How does this help with infrastructure cost management?

By implementing dynamic scaling, the skill ensures you only use the resources you need, scaling down during low-traffic periods to prevent over-provisioning.

Does this skill support major cloud providers?

Yes, it is designed to generate infrastructure-level scaling policies compatible with major cloud environments and Kubernetes-based deployments.

Is the generated configuration code secure?

Yes, the skill follows industry best practices for security and scalability to ensure that the resulting configurations are production-ready.

Can I define custom scaling metrics?

Absolutely. You can specify thresholds for CPU, memory, or request-based metrics to trigger scaling actions based on your specific application needs.

Can I use this for non-Kubernetes environments?

While it excels at Kubernetes HPA, it can also generate logic and policy definitions for general infrastructure-level dynamic resource allocation.

Auto-Scaling Configurator

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

byintent-solutions-io

Deployment & DevOps

Generates production-ready auto-scaling configurations and policies to ensure application high availability and dynamic resource management.

About

The Auto-Scaling Configurator skill enables Claude to design and implement robust scaling policies for both applications and infrastructure. By analyzing specific performance requirements such as CPU/memory thresholds and request volume, it automates the creation of Horizontal Pod Autoscaler (HPA) manifests and platform-specific scaling rules. This skill is essential for DevOps engineers looking to optimize system performance, minimize operational costs, and maintain resilience during fluctuating load conditions without the manual overhead of manual configuration.

Key Features

Infrastructure-level scaling policy design
High availability and fault tolerance optimization
Automated Kubernetes HPA manifest generation
Dynamic scaling based on CPU and memory utilization
Production-ready configuration code for various platforms
0 GitHub stars

Use Cases

Implementing dynamic resource allocation for peak business hour traffic management
Configuring fault-tolerant infrastructure policies to maintain system stability
Scaling a Kubernetes web application based on real-time CPU utilization thresholds

About

Key Features

Infrastructure-level scaling policy design
High availability and fault tolerance optimization
Automated Kubernetes HPA manifest generation
Dynamic scaling based on CPU and memory utilization
Production-ready configuration code for various platforms
0 GitHub stars

Use Cases

Implementing dynamic resource allocation for peak business hour traffic management
Configuring fault-tolerant infrastructure policies to maintain system stability
Scaling a Kubernetes web application based on real-time CPU utilization thresholds