Can I scale based on metrics other than CPU?

Yes, you can configure the skill to generate scaling policies based on memory utilization, request counts, or other specific application loads.

Is the generated code production-ready?

Yes, the skill follows best practices for security and scalability, providing complete configuration code that can be integrated into your deployment pipeline.

Does this skill help with cost optimization?

Absolutely. By implementing precise scaling thresholds and cooldown periods, it ensures you only use the resources necessary for your current load.

What platforms does this skill support?

The skill generates configurations primarily for Kubernetes (HPA) and major cloud infrastructure providers that support dynamic scaling policies.

Auto-Scaling Policy Configurator

Name: Auto-Scaling Policy Configurator
Author: jeremylongshore

byjeremylongshore

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883

Despliegue y DevOps

Automates the generation of production-ready auto-scaling policies and infrastructure configurations to ensure high availability and resource efficiency.

Acerca de

This skill empowers Claude to design and implement sophisticated auto-scaling strategies tailored to specific application needs and infrastructure environments. By analyzing target metrics such as CPU utilization, memory pressure, or request counts, the skill generates platform-specific configuration code—including Kubernetes Horizontal Pod Autoscalers (HPA)—that adheres to industry best practices. It is particularly useful for DevOps engineers looking to automate resource management, improve system resilience, and optimize cloud costs through dynamic resource allocation.

Características Principales

Tailors scaling triggers based on CPU, memory, or custom metrics
883 GitHub stars
Optimizes resource thresholds to prevent over-provisioning
Generates Kubernetes HPA and scaling policy configurations
Implements high availability and fault tolerance best practices
Provides deployment-ready Infrastructure-as-Code (IaC) snippets

Casos de Uso

Scaling web applications automatically during sudden traffic spikes
Setting up infrastructure-level scaling for peak business hour loads
Configuring dynamic resource allocation for Kubernetes deployments

Acerca de

Características Principales

Tailors scaling triggers based on CPU, memory, or custom metrics
883 GitHub stars
Optimizes resource thresholds to prevent over-provisioning
Generates Kubernetes HPA and scaling policy configurations
Implements high availability and fault tolerance best practices
Provides deployment-ready Infrastructure-as-Code (IaC) snippets

Casos de Uso

Scaling web applications automatically during sudden traffic spikes
Setting up infrastructure-level scaling for peak business hour loads
Configuring dynamic resource allocation for Kubernetes deployments