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.
Auto Scaling Groups Overview
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:
- Instance scaling up or down based on load or schedules
- Health checks to automatic instance replacement
- Integration with load balancers for distributing traffic evenly and ensuring high availability
- Rolling updates to ensure zero downtime during upgrades
Dev Environment: Cost Optimization Through Scalability and Scheduling
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.
Instance Type Selection
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.
Scaling Policies
We used a combination of On-Demand and Spot Instances within the ASG to help dynamically scale instances based on CPU usage:
- 1 On-Demand Instance: The first instance is always launched as On-Demand to ensure that we have a baseline instance available.
- 50/50 Mix of On-Demand and Spot Instances: The rest of the instances are split between On-Demand and Spot Instances. This hybrid approach allowed me to maintain flexibility while reducing costs significantly.
Scheduled Scaling
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.
Cost Savings
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.
Prod Environment: Maintaining Performance with Cost Flexibility
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.
Larger Instances for Stability
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.
Auto Scaling and Flexibility
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.
Instance Maintenance Policy for Auto Scaling Groups
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.
- Launch before terminating ensures high availability by provisioning new instances before terminating old ones.
- Terminate and launch is more cost-effective but temporarily reduces capacity during replacement.
- Custom policy allows fine-tuning to balance cost and availability by setting minimum and maximum instance thresholds.
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.
Health Checks and Self-Healing
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.
Load Balancing and SSL Integration
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.
Key Benefits of Using Auto Scaling Groups
- Cost Optimization: By scaling EC2 instances based on demand and utilizing Spot Instances in dev, we were able to significantly reduce costs. The ability to terminate idle instances outside of business hours in dev also helped avoid unnecessary charges.
- Improved Availability: The use of Auto Scaling Groups in prod ensured that the application had an uptime of 98%. Health checks and automatic instance replacement helped maintain uptime.
- Seamless Updates: Rolling updates allowed for smooth application updates with zero downtime, ensuring that the production environment remained stable while receiving necessary patches and improvements.
- Flexibility: The combination of On-Demand and Spot Instances in the dev environment and pure On-Demand instances in prod gave me the flexibility to balance cost and performance appropriately for each environment.
- Automated Management: With launch templates and ASGs, EC2 instance management became automated. The templates ensured that new instances were always launched with the correct configurations, and ASGs took care of scaling, updating, and replacing instances.
- Auto Scaling Group Activity Monitor provides real-time visibility into scaling actions, health checks, instance replacements, and updates, allowing me to track and respond quickly to ensure optimal performance and cost efficiency.
- Three Types of Scaling: Dynamic scaling, which adjusts capacity based on real-time demand; Predictive scaling, which uses historical data to forecast and preemptively adjust capacity; and Scheduled scaling, which allows you to set fixed scaling actions based on specific times or dates.
Conclusion
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.
