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gcp-composer-troubleshooting

Diagnose Apache Airflow task failures on Google Cloud Composer using Cloud Logging and Cloud Storage.

2|1|Updated May 25, 2026
Search Tags:#troubleshooting#gcp#composer#airflow#dag#rca
One-click install
npx skills add https://github.com/interflownex/All-in-One --skill gcp-composer-troubleshooting-interflownex
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gcp-composer-troubleshooting
Source: https://github.com/interflownex/All-in-One/tree/main/.gemini/skills/gcp-composer-troubleshooting
Command: npx skills add https://github.com/interflownex/All-in-One --skill gcp-composer-troubleshooting-interflownex

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill resolves complex failures in Cloud Composer and Apache Airflow environments by automating the retrieval of logs, code, and execution context to pinpoint root causes.

Core Features & Use Cases

  • Automated RCA: Correlates log errors with remote DAG code to identify specific failure points.
  • Environment Syncing: Validates code consistency between local workspaces and remote GCS buckets.
  • Use Case: When a production DAG fails, use this skill to fetch the exact remote code, analyze the stack trace from Cloud Logging, and generate a comprehensive Root Cause Analysis report.

Quick Start

Use the gcp-composer-troubleshooting skill to analyze the failure of DAG daily_sales_agg in the production environment.

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 DAG task in Google Cloud Composer?▼

Troubleshooting a failed DAG task in Cloud Composer involves correlating Cloud Logging stack traces with remote DAG code fetched from GCS buckets to identify specific failure points.

How does root cause analysis for Apache Airflow pipelines work?▼

Root cause analysis for Apache Airflow pipelines works by correlating aggregated log errors with the remote DAG code execution context to automatically diagnose task failures and configuration errors.

Do I need gcloud CLI to diagnose Cloud Composer configuration errors?▼

Yes, you need gcloud CLI integration to diagnose Cloud Composer configuration errors, as it interfaces directly with Cloud Logging and Cloud Storage for evidence-based troubleshooting.

What is the best way to validate code consistency between local workspaces and remote GCS buckets?▼

The best way to validate code consistency between local workspaces and remote GCS buckets is to perform environment syncing checks that compare the local DAG code against the deployed Cloud Composer environment.

Why does my Apache Airflow environment fail despite local DAG tests passing?▼

Your Apache Airflow environment might fail due to configuration inconsistencies between your local workspace and the remote GCS buckets, which requires an environment consistency check to diagnose.

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