Google Cloud Platform's repositories
python-docs-samples
Code samples used on cloud.google.com
generative-ai
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
golang-samples
Sample apps and code written for Google Cloud in the Go programming language.
nodejs-docs-samples
Node.js samples for Google Cloud Platform products.
vertex-ai-samples
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
cloud-foundation-toolkit
The Cloud Foundation toolkit provides GCP best practices as code.
k8s-config-connector
GCP Config Connector, a Kubernetes add-on for managing GCP resources
magic-modules
Add Google Cloud Platform support to Terraform
genai-for-marketing
Showcasing Google Cloud's generative AI for marketing scenarios via application frontend, backend, and detailed, step-by-step guidance for setting up and utilizing generative AI tools, including examples of their use in crafting marketing materials like blog posts and social media content, nl2sql analysis, and campaign personalization.
functions-framework-php
FaaS (Function as a service) framework for writing portable PHP functions
hpc-toolkit
Cloud HPC Toolkit is an open-source software offered by Google Cloud which makes it easy for customers to deploy HPC environments on Google Cloud.
cloud-sql-go-connector
A Go library for connecting securely to your Cloud SQL instances
terraform-google-conversion
This is a Golang library which provides functions to map a Terraform configuration for Google Cloud Platform into GCP's native API inventory format.
alloydb-go-connector
A Go library for connecting securely to your AlloyDB instances
functions-framework-cpp
Functions Framework for C++
mqtt-cloud-pubsub-connector
Lightweight connector to bridge MQTT brokers and Google Cloud Pub/Sub
terraform-genai-knowledge-base
Fine tune an LLM model to answer questions from your documents.
dataflux-pytorch
The Dataflux Accelerated Dataloader for PyTorch with GCS is an effort to improve ML-training efficiency when using data stored in GCS for training datasets. Using the Dataflux Accelerated Dataloader for training is up to 3X faster when the dataset consists of many small files (e.g., 100 - 500 KB).
ml-auto-solutions
A simplified and automated orchestration workflow to perform ML end-to-end (E2E) model tests and benchmarking on Cloud VMs across different frameworks.
terraform-google-enterprise-application
Deploy an enterprise developer platform on Google Cloud
terraform-ml-image-annotation-gcf
Deploys an app for ml image annotation using gcf
mis-ai-accelerator
Google Cloud Medical Imaging ML Development Accelerators
terraform-cloud-client-api
Deploys an example application that uses Cloud Client APIs