Which cloud providers does this skill support?

The skill provides comprehensive strategies and implementation patterns for the three major providers: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

Does it provide advice on reserved capacity?

Absolutely. It includes detailed comparisons and savings data for AWS Reserved Instances and Savings Plans, Azure Reserved VM Instances, and GCP Committed Use Discounts.

Can this skill help automate cloud cost savings?

Yes, it includes ready-to-use Terraform code snippets for setting up budget alerts, auto-scaling policies, and S3 lifecycle transitions to automate cost reduction.

How does it handle resource tagging for cost allocation?

It provides a standardized tagging framework that ensures every resource is associated with a specific project, environment, and cost center, facilitating detailed financial reporting.

Cloud Cost Optimization

Name: Cloud Cost Optimization
Author: drgaciw

bydrgaciw

Infraestructura en la Nube

Optimizes cloud infrastructure spending across AWS, Azure, and GCP through resource rightsizing, tagging strategies, and reserved capacity planning.

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This skill provides a comprehensive framework for identifying and reducing cloud waste across major cloud providers. It equips Claude with domain-specific patterns for AWS Savings Plans, Azure Reserved Instances, and GCP Committed Use Discounts, while also offering actionable Infrastructure as Code (Terraform) examples for automated cost governance. By implementing visibility, right-sizing, and architectural optimization strategies, it helps engineering teams maintain budget compliance and implement FinOps best practices without compromising performance or reliability.

Características Principales

Multi-cloud cost analysis strategies for AWS, Azure, and Google Cloud Platform
Standardized tagging strategies for granular cost allocation and visibility
Terraform patterns for cost-saving lifecycle policies and automated budget alerts
Optimization patterns for Reserved Instances, Savings Plans, and Spot/Preemptible instances
Right-sizing recommendations for compute, database, and storage resources
0 GitHub stars

Casos de Uso

Reducing monthly cloud bills by identifying and downsizing over-provisioned resources
Migrating to cost-efficient architecture patterns like Serverless and multi-tier storage
Implementing automated cost governance and budget monitoring via Infrastructure as Code

Acerca de

Características Principales

Multi-cloud cost analysis strategies for AWS, Azure, and Google Cloud Platform
Standardized tagging strategies for granular cost allocation and visibility
Terraform patterns for cost-saving lifecycle policies and automated budget alerts
Optimization patterns for Reserved Instances, Savings Plans, and Spot/Preemptible instances
Right-sizing recommendations for compute, database, and storage resources
0 GitHub stars

Casos de Uso

Reducing monthly cloud bills by identifying and downsizing over-provisioned resources
Migrating to cost-efficient architecture patterns like Serverless and multi-tier storage
Implementing automated cost governance and budget monitoring via Infrastructure as Code