Fabric Data Agent Performance remediate

Systematic toolkit for diagnosing and resolving performance issues in Microsoft Fabric Data Agents, Operations Agents, and their underlying Spark compute and data source infrastructure.

When to Use This Skill

• Data Agent responses are slow or timing out
• Agent-generated SQL/KQL/DAX queries return errors or produce incorrect results
• Spark session startup takes longer than expected (>10 seconds)
• Capacity throttling errors (HTTP 430) during agent workloads
• Operations Agent playbooks fail to execute or trigger actions
• Data source connections are unreliable or stale
• Example queries fail validation against schema
• Resource profiles need tuning for agent-specific workloads
• Table maintenance (VOrder, bin-compaction, vacuum) is overdue
• Autoscale Billing configuration needs optimization

Prerequisites

• Access: Fabric workspace Contributor or Admin role
• Tools: PowerShell 7+, Fabric REST API access (Microsoft Entra token)
• Endpoints: https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items
• Monitoring: Access to Fabric Admin Portal and Azure Cost Analysis
• Optional: Azure subscription admin for SKU resizing and Autoscale Billing

Diagnostic Decision Tree

Agent performance issue reported
├── Slow response times?
│   ├── First query after idle? → Spark session startup (see Workflow 1)
│   ├── All queries slow? → Resource profile mismatch (see Workflow 2)
│   └── Intermittent slowness? → Capacity throttling (see Workflow 3)
├── Incorrect query results?
│   ├── Wrong tables/columns? → Data source instructions (see Workflow 4)
│   ├── SQL syntax errors? → Example query validation (see Workflow 5)
│   └── Stale data? → Lakehouse table maintenance (see Workflow 6)
├── Agent not responding?
│   ├── HTTP 430 errors? → Concurrency limits (see Workflow 3)
│   ├── Connection failures? → Data source config (see Workflow 4)
│   └── Operations Agent stuck? → Playbook/action config (see Workflow 7)
└── Cost concerns?
    ├── Unexpected charges? → Autoscale Billing audit (see Workflow 8)
    └── Over-provisioned? → SKU right-sizing (see Workflow 8)

Step-by-Step Workflows

Workflow 1: Spark Session Startup Delays

Symptoms: First query takes 2-5 minutes, subsequent queries are fast.

Resolution steps: See workflow-spark-startup.md

Workflow 2: Resource Profile Optimization

Symptoms: Consistently slow reads or writes across all agent queries.

Resolution steps: See workflow-resource-profiles.md

Workflow 3: Capacity Throttling (HTTP 430)

Symptoms: TooManyRequestsForCapacity errors, jobs queued or rejected.

Formula: 1 Capacity Unit = 2 Spark VCores

Resolution steps: See workflow-capacity-throttling.md

Workflow 4: Data Source Configuration Issues

Symptoms: Agent queries wrong tables, returns irrelevant results, or fails to connect.

Data Agents use three configuration layers that all affect query quality:

1. Agent Instructions — Global routing rules (which data source for which topic)
2. Data Source Instructions — Schema context, table descriptions, column details
3. Example Queries — Few-shot SQL/KQL/DAX examples for query generation

Resolution steps: See workflow-data-source-config.md

Workflow 5: Example Query Validation

Symptoms: Agent ignores example queries, generates incorrect SQL/KQL syntax.

Key rule: The Fabric Data Agent only uses queries that contain valid SQL/KQL syntax AND match the schema of the selected tables. Queries that fail validation are silently ignored.

Resolution steps: See workflow-example-queries.md

Workflow 6: Lakehouse Table Maintenance

Symptoms: Queries over Delta tables are slow, small file problem, stale statistics.

Three maintenance operations available via REST API:

Resolution steps: See workflow-table-maintenance.md

Workflow 7: Operations Agent Debugging

Symptoms: Operations Agent not triggering actions, playbook failures.

Operations Agent definition requires: goals, instructions, at least one KustoDatabase data source, at least one PowerAutomateAction, and shouldRun: true.

Resolution steps: See workflow-operations-agent.md

Workflow 8: Autoscale Billing and SKU Right-Sizing

Symptoms: Unexpected costs, capacity contention between Spark and other workloads.

Resolution steps: See workflow-autoscale-billing.md

Available Scripts

remediate Quick Reference

References

• Spark Startup Workflow
• Resource Profile Workflow
• Capacity Throttling Workflow
• Data Source Config Workflow
• Example Query Workflow
• Table Maintenance Workflow
• Operations Agent Workflow
• Autoscale Billing Workflow