Which two metrics are collected for autoscaling triggers in monitoring services?

Which two metrics are collected for autoscaling triggers in monitoring services?

• A. Disk I/O and Network Latency
• B. CPU and Memory utilization
• C. Process count and Application response time
• D. Database connections and Cache hits

Answer: (B)

The selection of CPU and Memory utilization as the metrics collected for autoscaling triggers in monitoring services is well-founded due to their critical role in understanding system performance and resource demand. CPU utilization indicates how much of the processor's capacity is being used and is a direct indicator of the load the system is under. High CPU usage often signals that an application is under stress and may require additional resources to manage load effectively. Likewise, Memory utilization informs about the amount of RAM being consumed by processes. When memory usage is high, it can lead to system slowdowns or degraded application performance. By monitoring these two metrics, organizations can trigger autoscaling to provision additional compute resources to maintain optimal performance and avoid potential outages. This approach ensures that the infrastructure is responsive to fluctuations in demand, thereby ensuring seamless performance and user satisfaction. Other metrics, while relevant in specific contexts, do not serve the fundamental purpose of scaling resources based on immediate load and resource consumption.

The selection of CPU and Memory utilization as the metrics collected for autoscaling triggers in monitoring services is well-founded due to their critical role in understanding system performance and resource demand.

CPU utilization indicates how much of the processor's capacity is being used and is a direct indicator of the load the system is under. High CPU usage often signals that an application is under stress and may require additional resources to manage load effectively. Likewise, Memory utilization informs about the amount of RAM being consumed by processes. When memory usage is high, it can lead to system slowdowns or degraded application performance. By monitoring these two metrics, organizations can trigger autoscaling to provision additional compute resources to maintain optimal performance and avoid potential outages.

This approach ensures that the infrastructure is responsive to fluctuations in demand, thereby ensuring seamless performance and user satisfaction. Other metrics, while relevant in specific contexts, do not serve the fundamental purpose of scaling resources based on immediate load and resource consumption.