "check for updates", "am I up to date", "what version", "update skills", "show changelog".

Manage refresh schedules and job execution for an EXISTING Microsoft Fabric Materialized Lake View (MLV) via REST APIs: create, update, and delete refresh schedules (interval-based: hourly, daily, weekly), trigger on-demand refreshes, monitor job status, and cancel running jobs. Uses human-in-the-loop confirmations for safety. This skill does NOT author or create the MLV definition: writing the CREATE MATERIALIZED LAKE VIEW / CREATE OR REPLACE SQL is `spark-authoring-cli`, not this skill. Note: MLV discovery (list MLVs, lineage, data quality) requires UI as REST APIs are not yet available. Triggers: "schedule MLV refresh", "manage MLV refresh", "MLV refresh schedule", "schedule materialized lake view refresh", "automate MLV refresh", "trigger MLV refresh", "monitor MLV refresh", "MLV job status", "cancel MLV refresh", "refresh schedule", "MLV automation", "refresh my materialized views"

Diagnose failed Spark jobs, unhealthy Livy sessions, and performance bottlenecks in Microsoft Fabric via read-only CLI triage. Use ONLY for FAILED/unhealthy runs; running a notebook and reporting its success status is `spark-authoring-cli`. Use when the user wants to: (1) diagnose why a Spark job, notebook run, or Lakehouse job failed, (2) triage stuck or dead Livy sessions, (3) identify OOM, shuffle spill, or data skew, (4) retrieve driver/executor logs or Spark Advisor findings, (5) copy event logs and start a local Spark History Server, (6) diagnose Spark activities in a failed pipeline run. Triggers: "diagnose my failed notebook", "why did my spark job fail", "triage spark failure", "diagnose pipeline run failure", "why did my pipeline fail", "livy session stuck in starting", "spark executor OOM", "check spark advisor findings", "shuffle spill diagnosis", "why did my lakehouse job fail", "diagnose lakehouse table load", "data skew diagnosis", "open spark history server locally", "spark job triage".

Diagnose SQL database in Fabric performance via sqlcmd against Query Store, DMVs, sys.dm_db_resource_stats, and Extended Events on the OLTP endpoint. Identifies the top resource-consuming, slowest, or most expensive queries and handles query-performance ranking, blocking-chain, missing-index, and plan-regression diagnostics. For routine data queries use the sqldb-consumption-cli skill; for schema changes use the sqldb-authoring-cli skill. Triggers: "query store slow query analysis sqldb top queries", "top resource-consuming queries from query store sqldb", "slowest queries sql database in Fabric query store", "most expensive queries sqldb query store", "sql database in Fabric blocked sessions head blocker chain sqlcmd", "sqldb missing index recommendation", "sqldb regressed plan instability sqlcmd", "sqldb extended events trace".

Analyze Fabric Data Warehouse performance via CLI using sqlcmd and queryinsights views. Diagnose slow queries, SQL pool pressure, cache coldness, and recommend clustering keys. Triggers: "DW slow query analysis", "slowest queries warehouse", "queryinsights long running", "warehouse CPU resource consumers", "SQL pool pressure window", "pressure events warehouse", "DW cache warmth cold start", "cache warmth analysis", "warehouse cluster key recommendation", "cluster tables performance", "DW performance baseline comparison", "performance degraded warehouse", "warehouse user query patterns", "queryinsights diagnostics", "DW optimization sqlcmd".