The AWS Certified Solutions Architect – Associate exam, SAA-C03, includes assessment of this proficiency, recognizing it as a cornerstone of a well-architected framework. Therefore, the focus of this article is explaining the scalability capabilities of two AWS services: Amazon EC2 Auto Scaling and AWS Auto Scaling, and discussing their appropriate use cases.
1. Amazon EC2 Auto Scaling
Amazon Elastic Compute Cloud (Amazon EC2) Auto Scaling provides scalability for Amazon EC2 applications. This helps you to assure that you are running your preferred number of Amazon EC2 instances.
Amazon EC2 Auto Scaling can effortlessly scale Amazon EC2 instances to meet demand, schedule scaling activities, and manage unhealthy EC2 instances. This would mean fewer manual processes and less time spent on managing the infrastructure, boosting efficiency and productivity.
Use Case:
Let’s consider an e-commerce site which experiences high user traffic during weekends and holidays. To ensure user experience is not compromised during these peak periods, Amazon EC2 Auto Scaling can be used.
Supposing the site typically needs ten instances during regular periods, the company may configure their EC2 Auto Scaling to scale up to 20 instances during the peak periods. This is achieved by setting a CloudWatch alarm that triggers when the average CPU utilization exceeds a threshold, say 75%, for a specified period.
This way, Amazon EC2 Auto Scaling automatically adds (scales out) instances to handle the increased load, and reduces (scales in) the number of instances during off-peak times, thereby optimizing the cost.
2. AWS Auto Scaling
AWS Auto Scaling is designed to automatically scale resources across multiple services. This includes resources such as EC2 instances and Spot Fleets, ECS tasks, DynamoDB tables and indexes, and Aurora Replicas.
AWS Auto Scaling offers a unified scaling experience, providing scalability not just for applications in the cloud, but also for the database layer, such as Amazon RDS instances and Amazon DynamoDB tables.
Use Case:
Consider a web application that uses Amazon EC2 instances to serve its frontend, and Amazon RDS for backend database operations. During a sale event, an influx of users is expected, resulting in increased demand on both the web server and the database.
To handle this, AWS Auto Scaling can be set with a target utilization levels for multiple resources. For instance, set the target utilization level of both EC2 instances and RDS instances to 70%. AWS Auto Scaling will automatically adjust the resources to maintain the utilization at the target level. This ensures continuous performance of your application even during high traffic periods.
Conclusion:
Both Amazon EC2 Auto Scaling and AWS Auto Scaling provide efficient scalability capabilities. However, select the best service based on your architectural needs. If you need to scale EC2 instances only, Amazon EC2 Auto Scaling is the right choice. But if your architecture involves multiple resources and services, AWS Auto Scaling would be better suited. Nevertheless, by utilizing either of these services, organizations ensure improved application availability and performance, smarter scaling, and balance cost-efficiency, aligning with AWS Well-Architected Framework’s best practices.
Practice Test
True or False: Amazon EC2 Auto Scaling is designed to automatically adjust computing capacity based on demand.
- True
- False
Answer: True
Explanation: Amazon EC2 Auto Scaling automatically helps to increase or decrease the number of EC2 instances depending on demand, ensuring consistent performance during peak or idle periods.
What are the main benefits of AWS Auto Scaling? (Multiple Select)
- a) Increase efficiency
- b) Reduce cost
- c) None of the above
- d) All of the above
Answer: d) All of the above
Explanation: AWS Auto Scaling helps to efficiently use resources and reduce costs by adjusting capacity in line with demand.
True or False: AWS Auto Scaling is only applicable for Amazon EC2 instances.
- True
- False
Answer: False
Explanation: AWS Auto Scaling can be used with various AWS services such as Amazon EC2, DynamoDB, Amazon Aurora, etc.
What are the scaling plans in AWS Auto Scaling? (Multiple Select)
- a) Manual Scaling
- b) Scheduled Scaling
- c) Dynamic Scaling
- d) All of the above
Answer: d) All of the above
Explanation: AWS Auto Scaling offers Manual Scaling (user-defined), Scheduled Scaling (at defined times), and Dynamic Scaling (in response to changing demand).
Which AWS service provides automatic scaling for applications hosted in containerized services?
- a) Amazon ECS
- b) AWS Lambda
- c) Amazon RDS
- d) Amazon Redshift
Answer: a) Amazon ECS
Explanation: Amazon ECS, the Elastic Container Service, can automatically adjust the number of containers based on the demand of the application.
True or False: Management of Amazon EC2 Auto Scaling is complex and requires significant AWS experience.
- True
- False
Answer: False
Explanation: Amazon EC2 Auto Scaling is designed to be simple and user-friendly, allowing users to set desired configurations and leaving the rest of the task to AWS.
What AWS service allows for scaling of read and write throughput to adjust to actual traffic patterns?
- a) Amazon S3
- b) Amazon EC2
- c) Amazon DynamoDB
- d) Amazon RDS
Answer: c) Amazon DynamoDB
Explanation: Amazon DynamoDB can automatically adjust capacity as per fluctuations in workload patterns, enabling efficient scaling for applications.
True or False: AWS Auto Scaling can help optimize application availability.
- True
- False
Answer: True
Explanation: AWS Auto Scaling ensures optimal resource availability by adjusting capacity in real-time, preventing application overload and enhancing performance.
What AWS Auto Scaling strategy increases or decreases the current capacity of the group by a specified percentage?
- a) Exact capacity
- b) Step scaling
- c) Simple scaling
- d) Percent change in capacity
Answer: d) Percent change in capacity
Explanation: This strategy adjusts the capacity depending on the percentage change set, keeping the system adaptive to changing loads.
True or False: In Amazon EC2 Auto Scaling, it’s not possible to combine multiple launch templates or configurations to use with an Auto Scaling group.
- True
- False
Answer: False
Explanation: It is indeed possible to combine multiple launch templates or configurations with an Auto Scaling group in Amazon EC2 Auto Scaling.
Which of the following is not a use case of Auto Scaling?
- a) Fault tolerance
- b) Data replication
- c) Scalable web applications
- d) Multi-tier application scaling
Answer: b) Data replication
Explanation: AWS Auto Scaling is used for fault tolerance, scalable web applications, and multi-tier application scaling but it does not directly support data replication.
What type of AWS scaling continuously maintains average utilization of your Auto Scaling group to be at the specified target?
- a) Scheduled Scaling
- b) Step Scaling
- c) Target Tracking Scaling
- d) Manual Scaling
Answer: c) Target Tracking Scaling
Explanation: Target Tracking Scaling in AWS helps maintain average utilization at a specified target, keeping the capacity balanced according to changing loads.
True or False: Cost optimization is one of the primary benefits of AWS Auto Scaling.
- True
- False
Answer: True
Explanation: AWS Auto Scaling accurately matches resources to current demand, reducing unnecessary spendings and optimizing costs.
AWS Auto Scaling can be used to adjust capacity for which of the following AWS Services? (Multiple Select)
- a) EC2 Spot Fleets
- b) ECS tasks
- c) EMR jobs
- d) RDS instances
- e) DynamoDB tables
Answer: a) EC2 Spot Fleets, b) ECS tasks, c) EMR jobs, e) DynamoDB tables
Explanation: Except for RDS instances, Auto Scaling can be used to adjust capacity for EC2 Spot Fleets, ECS tasks, EMR jobs, and DynamoDB tables.
True or False: Amazon EC2 Auto Scaling can only adjust capacity in response to an alarm.
- True
- False
Answer: False
Explanation: While Amazon EC2 Auto Scaling can adjust capacity in response to an alarm, it can also adjust capacity at scheduled times or in response to changes in workload patterns.
Interview Questions
What is Amazon EC2 Auto Scaling?
Amazon EC2 Auto Scaling is a service that helps you ensure that you have the correct number of Amazon EC2 instances available to handle the load for your application. You can create a scaling policy for your application based on its specific needs.
How can AWS Auto Scaling benefit an organization?
AWS Auto Scaling allows organizations to optimize their applications for performance and cost. It can automatically add or remove AWS resources based on the demand of your applications, ensuring the right resources are available at the right time which can lead to cost savings.
Can you explain the key components of Amazon EC2 Auto Scaling?
The key components of Amazon EC2 Auto Scaling are groups, configuration templates, and scaling policies. The groups contain EC2 instances that share similar characteristics and are treated as a logical pooling for the purposes of scaling and management. Configuration templates are used to launch EC2 instances into an auto-scaling group and contain information such as instance type, key pair, security groups, and block device mapping among others. The scaling policies determine when and how to scale your applications.
What are the common use cases of Amazon EC2 Auto Scaling?
The common use cases of Amazon EC2 Auto Scaling include maintaining application availability, dynamically scaling your applications in response to changing demand, and scheduled scaling based on predictable load changes.
What is the difference between Amazon EC2 Auto Scaling and AWS Auto Scaling?
Amazon EC2 Auto Scaling is specifically for scaling Amazon EC2 instances in groups. AWS Auto Scaling, on the other hand, allows you to scale other AWS services as well, such as DynamoDB, ECS and Aurora among others.
What do you understand by the term ‘scale out’ and ‘scale in’?
‘Scale out’ refers to the process of adding more EC2 instances to a group in response to increased demand. On the other hand, ‘scale in’ refers to the process of removing unnecessary EC2 instances when demand decreases.
Can you describe how a lifecycle hook works with Amazon EC2 Auto Scaling?
Lifecycle hooks allow you to perform custom actions by pausing instances when an Auto Scaling event occurs. They cause instances to wait either at launch or at termination, before the instance becomes active or before it is terminated, allowing you to take appropriate actions.
How does predictive scaling work in AWS Auto Scaling?
Predictive scaling works by forecasting future demands using machine learning algorithms and schedules scaling actions in advance to meet the predicted demand.
What is cooldown in AWS Auto Scaling?
Cooldown is a period that helps to ensure that your Auto Scaling group doesn’t launch or terminate additional instances before the previous scaling activity takes effect.
How does AWS Auto Scaling work with Elastic Load Balancing?
AWS Auto Scaling works with Elastic Load Balancing by distributing incoming traffic across multiple targets, such as EC2 instances. When you enable Auto Scaling, it ensures that your application has the right amount of capacity to handle the current traffic demand.
What is scheduled scaling in AWS?
Scheduled scaling is an AWS function that allows you to scale your applications in anticipation of known traffic patterns.
How does Amazon EC2 Auto Scaling enhance fault tolerance?
Amazon EC2 Auto Scaling enhances fault tolerance by maintaining the health of applications, automatically replacing instances that are unresponsive, impaired, or detached from load balancers.
Are there charges for using AWS Auto Scaling?
AWS Auto Scaling itself is a free service. However, users pay for the underlying EC2 instances or other AWS resources they consume.
Can Amazon EC2 Auto Scaling be used across multiple AWS regions?
No, Amazon EC2 Auto Scaling cannot be used across multiple AWS regions. Auto Scaling groups are region-specific.
Can Auto Scaling policies be updated after they have been created?
Yes, Auto Scaling policies can be updated after they have been created. The changes to the policy take effect as soon as the update request is made.
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