AWS EC2 Auto Scaling: The Basics, Components, and Best Practices
Whether you’re growing rapidly or the business has declined, no matter the case, there are numerous aspects to consider. And, one of the most important is your cloud infrastructure or your computing needs. Reconfiguring the cloud computing capacity to your requirements is hectic, too much time, effort, and money are the mandates. But, Amazon Web Services offer a systematic approach to this challenge.
For AWS users, this can be done through Amazon EC2 Auto Scaling. One of the major benefits of cloud-based infrastructure is the simplicity with which capacity can be dynamically increased and decreased to meet demand. Let’s dive deeper in order to understand Amazon EC2 Auto Scaling and its processing capabilities.
What is Amazon EC2 Auto scaling?
Amazon EC2 Auto Scaling is the capability that allows its users to ensure the appropriate number of EC2 instances are being allocated to the cloud computing needs in order to handle the load of the program. Basically, during hours when the computing needs are low i.e night time and off-season, Auto Scaling allows you to automatically scale down and during hours when the computing needs are high, it scales up accordingly. With the help of Auto-Scaling, you can choose the exact number of EC2 instances needed to deliver a satisfactory level of performance for your application without over-provisioning capabilities or paying needless fees. This enables you to keep expenses down while the demand is low and ramp up resources when the demand is high to maintain application performance. Helping you save A LOT of bucks!
What are the Components of EC2 Auto scaling?
The three components of Amazon EC2 Auto scaling define the three aspects i.e. what, where, and when.
Here are the details:
- Configuration templates
This component defines WHAT will be launched by the auto scaler. As a configuration template for such EC2 instances, your organization can utilize a launch template and perhaps a launch configuration. For your instances, you can specify details like the AMI ID, instance type, key pair, private networks, as well as block device mapping.
This component defines WHERE will the autoscaling take place. Basically, defining which VPC and subnets to use, the load balancer, as well as the minimum and the maximum number of EC2 instances. Your EC2 instances are grouped to enable scaling and administration by treating them as logical units. You can select the minimum, maximum, as well as desired number of EC2 instances when creating an AWS EC2 auto scaling group. Exploring the Auto Scaling groups will help you find several additional features in detail.
- Scaling options
This component defines WHEN autoscaling takes place. You can scale your Auto Scaling groups in several ways with AWS EC2 Auto Scaling. For example, users can set up a group to scale depending on a timetable or when certain circumstances are met for dynamic scaling.
Process: How does EC2 Auto Scaling work?
Auto Scaling groups are groups of EC2 instances that you build. Each group has a minimum number of instances that can be specified, and Amazon EC2 Auto Scaling makes sure that your group never falls below this amount. Each Auto Scaling group has a maximum number of instances that can be specified, and AWS EC2 Auto Scaling makes sure that your group never exceeds this amount. As the demand for your application rises or falls, AWS EC2 Auto Scaling can deploy or terminate instances provided scaling policies are specified to scale up and down.
The process of EC2 Auto Scaling can be carried out through:
Scaling Down: A user, a scaling policy or a scheduled event – one of these three tends to eliminate the instance according to the guidelines. This scales down the computing needs.
Scaling Up: A user, a scaling policy or a scheduled event – one of these three tends to add the instance according to the guidelines. And, the instance remains active until any of the above “Scaling Down” events occurs.
Top AWS EC2 Auto Scaling Best Practices
Following are the top AWS EC2 Auto Scaling best practices that you can follow to improvise the proceedings:
- The concept of Amazon EC2 Auto Scaling is based on load metrics with a one-minute frequency. This makes it possible to react to modifications in application usage more quickly. Response times are slowed when a scaling measure is used, and scaling responses based on outdated data are probable.
- Check for Auto Scaling Group Health. Make sure the health check feature is set up properly to identify operational EC2 instances associated with an Auto Scaling group. Otherwise, an Auto Scaling group is unable to carry out fundamental tasks like replacing failed instances.
- To prepare for future capacity, predictive scaling uses workload predictions. The accuracy of predictions will be improved if workloads exhibit a cyclical performance pattern. To assess the accuracy of the forecasts and scaling actions the policy delivers, try running anticipatory scaling in “forecast only” mode. Set the policy to “forecast and scale” if you are pleased with the predictions.
- Make absolutely sure your Auto Scaling group is set up to deliver email notifications on scale-up or scale-down events if you don’t have any other monitoring tools for Auto Scaling. When alerts are turned on, an AWS SNS topic linked to the auto scaling group gets notices of scaling events and sends them to the email address you provided during setup.
How nOps can help you improve AWS EC2 Auto Scaling
Every saving game in the cloud computing space starts and ends with appropriately analyzing the cloud cost. Where, when, and how your cloud instances are being spent, is the only and most important strategy for optimizing the costs; all other strategies come later. Even with the AWS EC2 Auto Scaling, one won’t be able to proceed in the right way without analyzing the daily cloud needs and the three Ws i.e. when, where, and why.
And, to help you with the smoothest analytics and insights into your cloud computing needs, nOps Amazon Web Services helps you integrate your AWS service with the cost optimization models. Plus, the sorted version of daily data is pure bliss amidst the chaotic dashboards, CSVs, and excels of AWS data centers. Furthermore, even if the chosen pricing model is not helping you save appropriately, with our ShareSave solution you can consolidate cloud accounts into a single pricing model and offer ongoing visibility to change requests. This helps you easily manage cloud costs and save more money.