A company is deploying a web application in the cloud and expects variable traffic, with occasional spikes during certain events. To ensure the application remains responsive without incurring unnecessary costs during off-peak times, the cloud engineer has been asked to configure an auto-scaling service. What is the most effective scaling policy the engineer should implement to meet these requirements?
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Target tracking scaling policy, configuring it to maintain a specific target for average CPU utilization.
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Maintain a fixed number of instances at all times, regardless of traffic patterns.
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Manual scaling policy, requiring an administrator to manually increase or decrease the number of instances as needed.
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Schedule-based scaling policy, adding instances in anticipation of high traffic events known in advance.
A target tracking scaling policy allows the cloud engineer to specify a target value for a specific metric, such as Average CPU Utilization. The auto-scaling service then automatically adjusts the number of instances to keep the metric close to the target value. This ensures the application scales out during traffic spikes and scales in when the load decreases, optimizing resource use and cost. Other policies, like maintaining a fixed instance count, do not account for variable traffic and could lead to underprovisioning or overprovisioning of resources.
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What exactly is a target tracking scaling policy?
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How does auto-scaling optimize costs compared to fixed instance counts?
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What other scaling policies are available besides target tracking?