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Dynamic automatic adjustment of instances and resources to load, improving availability and cost-efficiency.
Autoscaling automatically adjusts an application's instance count and resource allocation to match real load. It improves availability and cost efficiency by dynamically scaling capacity — in cloud platforms, container orchestrators, or hybrid environments. Policies, metrics and thresholds determine scaling behaviour and safety limits.
Number of running instances or pods to measure capacity.
Percentage resource utilization to trigger scaling actions.
Throughput and response time as indicators for needed scaling.
Widely used implementation of pod-based autoscaling based on CPU and custom metrics.
Cloud provider mechanism to autoscale EC2 instances using policies and target metrics.
Examples from functions-as-a-service (e.g., provisioned concurrency) for controlling cold starts and throughput.
Set up metrics and observability; validate relevant metrics.
Define scaling rules with min/max and cooldown parameters.
Test autoscaling in stages (staging → canary → prod) and monitor.