What platforms does this skill support?

It primarily supports Kubernetes for Horizontal Pod Autoscaling (HPA) and general cloud infrastructure platforms through standardized configuration code.

Does it provide deployment-ready code?

Yes, the skill generates complete, production-ready configuration files that can be reviewed and directly applied to your infrastructure.

Can it scale based on custom metrics?

Yes, it can configure policies based on CPU, memory utilization, or specific incoming request thresholds as required by your application.

Does it include security best practices?

Yes, all generated configurations follow industry-standard security and scalability best practices to ensure resilient and safe infrastructure.

How does it help with cost management?

By implementing dynamic scaling, it ensures you only provision the resources needed for current demand, preventing expensive over-provisioning.

Auto-Scaling Configurator

Name: Auto-Scaling Configurator
Author: BbgnsurfTech

byBbgnsurfTech

•

Despliegue y DevOps

Automates the generation of production-ready auto-scaling policies and high-availability configurations for cloud infrastructure.

Acerca de

The Auto-Scaling Configurator skill empowers Claude to design and implement dynamic resource allocation strategies tailored to specific application requirements. By analyzing target metrics such as CPU and memory utilization, it generates precise configurations like Kubernetes Horizontal Pod Autoscalers (HPA) and infrastructure-level scaling policies. This skill ensures your applications maintain high availability and performance during peak loads while optimizing cloud costs through intelligent, metric-driven resource management.

Características Principales

3 GitHub stars
Suggests optimal scaling metrics based on specific application load profiles
Implements high-availability and fault-tolerance patterns
Creates dynamic scaling policies based on CPU and memory thresholds
Provides production-ready infrastructure-as-code snippets
Generates Kubernetes Horizontal Pod Autoscaler (HPA) configurations

Casos de Uso

Configuring cloud infrastructure to automatically scale out during peak business hours
Establishing resilience and cost-efficiency through metric-based dynamic resource allocation
Setting up HPA for a Kubernetes-based web application to handle traffic spikes

Acerca de

Características Principales

3 GitHub stars
Suggests optimal scaling metrics based on specific application load profiles
Implements high-availability and fault-tolerance patterns
Creates dynamic scaling policies based on CPU and memory thresholds
Provides production-ready infrastructure-as-code snippets
Generates Kubernetes Horizontal Pod Autoscaler (HPA) configurations

Casos de Uso

Configuring cloud infrastructure to automatically scale out during peak business hours
Establishing resilience and cost-efficiency through metric-based dynamic resource allocation
Setting up HPA for a Kubernetes-based web application to handle traffic spikes