ECS Service Auto Scaling

5 minutes 5 Questions

Amazon ECS Service Auto Scaling allows you to automatically adjust your ECS services' desired task count in response to changing workloads. You can configure two types of scaling policies: Target Tracking Scaling and Step Scaling. Target Tracking Scaling maintains a specified average value for a chosen CloudWatch metric (e.g., CPU or memory utilization). Step Scaling defines the number of tasks to add or remove based on CloudWatch metric alarm thresholds. Auto Scaling ensures that the appropriate number of tasks are allocated to handle the load, optimizing resource usage, and cost.

Guide on Amazon ECS Service Auto Scaling

What it is: The ECS (Elastic Container Service) Service Auto Scaling in AWS (Amazon Web Services) is a feature that automatically adjusts the desired count of tasks in your service in response to Cloudwatch alarms. br/>
Why it is important: Auto Scaling is crucial because it allows applications to scale out (add more instances) to handle increased load and to scale in (remove instances) to minimize costs during times of lower demand. This ensures that you have the appropriate number of Amazon EC2 instances available to handle the load for your application. br/>
How it works: The Auto Scaling works by you defining scaling policies based on CloudWatch alarms. When those alarms trigger, Amazon ECS automatically adjusts the desired count of tasks in your service. br/>
Exam Tips on ECS Service Auto Scaling: In the exam, answering questions on ECS Service Auto Scaling requires understanding the basic concept, importance, and workings of the feature. It will also be helpful to understand the correlation between Auto Scaling and CloudWatch alarms. You will also need to know when to apply auto-scaling. For example, when the load in your applications goes up or when there is a need to minimize costs. Remember, the key to successfully answering these questions is a clear understanding of what ECS Service Auto Scaling is, its importance and functionality.

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Question 1

ABC Corp runs its APIs on Amazon ECS services behind an Application Load Balancer (ALB). There's a requirement to scale the ECS service dynamically, based on the number of requests per target. Which approach would you recommend?

Use ECS Service Auto Scaling with an ALB RequestCountPerTarget metric. Adjust the desired ECS task count manually according to load. Configure horizontal pod autoscaling based on ALB RequestCountPerTarget metric. Enable AWS Auto Scaling for the entire ECS cluster.

Correct Answer: Use ECS Service Auto Scaling with an ALB RequestCountPerTarget metric.

ECS Service Auto Scaling is the appropriate choice for adjusting ECS tasks automatically. Use the ALB RequestCountPerTarget metric in target tracking scaling policies to scale the service based on the number of requests per target. Other options like horizontal pod autoscaling and EC2 instance-level Auto Scaling don't address the scaling of the individual ECS service.

Question 2

An e-commerce company runs its web frontend as an ECS service. After a recently successful marketing campaign, they expect traffic spikes. How can they prepare for the traffic spikes with minimal manual work?

Set up ECS Service Auto Scaling with target tracking and configure multiple scaling policies. Enable AWS Auto Scaling for the entire ECS cluster. Configure scheduled-based ECS Service Auto Scaling. Implement a custom Lambda scaler to adjust the ECS tasks count based on the marketing campaign date.

Correct Answer: Set up ECS Service Auto Scaling with target tracking and configure multiple scaling policies.

ECS Service Auto Scaling with target tracking, supports multiple scaling policies, allowing automatic adjustment of running tasks based on predefined metric targets when traffic spikes occur. Other options like custom Lambda scalers, enabling AWS Auto Scaling for the entire ECS cluster, or scaling the underlying EC2 instances alone don't adapt dynamically.

Question 3

A company uses Amazon ECS to deploy a critical application with multiple microservices. The chief architect notices that one of the microservices has variable load and needs to scale automatically to maintain optimal performance. Which configuration should be implemented for this ECS service?

Enable AWS Auto Scaling for the entire ECS cluster. Configure Service Auto Scaling with target tracking scaling policies. Configure Service Auto Scaling with scheduled scaling actions. Configure EC2 Auto Scaling with target tracking scaling policies.

Correct Answer: Configure Service Auto Scaling with target tracking scaling policies.

Service Auto Scaling with target tracking scaling policies is the appropriate solution as it adjusts the desired number of tasks automatically based on predefined CloudWatch metric targets. EC2 Auto Scaling only scales the underlying instances, and enabling cluster-level scaling doesn't address the specific microservice. Scheduled scaling actions and Lambda functions require manual management, increasing the complexity.

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