Building on our AWS Application Load Balancer (ALB) exploration, this article dives into AWS Auto Scaling Groups (ASG), a vital technology for dynamically scaling your application in response to varying loads. This guide will demonstrate setting up an ASG that integrates seamlessly with the previously configured ALB, ensuring efficient traffic management and cost-effective scalability.

Understanding Auto Scaling Groups

AWS Auto Scaling Groups manage load variations by adjusting the number of Amazon EC2 instances. Key benefits of ASGs include:

  • Scalability: Automatically scales out to meet increasing loads and scales in when demands decrease.
  • Resilience: Maintains a defined minimum and maximum number of instances, replacing any that fail or are terminated.
  • Load Distribution: Registers new instances to load balancers to ensure even traffic distribution.
  • Operational Continuity: Recreates EC2 instances to guarantee continuous service availability.

Types of Scaling Policies

ASGs support various scaling policies tailored to different operational needs:

  • Dynamic Scaling: Adapts in real-time to changing performance metrics.
    • Target Tracking: Simplifies setting up by maintaining a specific metric level, like keeping CPU utilization at 40%.
    • Step Scaling: Adjusts the number of instances in steps based on selected CloudWatch alarm metrics.
    • Scheduled Scaling: Anticipates and adjusts capacity based on known future events, enhancing readiness for predictable traffic increases.
  • Predictive Scaling: Uses machine learning to forecast future traffic and schedule appropriate scaling actions, enhancing your ability to handle predictable load changes.

Important Metrics and Cooldowns for Scaling

Before diving into the hands-on setup, it’s crucial to understand the metrics used for scaling and the concept of scaling cooldowns:

  • Good Metrics to Scale On:
    • CPUUtilization: Monitors average CPU utilization across your instances, ideal for compute-intensive applications.
    • RequestCountPerTarget: Ensures the number of requests per EC2 instance remains stable, indicating even load distribution.
    • Average Network In/Out: Important if your application is network-bound and traffic volume directly impacts performance.
    • Custom Metrics: AWS CloudWatch allows the pushing of custom metrics that can be tailored to specific needs of your application.
  • Scaling Cooldowns:
    • After a scaling activity, ASGs enter a cooldown period (default 300 seconds) during which no additional scaling activities are initiated. This pause allows metrics to stabilize after the scaling event.
    • Advice: Utilize a ready-to-use AMI to decrease configuration time, enabling faster request servicing and shorter cooldown periods.

Hands-On: Configuring Auto Scaling with ALB

Let’s apply these concepts practically by setting up a simple/step scaling policy based on CPU utilization. We’ll increase capacity when CPU usage exceeds 50% and decrease when it falls below 20%. We’ll also use a tool to artificially stress the CPU and demonstrate the scaling process.

Step 1: Create a Launch Template

First, create a launch template for your ASG. This template includes:

  • AMI and Instance Type: Specifies the base image and size of the EC2 instances.
  • EC2 User Data: Scripts for initial configuration.
  • Security Groups, SSH Keys, and IAM Roles: Ensures secure and authorized access.
  • Networking Details: Subnet and VPC settings for network connectivity.

Step 2: Establish the Auto Scaling Group

Next, establish the ASG:

  • Link to ALB and Target Group: Connect your ASG to the previously set up ALB to maintain traffic management continuity.
  • Define Scaling Policies: Implement the step scaling policy based on CPU utilization. Configure CloudWatch alarms to trigger these policies.

Step 3: Simulate Load and Monitor Scaling

Using a stress tool, simulate high CPU usage to trigger your scaling policies. Monitor the ASG’s response to ensure it scales out and in as expected.

Conclusion and Next Steps

Integrating AWS Auto Scaling Groups with ALB not only ensures your application adapts to load changes but also maintains efficiency and service availability. This setup positions you to effectively manage application demands while optimizing costs.

Next Steps: Explore further scalability strategies within AWS, such as incorporating additional predictive and dynamic scaling policies based on other metrics like network traffic or custom application metrics.