When to Use Amazon EC2 Auto Scaling Versus AWS Auto Scaling
One of the main benefits of cloud-based infrastructure is the ability to easily scale up and down capacity to meet demand. For AWS users, this can be done through the Amazon EC2 Auto Scaling and AWS Auto Scaling tools.
While both tools offer scaling-related functionality, they are designed for different use cases. Let’s go over the differences between them to help identify the service that best fits your particular situation.
EC2 Auto Scaling
When AWS introduced the EC2 Auto Scaling service in 2009, it pioneered configurable scaling. As the name suggests, it focuses on the Amazon Elastic Compute Cloud (EC2) service and allows users to automatically launch and terminate EC2 instances based on configurable settings.
The most common use case in EC2 Auto Scaling is to configure CloudWatch alarms to launch new EC2 instances when a specific metric exceeds a threshold. For example, a developer can configure Auto Scaling to launch two EC2 instances when the CPU usage is above 50% for five consecutive minutes. Users also configure CloudWatch alarms to reduce the number of EC2 instances, for example, when CPU usage drops to a value considered low usage.
For some applications, developers can also configure EC2 Auto Scaling to launch and terminate instances based on schedules. This is useful for known times of low usage such as nights or weekends.
AWS Auto Scaling, on the other hand, provides a centralized place to manage configurations for a wider range of scalable resources, such as EC2 instances, Amazon Elastic Container Service (ECS), Amazon DynamoDB tables, or Amazon Read Replicas. Relational Database Aurora.
With AWS Auto Scaling, users can keep EC2 Auto Scaling groups within a configurable range of metrics. Developers can configure dynamic DynamoDB read / write capacity units for a specific table, also based on usage. ECS services can be configured to initiate or terminate ECS tasks based on CloudWatch metrics. The same is true for RDS Read Replicas; AWS Auto Scaling can add or stop RDS Read Replicas based on usage.
AWS Auto Scaling introduced the concept of scale plans, which use scaling policies to manage resource usage. Application owners can select a target usage, such as 50% CPU usage, and AWS Auto Scaling will add or remove capacity to meet that goal.
Key Differences Between Amazon EC2 Auto Scaling and AWS Auto Scaling
Overall, AWS Auto Scaling is a simplified option for scaling multiple Amazon cloud services based on usage goals. Amazon EC2 Auto Scaling focuses strictly on EC2 instances to allow developers to configure more detailed scaling behaviors.
Another important distinction is that AWS Auto Scaling focuses on using the target – for example, “Add a certain number of EC2 instances when a particular metric exceeds a threshold” – rather than letting developers configure specific actions. Meanwhile, EC2 Auto Scaling relies on predictive scaling, which uses machine learning to determine the right amount of resource capacity needed to maintain target usage for EC2 instances.
While EC2 Auto Scaling offers more flexibility, AWS Auto Scaling offers simplicity. The choice will come down to the features and capabilities most relevant to the IT team and developers planning to evolve the cloud environment.