GoogleCloudPlatform/professional-services resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3065 stars · 1469 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of example solutions, tools, and reference architectures developed by Google Cloud's Professional Services team, primarily in Python. It is not an officially supported Google product but serves as a reference for building on GCP products like BigQuery, Dataflow, and GKE.

Use cases

• find example architectures for deploying on google cloud
• learn how to analyze reddit data in bigquery in realtime
• generate large synthetic datasets to stress-test bigquery
• automate bigquery schema and dataset management from the cli
• set up cicd on gke with gitlab
• build a pipeline to moderate audio content with ml apis
• detect anomalies in bigquery audit logs

When to choose

• you want copyable reference implementations for common Google Cloud patterns
• you need starting points for BigQuery, Dataflow, or GKE solutions
• you are learning GCP through practical, production-oriented examples

When to avoid

• you need officially supported, production-grade Google products with SLAs
• you are not using Google Cloud Platform
• you need a single cohesive tool rather than a grab-bag of independent examples

Facets

learning-resource · maturity active

developer-tools etl machine-learning data-science infrastructure-as-code ci-cd cloud-computing big-data machine-learning developer-tools python cloud cli google-cloud-platform bigquery dataflow gke example-solutions reference-architectures sample-code data-engineering devops docker kubernetes

Member repositories

For agents

markdown · JSON · MCP: product_card(name="GoogleCloudPlatform/professional-services")