Execute Databricks incident response procedures with triage, mitigation, and postmortem.
Use when responding to Databricks-related outages, investigating job failures,
or running post-incident reviews for pipeline failures.
Trigger with phrases like "databricks incident", "databricks outage",
"databricks down", "databricks on-call", "databricks emergency", "job failed".
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
Execute Databricks incident response procedures with triage, mitigation, and postmortem.
Use when responding to Databricks-related outages, investigating job failures,
or running post-incident reviews for pipeline failures.
Trigger with phrases like "databricks incident", "databricks outage",
"databricks down", "databricks on-call", "databricks emergency", "job failed".
allowed-tools
Read, Grep, Bash(databricks:*), Bash(curl:*)
version
1.0.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
compatible-with
claude-code, codex, openclaw
tags
["saas","databricks","incident-response"]
Databricks Incident Runbook
Overview
Rapid incident response for Databricks: triage script, decision tree, immediate actions by error type, communication templates, evidence collection, and postmortem template. Designed for on-call engineers to follow during live incidents.
RUN_ID="your-run-id"# Get run details and error
databricks runs get --run-id $RUN_ID | jq '{
state: .state,
tasks: [.tasks[]? | {key: .task_key, result: .state.result_state, error: .state.state_message}]
}'# Get task output for failed tasks
databricks runs get-output --run-id $RUN_ID | jq '{
error: .error,
trace: (.error_trace // "" | .[0:1000])
}'# Repair failed tasks only (skip successful ones)
databricks runs repair --run-id $RUN_ID --rerun-tasks FAILED
Step 3c: Data Quality Issue
-- Quick data sanity checkSELECTCOUNT(*) AS total_rows,
COUNT(DISTINCT id) AS unique_ids,
SUM(CASEWHEN amount ISNULLTHEN1ELSE0END) AS null_amounts,
MIN(created_at) AS oldest,
MAX(created_at) AS newest
FROM prod_catalog.silver.orders
WHERE created_at >current_timestamp() -INTERVAL1DAY;
-- Check recent table changesDESCRIBE HISTORY prod_catalog.silver.orders LIMIT 10;
-- Restore to previous version if corrupted
RESTORE TABLE prod_catalog.silver.orders TO VERSION ASOF5;
Step 3d: Permission Error
# Check current user
databricks current-user me
# Check job permissions
databricks permissions get jobs --job-id $JOB_ID# Fix permissions
databricks permissions update jobs --job-id $JOB_ID --json '{
"access_control_list": [{
"user_name": "service-principal@company.com",
"permission_level": "CAN_MANAGE_RUN"
}]
}'
**Data Pipeline Delay**
We are experiencing delays in data processing.
Dashboard data may be up to [X] hours stale.
Started: [Time] UTC
Status: Actively investigating
Next update: [Time] UTC