Gcp Managed Airflow Migrations

by gemini-cli-extensions2df10e25bbf7Apache-2.0215 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

Provides guidance for migrating Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers migration to Airflow 2.11.1 (MSAA Gen 2 and 3) and Airflow 3 (MSAA Gen 3), including environment inspection, GCS download/upload and scanning patterns for breaking changes.

Instructions only

Add to a SourceWeft workspace

  1. Open the skill in your dashboard and add it to a workspace.
  2. Enable it for the chats that should use it.

This skill is instructions only: it ships no scripts to execute.

Add to SourceWeft

You will be asked to sign in first, then taken straight to this skill.

Ask your agent to install it

Paste this prompt into Claude Code, Codex, Cursor or another agent that can run commands — or into SourceWeft chat. The agent reads this skill's install guide, shows you its source, license and scripts, and installs it with the SourceWeft CLI once you agree.

Read https://sourceweft.com/skills/gh-gemini-cli-extensions-data-agent-kit-starter-pack-gcp-managed-airflow-migrations/install.md and install the skill it describes. Before installing, show me its source, license and whether it ships scripts, and wait for my OK. Ask me before changing anything else on my machine.

Read the install guide the agent follows

Install it yourself from a terminal

For Claude Code, Codex, Cursor and other local agents. The SourceWeft CLI fetches the skill from its source repository at the commit scanned here, and verifies every file against the hashes recorded when the skill was scanned. If anything differs, nothing is written.

npx @sourceweft/cli skills install gh-gemini-cli-extensions-data-agent-kit-starter-pack-gcp-managed-airflow-migrations

Add --agent claude-code, codex, cursor or universal to choose which agent gets it (Claude Code by default).

Upstream installer — not verified by SourceWeft

The open-source skills installer fetches the same pinned commit, but does not check the files against the hashes SourceWeft recorded.

npx skills add https://github.com/gemini-cli-extensions/data-agent-kit-starter-pack/tree/2df10e25bbf7dba2570dce1b2e2e77870143969e/skills/gcp-managed-airflow-migrations

Source and attribution

Source:gemini-cli-extensions/data-agent-kit-starter-packinskills/gcp-managed-airflow-migrationsat commit2df10e2

License: Apache-2.0

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal

More from gemini-cli-extensions/data-agent-kit-starter-pack

Schema Mapping

gemini-cli-extensions

Plans source-to-target schema mappings for ETL, ELT, or data integration work, producing a documented Mapping Manifesto.

Data & Analytics215updated today

Resolving Mcp Region Configs

gemini-cli-extensions

Fixes unreplaced region placeholders in regional Google Cloud MCP server configs so missing MCP tools register.

DevOps & Cloud215updated today

Notebook Guidance

gemini-cli-extensions

This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.

Awaiting classification215updated today

Ml Best Practices

gemini-cli-extensions

Guides machine learning notebooks with step-by-step plans for clustering, forecasting, classification, regression and model comparison.

Data & Analytics215updated today

Managing Python Dependencies

gemini-cli-extensions

Guides agents to detect a Python project's dependency manager and install packages correctly instead of using global pip.

Software Development215updated today

Google Cloud Storage Fuse

gemini-cli-extensions

Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when you need to interact with gcsfuse — decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size the file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or GCS bill spikes on existing mounts with gcsfuse metrics. Covers mount semantics, the gcsfuse CLI and config file, the GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or for fully POSIX-compliant shared file systems (Filestore, Managed Lustre).

Awaiting classification215updated today