Does it support BigQuery cost management?

It offers SQL patterns for setting maximum bytes billed and utilizing partitioning and clustering to significantly reduce the cost of large data queries.

How does this skill help with expiring GCP credits?

It provides a strategic burn strategy that prioritizes high-value, lasting uses like ML training and dataset generation over ephemeral compute tasks that provide no long-term value.

Can it help identify unused Google Cloud resources?

Yes, it includes specific gcloud commands to locate unused disks, reserved but unattached IP addresses, and idle virtual machines based on CPU utilization.

Is it compatible with serverless GCP workflows?

Absolutely, it includes optimization configurations for Cloud Run and Cloud Functions to minimize cold starts and maximize request concurrency to lower costs.

GCP Resource Optimizer

Name: GCP Resource Optimizer
Author: organvm-iv-taxis

byorganvm-iv-taxis

•

Cloud Infrastructure

Optimizes Google Cloud Platform resource allocation and manages cloud credits to maximize infrastructure efficiency and cost-effectiveness.

The GCP Resource Optimizer skill provides Claude with specialized knowledge to audit, plan, and optimize Google Cloud Platform deployments. It enables users to strategically manage expiring cloud credits, implement right-sizing for Compute Engine instances, and configure cost-effective storage and serverless architectures. By leveraging predefined CLI commands and best practices, this skill helps developers and DevOps teams identify unused resources, set up budget alerts, and transition to 'serverless-first' patterns that reduce unnecessary cloud spend.

Key Features

01Compute Engine right-sizing and Spot VM implementation workflows

02Strategic credit burn planning to maximize value from expiring GCP credits

032 GitHub stars

04Automated discovery scripts for unused disks, IPs, and idle instances

05Serverless-first architecture patterns for cost-efficient scaling

06Cloud Storage lifecycle rules and BigQuery query cost optimization

Use Cases

01Designing budget-conscious deployment architectures using scale-to-zero serverless patterns

02Reducing monthly cloud spend by auditing existing projects for unused or over-provisioned resources

03Maximizing value from expiring cloud credits by prioritizing long-term assets over ephemeral compute

Key Features

01Compute Engine right-sizing and Spot VM implementation workflows

02Strategic credit burn planning to maximize value from expiring GCP credits

032 GitHub stars

04Automated discovery scripts for unused disks, IPs, and idle instances

05Serverless-first architecture patterns for cost-efficient scaling

06Cloud Storage lifecycle rules and BigQuery query cost optimization

Use Cases

01Designing budget-conscious deployment architectures using scale-to-zero serverless patterns

02Reducing monthly cloud spend by auditing existing projects for unused or over-provisioned resources

03Maximizing value from expiring cloud credits by prioritizing long-term assets over ephemeral compute