Today, We are about to learn What is the main function of Target tracking?, What is the use of target tracking?, How does target tracking work?
What is the main function of Target tracking?
Target tracking primarily works in AWS Auto Scaling to dynamically adjust the number of instances in response to changes in a specified metric. Its main function is to maintain a target value for the metric by adding or removing instances from an autoscaling group. For example, if you set a target tracking policy for CPU usage at 50%, autoscaling will adjust the number of instances to keep the average CPU usage close to this target value.
Using target tracking in AWS autoscaling is about automating the scaling process based on a desired metric. It simplifies the management of scaling policies by allowing you to specify a target value for a metric rather than defining specific thresholds and scaling actions. This approach ensures that your application can dynamically scale to handle diverse workloads without manual intervention, optimize performance and profitability.
What is the use of target tracking?
Target tracking works by continuously monitoring the specified metric (such as CPU usage, number of requests, etc.) and comparing it to the target value you set. Based on the deviation from the target, autoscale calculates and applies scaling adjustments to the number of instances in your autoscale group. For example, if the metric exceeds the target, autoscaling will add instances to reduce the metric towards the target; If the metric falls below the target, it will remove instances accordingly.
How does target tracking work?
In the context of AWS terminology, “Target Track” appears to be a typographical error or a misunderstood term. It may refer to “target tracking”, which is the correct term used in AWS Auto scaling to describe the mechanism of maintaining a specified target value for a metric through scaling actions automated.
In IoT (Internet of Things), target tracking can refer to a similar concept where IoT devices adjust their operations or behaviors based on a target metric or condition. For example, in a smart thermostat system, the device can adjust the temperature setting to maintain a target indoor temperature based on user preferences or external weather conditions. Target tracking in IoT applications aims to achieve desired operational states or conditions autonomously, similar to how it works within the AWS Auto scale, but applied to IoT device management and operations.
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