Scaling Policies

5 minutes 5 Questions

Scaling Policies are rules that define how an Auto Scaling group should scale up or scale down based on specific metrics or conditions. They can be created based on Amazon CloudWatch alarms, target tracking scaling policies, or scheduled (time-based) policies. Scaling policies determine when to add…

AWS Solution Architect: Auto-Scaling - Scaling Policies

Scaling Policies are an integral part of the AWS Auto-Scaling feature. They determine when and how to scale your applications.

Importance: Scaling Policies are important because they enable your application to handle variations in workload and traffic. By effectively using Scaling Policies, you can maintain the performance and availability of your applications, while also controlling your AWS costs.

Concept: Scaling Policies are rules that define when and how to adjust the quantity of EC2 instances in an Auto Scaling group. You can scale based on metrics like CPU Utilization, Network Traffic or even custom metrics. There are three types of Scaling Policies: Target Tracking Scaling, Step Scaling, and Simple/Manual Scaling.

How it Works: When a certain defined metric crosses the threshold, the Scaling Policy triggers an action to adjust the number of instances. For example, if CPU Utilization exceeds 70%, a policy could be set to add 2 more instances to the group.

Exam Tips: When answering questions on Scaling Policies, understand the scenario and choose the appropriate type of Scaling Policy. Remember that Target Tracking Scaling is often used to maintain a specific level of a metric (like keeping CPU Utilization at 50%), Step Scaling is used for more granular control, and Simple/Manual Scaling is used when sporadic scaling is needed. AWS might present an extreme increase in demand scenario, thus enabling automatic scaling to cover it would be the right answer. If a question involves managing costs or meeting certain performance levels, the answer likely involves leveraging Scaling Policies.

Remember: Scaling Policies in AWS are not just about handling increased demand, but also about efficiently managing resources and controlling costs.

When studying for your exam, ensure you understand the different types of Scaling Policies, when to use each, and how they can be configured and fine-tuned to suit different scenarious.

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Question 1

Your company has a web application running on AWS, and it faces sudden spikes in traffic every morning. Management wants you to design an autoscaling policy to handle these spikes effectively. Which scaling policy would be the best choice?

Step Scaling Simple Scaling Scheduled Scaling Target Tracking Scaling

Correct Answer: Target Tracking Scaling

Target Tracking Scaling automates scaling based on a target value of predefined CloudWatch metrics. This would handle the spikes in traffic effectively without manual intervention.

Question 2

A company has a critical batch process running on EC2 instances late at night during low-traffic hours. Which scaling policy would be efficient to automatically launch new instances to process the workload faster?

Simple Scaling Scheduled Scaling Target Tracking Scaling Step Scaling

Correct Answer: Scheduled Scaling

Scheduled Scaling allows scaling actions to be planned at specific times or recurring periods, making it the best choice for scaling during low-traffic hours for a critical batch process.

Question 3

An online gaming application can have arbitrary capacity requirements ranging from 100 to 10,000 concurrent users. Which autoscaling policy should the architect suggest for such unpredictable workloads?

Target Tracking Scaling Scheduled Scaling Step Scaling Simple Scaling

Correct Answer: Step Scaling

Step Scaling allows to choose multiple steps of scaling to add or remove instances based on varying levels of demand. It is suitable for unpredictable workloads where the application might require rapid scaling.

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