You are configuring Azure Monitor autoscale rules for different workloads. Match each scaling requirement on the left to its correct Azure Monitor metric and time aggregation configuration on the right.
- A memory-sensitive background worker running on an Azure App Service plan must scale out when the average memory usage across the instances exceeds .Metric: Memory Percentage; Time Aggregation: Average
- A CPU-intensive batch rendering service on an Azure Virtual Machine Scale Set (VMSS) must scale out if any single VM instance reaches CPU utilization.Metric: CPU Percentage; Time Aggregation: Maximum
- An API gateway on an Azure App Service plan must scale out when the total volume of network payload data received by the plan exceeds .Metric: Data In; Time Aggregation: Total
Cevap
Match the memory-sensitive worker to Memory Percentage and Average; match the CPU-intensive batch rendering to CPU Percentage and Maximum; and match the API gateway network volume to Data In and Total.
The correct pairings align the metric and time aggregation with the workload constraints: Memory Percentage (Average) for overall memory usage, CPU Percentage (Maximum) to scale when any single instance peaks, and Data In (Total) to measure the cumulative incoming network payload.
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Anahtar Kavram
Azure Monitor autoscale rules require selecting the correct resource metric and time aggregation (statistic) to properly align with workload requirements and prevent issues like flapping or missed scaling events.
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