gcp-composer-troubleshooting

Diagnose failed Cloud Composer DAGs and generate root cause analysis reports.

Updated Jan 8, 2026
One-click install
npx skills add https://github.com/arslan9024/White-Caves --skill gcp-composer-troubleshooting-arslan9024
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gcp-composer-troubleshooting
Source: https://github.com/arslan9024/White-Caves/tree/main/.agents/skills/gcp_composer_troubleshooting
Command: npx skills add https://github.com/arslan9024/White-Caves --skill gcp-composer-troubleshooting-arslan9024

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Debugging failed Airflow DAGs in Google Cloud Composer requires manually digging through scattered logs and verifying which code version actually ran remotely. This Skill automates evidence gathering and produces a structured Root Cause Analysis (RCA) report. ## Core Features & Use Cases - Log-Based Evidence Gathering: Uses gcloud logging read with severity, DAG ID, and environment filters to locate failures and stack traces. - Remote Code Verification: Downloads the actual DAG code from the environment's GCS bucket to confirm the running version before analysis. - RCA Report Generation: Correlates log errors with exact code lines and produces a saved RCA report with a proposed fix. - Use Case: A data engineer sees that the daily_sales_agg DAG failed yesterday. The Skill fetches the error logs, downloads the remote DAG file, identifies a KeyError: 'region' at line 45, and writes an RCA report recommending record.get('region', 'unknown'). ## Quick Start Ask the assistant to troubleshoot why your Cloud Composer DAG failed and generate an RCA report for it.

Frequently Asked Questions about gcp-composer-troubleshooting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I troubleshoot a failed Cloud Composer DAG?▼

Use gcloud logging read with filters like resource.type="cloud_composer_environment", the DAG ID label, and severity>=ERROR to find failure logs. Then download the actual DAG code from the environment's GCS bucket to correlate the error with the exact failing line.

How to generate a root cause analysis report for Airflow failures?▼

Gather the DAG ID, run ID, and task ID, retrieve error logs via gcloud logging, and download the remote DAG code with gcloud storage cp. Correlate the stack trace with specific code lines, then document the root cause and proposed fix in an RCA report file.

Why does my local DAG code differ from the Composer environment?▼

The remote environment runs the code uploaded to its GCS bucket, which may not match your local files. Always download the remote DAG with gcloud storage cp before analysis, since the remote version is the source of truth for the failure.

Can this skill fix my broken Airflow DAG automatically?▼

No, the skill is read-only by design. It analyzes logs and code to prove the root cause and proposes a fix, but it does not modify code unless you explicitly ask it to apply the fix.

What gcloud commands are used to debug Composer pipelines?▼

Key commands include gcloud composer environments list, dags list-runs for run history, gcloud logging read for error logs, and gcloud storage cp to download DAG files from the environment bucket for inspection.