Gcp Dataflow

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

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.

Only the file list is public. File contents are available once the skill is installed in a workspace.

PathSizeType
references/bottlenecks_and_parallelism_context.md5 KBtext/markdown
references/dataflow_diagnostics_reference.md3.4 KBtext/markdown
references/dataflow_metrics_bigquery.md447 Btext/markdown
references/dataflow_metrics_core_job.md6.8 KBtext/markdown
references/dataflow_metrics_pubsub.md3.3 KBtext/markdown
references/dataflow_metrics_streaming_engine.md5 KBtext/markdown
references/python_flex_template_reference.md1.9 KBtext/markdown
references/streaming_horizontal_autoscaling_analysis.md4.6 KBtext/markdown
references/streaming_job_health.md2.7 KBtext/markdown
SKILL.md20.9 KBtext/markdown

Source and attribution

Source:gemini-cli-extensions/data-agent-kit-starter-packinskills/gcp-dataflowat commit2df10e2

License: Apache-2.0

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