Can it help reduce my Google Cloud bill?

Yes, it includes cost optimization strategies like using Preemptible VMs, BigQuery slot reservations, and automated storage archiving.

Does it support Infrastructure as Code (IaC)?

Yes, it includes specialized Terraform patterns for provisioning GCP infrastructure, specifically focusing on GKE and security configurations.

How does this skill handle GCP security?

It follows security-first principles, prioritizing Workload Identity over service account keys, and implementing VPC Service Controls and Binary Authorization.

Is this skill for the Claude Code CLI?

Yes, this is a specialized skill designed to enhance Claude Code's capabilities when performing GCP-related devops and architecture tasks.

What GCP services does this skill cover?

The skill provides patterns and best practices for core services including GKE, Cloud Run, Compute Engine, Cloud Storage, BigQuery, Cloud SQL, and Cloud Functions.

Google Cloud Platform Patterns

Name: Google Cloud Platform Patterns
Author: jpoutrin

byjpoutrin

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Cloud Infrastructure

Implements and optimizes Google Cloud Platform infrastructure using proven architectural patterns and security best practices.

About

The Google Cloud Platform Patterns skill equips Claude with specialized knowledge for designing, deploying, and managing GCP resources. It provides production-ready patterns for core services like GKE, Cloud Run, and BigQuery, ensuring that all implementations adhere to industry-standard security protocols such as Workload Identity and VPC Service Controls. Whether you are generating Terraform modules for infrastructure as code or optimizing SQL queries for BigQuery, this skill streamlines the cloud development lifecycle with expert-level architectural guidance.

Key Features

Offers BigQuery optimization strategies for performance and cost efficiency
Provides Terraform patterns for GKE and automated resource provisioning
Guides implementation of serverless architectures using Cloud Run and Functions
Implements GCP security best practices including Workload Identity and IAM
Assists with cloud cost management through autoscaling and storage tiering
2 GitHub stars

Use Cases

Designing a cost-effective data warehouse using BigQuery partitioning and clustering
Provisioning a secure GKE cluster with Terraform and Workload Identity
Migrating monolithic applications to serverless containers on Cloud Run

About

Key Features

Offers BigQuery optimization strategies for performance and cost efficiency
Provides Terraform patterns for GKE and automated resource provisioning
Guides implementation of serverless architectures using Cloud Run and Functions
Implements GCP security best practices including Workload Identity and IAM
Assists with cloud cost management through autoscaling and storage tiering
2 GitHub stars

Use Cases

Designing a cost-effective data warehouse using BigQuery partitioning and clustering
Provisioning a secure GKE cluster with Terraform and Workload Identity
Migrating monolithic applications to serverless containers on Cloud Run