gcp-composer-troubleshooting

Diagnoses Cloud Composer and Airflow DAG failures using gcloud logs and remote code for root cause analysis.

1|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/tottenjordan/me-skittles --skill gcp-composer-troubleshooting-tottenjordan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gcp-composer-troubleshooting
Source: https://github.com/tottenjordan/me-skittles/tree/main/gemini/gcp-composer-troubleshooting
Command: npx skills add https://github.com/tottenjordan/me-skittles --skill gcp-composer-troubleshooting-tottenjordan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? When a Cloud Composer (Apache Airflow) DAG fails, finding the root cause requires digging through scattered logs and verifying which code version actually ran remotely. This Skill guides an agent through a disciplined, evidence-based Root Cause Analysis (RCA) workflow instead of guesswork. ## Core Features & Use Cases - Structured RCA Process: Follows a strict five-step flow from context gathering and log analysis to code retrieval, root cause identification, and fix proposal. - Remote Code Verification: Downloads the actual DAG code running in the Composer environment via gcloud storage, since local files may not match the deployed version. - Log-Based Evidence Gathering: Uses gcloud logging filters on severity, environment, and DAG ID to locate tracebacks, import errors, and task failures. - Use Case: A user reports that the DAG daily_sales_agg failed yesterday at 2pm. The agent fetches error logs, downloads the remote DAG file, pinpoints a KeyError on line 45, and produces an RCA report with a proposed fix. ## Quick Start Ask the agent to troubleshoot why your Composer DAG failed and generate a root cause analysis 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?▼

Start by gathering the DAG ID, run ID, and task ID, then use gcloud logging read with severity ERROR filters on the cloud_composer_environment resource. Download the actual remote DAG code from the environment's GCS bucket and correlate log tracebacks with specific code lines to identify the root cause.

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

Follow a structured RCA process: collect context, retrieve error logs with gcloud logging, download the running DAG code via gcloud storage, pinpoint the failing line, then document the root cause with cited log entries and code snippets. Save the findings as an RCA report file.

Why does my local DAG code not match the Composer environment?▼

The remote environment runs whatever code was last synced to its GCS bucket, which may differ from your local files. Always download the remote DAG with gcloud storage cp before analysis, since the deployed code is the source of truth for the failure.

What gcloud commands fetch Cloud Composer error logs?▼

Use gcloud logging read with a filter like resource.type=cloud_composer_environment combined with the environment name, dag_id label, and severity>=ERROR. Add --limit and a table format with timestamp, severity, task_id, and textPayload for readable output.

Can this skill automatically fix my broken DAG code?▼

No, it operates read-only by default and only analyzes logs and code to produce an RCA report with a proposed fix. It modifies code only when you explicitly ask it to apply the fix after the analysis is complete.