Understanding scaling options for your Azure Functions is crucial for performance and cost optimization.
Autoscaling automatically adjusts the number of instances running your function based on demand. This ensures your function can handle varying workloads without manual intervention. You can configure scaling based on metrics like CPU usage, queue length, or HTTP requests.
You'll define scaling rules within your function app's configuration. These rules dictate how many instances to run based on metrics.
// Example (Simplified)
// Scale up when CPU usage exceeds 70%
// Scale down when CPU usage falls below 30%
Azure Functions offers different instance sizes to accommodate varying computational needs. Larger instances provide more resources (CPU, memory) but also cost more. Start with a smaller instance and scale up if necessary.
Common instance sizes include: Consumption Plan (Standard and Premium), App Service Plan.
Concurrency determines the maximum number of executions that a function instance can handle concurrently. Increase concurrency for higher throughput, but be mindful of potential resource contention.
You can configure concurrency limits within your function app settings.