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From auto-scaling-configurator
Configures auto-scaling policies for AWS ASG, GCP MIG, Azure VMSS, and Kubernetes HPA. Generates Terraform, YAML, or CLI configs with metric thresholds and cooldowns.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin auto-scaling-configuratorHow this skill is triggered — by the user, by Claude, or both
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/auto-scaling-configurator:configuring-auto-scaling-policiesThis skill is limited to the following tools:
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Configure auto-scaling policies for cloud workloads across AWS Auto Scaling Groups, GCP Managed Instance Groups, Azure VMSS, and Kubernetes Horizontal Pod Autoscaler (HPA). Generate scaling configurations based on CPU, memory, request rate, or custom metrics with appropriate thresholds, cooldown periods, and scale-in protection.
Provides AWS CloudFormation templates for Auto Scaling Groups on EC2, ECS, and Lambda, including launch configurations/templates, scaling policies, lifecycle hooks, predictive scaling, and best practices for high availability.
Configures CAST AI autoscaler policies, spot instances, downscalers, evictors, and node templates for Kubernetes cluster cost optimization.
Guides on Azure Kubernetes Service (AKS) Automatic mode GA 2025: Karpenter autoscaling, HPA/VPA/KEDA, workload identity, networking, billing model, and cluster creation via az CLI.
Share bugs, ideas, or general feedback.
Configure auto-scaling policies for cloud workloads across AWS Auto Scaling Groups, GCP Managed Instance Groups, Azure VMSS, and Kubernetes Horizontal Pod Autoscaler (HPA). Generate scaling configurations based on CPU, memory, request rate, or custom metrics with appropriate thresholds, cooldown periods, and scale-in protection.
aws, gcloud, or az)kubectl configured with cluster access and metrics-server deployed| Error | Cause | Solution |
|---|---|---|
No scaling activity despite high load | Metric not reaching threshold or cooldown active | Verify metric source in CloudWatch/Stackdriver; check cooldown timer with describe-scaling-activities |
Scaling too aggressively (flapping) | Cooldown too short or threshold too sensitive | Increase cooldown period and widen the gap between scale-out and scale-in thresholds |
Max capacity reached | Instance/pod limit hit during traffic spike | Raise max_size or implement request queuing as a backpressure mechanism |
HPA unable to compute replica count | Metrics server not deployed or metric unavailable | Install metrics-server and verify kubectl top pods returns data |
FailedScaleUp: insufficient capacity | Cloud provider out of capacity in selected AZ/region | Add multiple AZs to the ASG or use mixed instance types with allocation strategy |