When running applications on AWS EC2 instances, managing costs can be challenging, especially as the demand for resources fluctuates. One of the most effective strategies we’ve used to optimize costs and maintain performance for clients is leveraging Auto Scaling Groups (ASGs). By dynamically scaling EC2 instances in response to demand measured by CPU spikes, we’ve been able to achieve significant cost savings while ensuring client applications remain performant and highly available across both development and production environments.
In this article, we will walk through how we use Auto Scaling Groups to lower costs for EC2 instances in two different environments: Development (dev) and Production (prod) for clients. We will cover the strategies used, the configurations in place, and how these optimizations led to cost savings.
An Auto Scaling Group (ASG) allows you to automatically adjust the number of EC2 instances in response to traffic patterns, resource usage, or other defined policies. ASGs work by monitoring a set of EC2 instances and scaling the number up or down depending on demand, helping you avoid over-provisioning and under-utilization of resources.
ASGs are highly customizable with features like:
In the dev environment, the primary goal was to minimize costs while still maintaining scalability for testing, development, and quality assurance. Since the workload is generally lower than in production, we focused on optimizing both instance type and scaling policies.
For dev, we use smaller EC2 instance types that are cost-effective but still capable of handling the workloads during working hours. These smaller instances were able to scale out (i.e., add more instances) as needed, depending on traffic, but would scale down during off-peak hours.
We used a combination of On-Demand and Spot Instances within the ASG to help dynamically scale instances based on CPU usage:
One of the key optimizations in the dev environment was scheduled scaling. We scheduled the EC2 instances to only run between 7 AM and 6 PM, reflecting the working hours when developers were active. Outside of these hours, the instances would be automatically terminated, reducing idle time and cutting costs.
With this configuration, we achieved over 60% cost saving in the dev environment. By utilizing a mix of smaller instances and Spot Instances, combined with the scheduling of EC2 uptime, we ensured that resources were used efficiently while minimizing idle time.
In the prod environment, the focus shifted towards ensuring high availability and performance while still optimizing costs. Applications needed to be up and running at all times, so we couldn’t rely on scheduled scaling the way we did in dev. However, there were still opportunities for flexibility and cost optimization.
For production, we used larger EC2 instances to ensure that the applications could handle higher traffic volumes and provide consistent performance. However, unlike the dev environment, all the instances in prod were On-Demand. This allowed us to have the flexibility to spin up new instances when needed without the risk of Spot Instance interruptions.
The Auto Scaling Group was configured to automatically scale instances up or down based on traffic and resource utilization, ensuring we only paid for what we used. Even though the prod instances were larger and more expensive, the ability to scale dynamically helped balance out costs. During periods of low demand, the Auto Scaling Group would automatically terminate idle instances, reducing overall expenses.
To manage instance replacements during updates, we use the Maintenance Policy within the Auto Scaling Group. This policy determines whether a new instance is launched before or after an existing one is terminated.
In production, we typically use Launch before terminating to maintain uptime, while in dev environments, we prefer Terminate and launch to save costs. By adjusting these settings, we can optimize instance replacements based on the specific needs of each environment.
One of the biggest benefits of using Auto Scaling Groups is the health check feature. The ASG constantly monitors the health of the EC2 instances. If an instance becomes unhealthy or unresponsive, the ASG automatically terminates the problematic instance and launches a new, healthy one to replace it. This self-healing capability ensured high availability and minimized the manual intervention needed.
We integrated the Auto Scaling Group with an Application Load Balancer (ALB) to evenly distribute traffic across the instances. The ALB also handled SSL termination, providing secure communication between clients and the instances. This integration not only helped with performance by distributing traffic efficiently, but also ensured that the application remained highly available, regardless of which instance was handling the traffic at any given time.
Using Auto Scaling Groups in conjunction with EC2 instances allowed the client to balance cost savings with performance across both development and production environments. The combination of smaller and spot instances in dev, scheduled scaling, and the flexibility to scale in production ensured that we could keep costs low while maintaining a high level of service.
By leveraging the power of Auto Scaling Groups, Application Load Balancers, and scheduled scaling policies, AWS provides a powerful, flexible, and cost-effective solution for managing EC2 instances across a variety of use cases. For anyone looking to optimize AWS costs while ensuring scalability and availability, Auto Scaling Groups are a must-use feature.