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gcp-dataflow

Skill

Guides writing, packaging, executing, and troubleshooting Apache Beam pipelines on Dataflow. Use when creating new pipelines, configuring Flex Templates, or analyzing performance of Dataflow jobs. Capabilities include Java/Python/Go setup, Cloud Build integration, and deep diagnostic analysis of job

0Writing

Install

git clone https://github.com/gemini-cli-extensions/data-agent-kit-starter-pack.git ~/.claude/skills/gcp-dataflow

What is gcp-dataflow?

Guides writing, packaging, executing, and troubleshooting Apache Beam pipelines on Dataflow. Use when creating new pipelines, configuring Flex Templates, or analyzing performance of Dataflow jobs. Capabilities include Java/Python/Go setup, Cloud Build integration, and deep diagnostic analysis of job health and autoscaling. Use when: - Creating an Apache Beam Dataflow pipeline. - Creating a Google Dataflow Flex Template. - Using an existing Google Dataflow Template. - Debugging Dataflow pipeline - Troubleshooting Dataflow pipeline - Analyzing Performance of Dataflow pipeline. Key capabilities: Java/Python/Go project setup, Flex Templates (with Cloud Build), and diagnostics for streaming job health, bottlenecks, and autoscaling. Do NOT use for: - General GCP resource management unrelated to Dataflow. - Issues with other GCP services (e.g., GCE, GCS, BigQuery) unless directly impacting Dataflow pipeline execution. - Pipeline technologies other than Apache Beam on Dataflow.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~246 tokens of context used while enabled, before you invoke anything

Documentation

README · ~11 min read

Apache Beam Pipelines on Cloud Dataflow

Pipeline authoring

Use this section when implementing Dataflow pipeline logic using Apache Beam.

Check if existing Google Dataflow Template exists

Google provides a variety of pre-built, open source Dataflow templates that can be used for common scenarios. Before implementing a pipeline from scratch, you MUST follow the steps below to check whether a Dataflow template for the pipeline logic you need to implement already exists.

  • Step 1: Check for a matching Google Dataflow Template

    • Identify the source and sink (e.g., GCS to BigQuery) from the

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