Does this skill help with high availability?

Absolutely. By implementing dynamic scaling, the skill ensures your infrastructure remains resilient and responsive under varying load conditions.

What metrics are supported for scaling decisions?

Common metrics include CPU utilization, memory usage, and request counts, though the skill can adapt to other business-specific scaling requirements.

Can I set custom thresholds for scaling?

Yes, you can specify target metrics like CPU percentage, memory usage, or request volume to define when your application should scale up or down.

What platforms does this skill support?

The skill is designed to generate configurations for various platforms, with a focus on Kubernetes HPA and general cloud infrastructure scaling policies.

Auto-Scaling Configurator

Name: Auto-Scaling Configurator
Author: intent-solutions-io

byintent-solutions-io

部署与 DevOps

Generates production-grade auto-scaling policies and configurations for Kubernetes and cloud infrastructure.

关于

The Auto-Scaling Configurator skill empowers developers and DevOps engineers to automate the creation of complex scaling policies for applications and infrastructure. By interpreting natural language requirements, it generates production-ready configurations for Kubernetes Horizontal Pod Autoscalers (HPA) and dynamic resource allocation systems. This skill is essential for maintaining high availability and performance while optimizing cloud costs, as it bridges the gap between high-level scaling requirements and the technical implementation of metric-based thresholds and infrastructure-as-code snippets.

主要功能

Production-ready infrastructure-as-code output
Kubernetes HPA configuration generation
Load-based scaling policy optimization
Dynamic resource allocation for high availability
0 GitHub stars
Metric-based scaling (CPU, memory, and custom metrics)

使用场景

Setting up dynamic scaling for web applications based on CPU utilization
Configuring Horizontal Pod Autoscaling for Kubernetes clusters
Managing infrastructure scaling for peak traffic during business hours

关于

主要功能

Production-ready infrastructure-as-code output
Kubernetes HPA configuration generation
Load-based scaling policy optimization
Dynamic resource allocation for high availability
0 GitHub stars
Metric-based scaling (CPU, memory, and custom metrics)

使用场景

Setting up dynamic scaling for web applications based on CPU utilization
Configuring Horizontal Pod Autoscaling for Kubernetes clusters
Managing infrastructure scaling for peak traffic during business hours