This repository offers a comprehensive collection of common solutions, tools, and examples developed by Google Cloud's Professional Services team. It targets engineers and architects seeking practical, ready-to-use code and guidance for implementing various Google Cloud Platform services, aiming to accelerate adoption and solve complex cloud challenges.

How It Works

The repository is organized into folders for examples and tools, covering a wide array of Google Cloud services including BigQuery, Dataflow, Dataproc, GKE, and AI Platform. Solutions often leverage managed services and serverless architectures for scalability and efficiency, providing reference implementations for common use cases like data migration, CI/CD, machine learning pipelines, and cost optimization.

Quick Start & Requirements

• Solutions are typically implemented using Python, Terraform, or shell scripts.
• Many examples require a Google Cloud Platform account and specific service enablement.
• Specific prerequisites (e.g., certain Python libraries, GCP SDK, Docker) are detailed within individual solution directories.
• Refer to individual solution READMEs for detailed setup and execution instructions.

Highlighted Details

• Extensive coverage of BigQuery utilities for data migration, analysis, and management.
• Numerous Dataflow examples demonstrating ETL, streaming, and custom template creation.
• Tools for automating infrastructure management, security, and cost optimization across GCP.
• Machine learning examples showcasing model training, deployment, and analysis using various GCP AI services.

Maintenance & Community

• This repository is maintained by Google Cloud's Professional Services team.
• Contact: professional-services-oss@google.com.
• Contribution guidelines are available within the repository.

Licensing & Compatibility

• All solutions are provided under the Apache 2.0 license.
• This license permits commercial use and integration with closed-source projects.

Limitations & Caveats

• The repository explicitly states that it is not an officially supported Google product.
• Solutions are provided as-is, and users are responsible for testing and adapting them to their specific environments.