Google Cloud
A curated list of awesome applications, tools, and resources for Google Cloud Platform.
What is Google Cloud?
Awesome Google Cloud is a curated list of awesome applications, tools, and resources for Google Cloud Platform (GCP). It serves as a directory for developers to discover libraries, sample projects, tutorials, and community contributions across GCP's modular cloud services like computing, data analytics, AI, and storage. The project solves the problem of fragmented information by providing a centralized, organized repository of high-quality GCP-related content.
Developers, engineers, and cloud practitioners who are building, deploying, or learning on Google Cloud Platform and want to discover tools, examples, and best practices.
Developers choose this list because it is a trusted, community-vetted collection that saves time searching for GCP resources, offers structured categorization by service, and includes both official and community-contributed content for practical learning and implementation.
Overview
A curated list of awesome stuff for Google Cloud.
Use Cases
Best For
- Finding sample applications and demos for Google Cloud services like Cloud Run or Kubernetes Engine
- Discovering open-source tools and libraries that integrate with GCP (e.g., dataflow templates, BigQuery utilities)
- Learning Google Cloud through curated tutorials, codelabs, and interactive labs
- Exploring community-contributed projects and use cases for AI, big data, and serverless on GCP
- Staying updated on ecosystem tools for security, monitoring, and deployment in Google Cloud
- Referencing when starting a new GCP project to identify relevant frameworks and best practices
Not Ideal For
- Projects requiring official, up-to-the-minute GCP documentation and direct support channels
- Teams seeking interactive, guided learning platforms with built-in labs and certification tracking
- Developers working in multi-cloud environments who need resources across AWS, Azure, and GCP
- Users who prefer a searchable, dynamic database over a static, categorized list for resource discovery
Pros & Cons
Pros
Resources are neatly divided by GCP product areas like Compute, AI, and Big Data, as shown in the TOC, making it easy to navigate specific needs without sifting through unrelated content.
The list is actively maintained with an open contribution process, ensuring a mix of official and community-vetted resources, highlighted in the Contributing section for ongoing relevance.
It links to interactive labs, codelabs, and courses such as Qwiklabs and Coursera, providing practical learning paths beyond mere tool listings in the 'Interactive Learning Resources' section.
Covers a wide range from AI and Big Data to security tools, evidenced by sections on Cloud Vision API for AI and Forseti for security, helping users explore diverse GCP services.
Cons
As a GitHub-based list, it relies on community pull requests for updates, so resources can become outdated without frequent maintenance, unlike automated feeds or official docs.
Users must browse through categories or use external tools to find specific resources, as the README only offers a TOC without search functionality, hindering quick discovery.
The list only includes Google Cloud resources, making it less useful for teams adopting multi-cloud strategies or comparing tools with competitors like AWS or Azure.
Frequently Asked Questions
Related Projects
Apps This project is dedicated to collecting high-quality macOS software and organizing them systematically by different categories for easy search and use.
Node.js:zap: Delightful Node.js packages and resources [BECAUSE OF TOO MUCH SPAM AND LOW-QUALITY SUBMISSIONS, SUBMISSIONS ARE PAUSED UNTIL JULY]
FlutterAn awesome list that curates the best Flutter libraries, tools, tutorials, articles and more.
iOSA curated list of awesome iOS ecosystem, including Objective-C and Swift Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.