Concepts
Auto scaling in AWS can be implemented in multiple ways, serving both the EC2 compute layer and other resources.
EC2 Auto Scaling
EC2 Auto Scaling helps you ensure that you have the correct number of Amazon EC2 instances available to handle the load for your application.
Key Features:
- Dynamic Scaling: Adjusts the number of EC2 instances in response to varying load.
- Predictive Scaling: Uses machine learning algorithms to predict traffic and preemptively scale out resources.
- Scheduled Scaling: Increases or decreases the number of instances based on specific schedules.
How It Works:
- Create a launch template (or configuration) defining the EC2 instances.
- Define the scaling policies based on desired metrics (e.g., CPU utilization, network traffic).
- EC2 Auto Scaling creates and terminates instances based on these policies.
Example Policy for Dynamic Scaling
Create a scaling policy to add new EC2 instances when average CPU utilization exceeds 70%:
{
“AutoScalingGroupName”: “MyAutoScalingGroup”,
“PolicyName”: “ScaleOut”,
“PolicyType”: “TargetTrackingScaling”,
“TargetTrackingConfiguration”: {
“PredefinedMetricSpecification”: {
“PredefinedMetricType”: “ASGAverageCPUUtilization”
},
“TargetValue”: 70.0
}
}
AWS Auto Scaling
AWS Auto Scaling is broader and can be used to set up scaling for multiple resources beyond EC2, such as:
- Amazon ECS services
- Amazon DynamoDB tables and indexes
- Amazon RDS DB instances
- Amazon Aurora Replicas
- Amazon SageMaker endpoints
Application Auto Scaling
This type enables you to configure automatic scaling for the supported AWS services shown in the table below:
| Service | Scalable Dimension |
|---|---|
| Amazon ECS | Service tasks |
| DynamoDB | Table read/write capacity |
| RDS | Read Replicas |
| Aurora | Read Replicas |
| Amazon EMR | Instance groups |
| AppStream 2.0 | Fleet capacity |
Hibernation
Hibernation is an option for EC2 instances that allows you to pause your instance and resume it later. It’s ideal for scenarios where you have long-running processes that you might want to pause during off-peak times to save costs.
Key Points:
- When an instance is hibernated, the in-memory (RAM) state is preserved.
- The instance is stopped and the RAM state is written to a file in the root EBS volume, which allows the instance to resume its state.
- Currently, not all instance types support hibernation.
How To Enable Hibernation:
When you launch an instance, you can enable hibernation by setting the ‘Hibernate’ option.
aws ec2 run-instances –instance-type m3.medium –image-id ami-example –hibernate
Using auto scaling and hibernation effectively requires anticipating load patterns and understanding application behavior. This knowledge ensures that you can maximize performance and availability while optimizing costs on AWS. If you are preparing for the AWS Certified Solutions Architect – Associate exam, expect to illustrate a comprehensible understanding of these scaling strategies along with when and how to implement them as per different scenarios.
Answer the Questions in Comment Section
True/False: Auto Scaling in AWS allows you to scale EC2 instances based only on a fixed schedule.
- Answer: False
Explanation: AWS Auto Scaling allows you to scale EC2 instances based on demand (dynamic scaling) or on a fixed schedule.
True/False: Hibernation of EC2 instances saves the contents of the RAM to the root EBS volume.
- Answer: True
Explanation: Hibernation for EC2 instances saves the in-memory state to the root EBS volume, allowing for faster startup times when the instance is resumed.
Single Select: What service would you use for automatically adding or removing EC2 instances based on demand?
- A) AWS Lambda
- B) Amazon CloudFront
- C) AWS Auto Scaling
- D) Amazon RDS
Answer: C) AWS Auto Scaling
Explanation: AWS Auto Scaling dynamically adjusts the number of EC2 instances in your infrastructure to meet demand.
Multiple Select: Which of the following are valid scaling policies in AWS Auto Scaling?
- A) Target Tracking Scaling
- B) Simple Scaling
- C) Step Scaling
- D) Random Scaling
Answer: A) Target Tracking Scaling, B) Simple Scaling, C) Step Scaling
Explanation: Target Tracking, Simple, and Step Scaling are legitimate scaling policies, whereas Random Scaling is not.
True/False: Amazon ECS services can be scaled automatically using AWS Auto Scaling.
- Answer: True
Explanation: AWS Auto Scaling can also be used to scale Amazon ECS services, not just EC2 instances.
Single Select: AWS Auto Scaling can scale resources for which of the following services?
- A) Amazon EC2
- B) Amazon ECS
- C) Amazon RDS
- D) All of the above
Answer: D) All of the above
Explanation: AWS Auto Scaling can scale various services including Amazon EC2, ECS, and RDS, and more.
True/False: AWS Fargate is a serverless compute engine that can be scaled manually only.
- Answer: False
Explanation: AWS Fargate can also be automatically scaled using AWS Auto Scaling policies.
True/False: AWS’s Application Auto Scaling can be used to scale non-AWS resources.
- Answer: False
Explanation: AWS’s Application Auto Scaling is meant for scaling resources within the AWS ecosystem only.
Single Select: What is a cooldown period in the context of AWS Auto Scaling?
- A) A time period to cool down the physical servers.
- B) A waiting period before additional scaling activities can start after the previous one.
- C) The time required to terminate EC2 instances.
- D) A period to reduce the cost by turning off unused instances.
Answer: B) A waiting period before additional scaling activities can start after the previous one.
Explanation: A cooldown period is a predefined time frame during which AWS Auto Scaling does not allow additional scaling activities.
Multiple Select: Which AWS services offer built-in scaling features?
- A) AWS Lambda
- B) Amazon Elasticache
- C) Amazon S3
- D) Amazon DynamoDB
Answer: A) AWS Lambda, B) Amazon Elasticache, D) Amazon DynamoDB
Explanation: AWS Lambda, Amazon ElastiCache, and Amazon DynamoDB have built-in scaling capabilities. Amazon S3 is a storage service that can handle high levels of storage automatically, but it is not typically discussed in terms of scaling compute or database instances like the others.
True/False: To enable hibernation for an EC2 instance, you must configure the instance at launch.
- Answer: True
Explanation: Hibernation must be enabled at the time of launching the EC2 instance; it cannot be enabled later.
Single Select: What does AWS Auto Scaling use to determine when to scale out or scale in your application resources?
- A) CPU Utilization
- B) Predefined schedules
- C) Health Check status
- D) All of the above
Answer: D) All of the above
Explanation: AWS Auto Scaling uses various metrics like CPU Utilization, schedules, and health check statuses among other monitoring data to determine the need to scale out or scale in.
Great blog post! The section on auto scaling really helped me understand how to dynamically adjust resources.
I appreciate the detailed explanation on hibernation. Never knew it could save so much on cost.
I’ve been using auto scaling for a while now, but I’m curious about its limitations. Has anyone faced challenges with it?
Hibernation seems great, but how fast is the wake-up process? Can it impact real-time application performance?
Auto scaling has been a lifesaver for our e-commerce site during peak times. Highly recommend!
This post was super helpful. Thanks for sharing!
For manual scaling, what are the typical scenarios where this is preferred over auto scaling?
Does anyone use predictive scaling? How accurate is it?