How does AWS Auto Scaling work with EC2 instances, and how would you configure it to ensure high availability and cost optimization?

Answer:

How AWS Auto Scaling Works with EC2:

AWS Auto Scaling automatically adjusts the number of EC2 instances in your application’s architecture based on defined policies, conditions, or schedules. It ensures your application has the right amount of compute capacity at any given time.

There are two key components involved:

1. Launch Template or Launch Configuration

   • This defines how new EC2 instances should be launched (e.g., AMI ID, instance type, key pair, security groups, etc.).

2. Auto Scaling Group (ASG)

   • A logical group of EC2 instances that are managed together.

   • You define:

     • Minimum, maximum, and desired number of instances.

     • Scaling policies (when and how to scale).

     • Availability Zones and subnets to launch instances in.

Configuring Auto Scaling for High Availability:

1. Multi-AZ Deployment:

   • When creating the Auto Scaling Group, select multiple Availability Zones.

   • This ensures that even if one AZ goes down, your app is still running in another.

2. Health Checks:

   • Enable EC2 and ELB health checks.

   • Auto Scaling will automatically replace unhealthy instances.

3. Elastic Load Balancer (ELB):

   • Attach your ASG to an ELB or Application Load Balancer (ALB).

   • Distributes incoming traffic evenly across healthy instances.

4. Use Launch Templates with Mixed Instance Types (Optional):

   • Support multiple instance types and purchase options (e.g., On-Demand + Spot).

   • Increases resiliency if some instance types are unavailable.

Configuring Auto Scaling for Cost Optimization:

1. Dynamic Scaling Policies:

   • Use CloudWatch metrics (like CPU utilization, memory, or custom metrics).

   • Example: Scale out if CPU > 70% for 5 minutes, scale in if CPU < 30%.

2. Predictive Scaling (Optional):

   • Uses machine learning to forecast demand and proactively scale.

   • Helps reduce sudden overprovisioning.

3. Scheduled Scaling:

   • Define scaling based on known usage patterns (e.g., scale up at 8 AM, scale down at 8 PM).

4. Use Spot Instances with Instance Weighting:

   • Reduce cost by mixing On-Demand and Spot Instances using instance weighting and priorities.

5. Right-size Instances:

   • Use Compute Optimizer or analyze CloudWatch metrics to select cost-efficient instance types.

Example Setup:

• Launch Template: t3.medium instance, AMI for your app, security group allowing HTTP/HTTPS.

• Auto Scaling Group: min=2, max=6, desired=3

• Scaling Policy:

  • Add instance if average CPU > 70% for 5 min

  • Remove instance if average CPU < 30% for 5 min

• Load Balancer: ALB distributing to instances in 2 AZs

• Health Checks: ELB and EC2 checks enabled

• CloudWatch Alarms: For scaling triggers

• Cost Optimizations: Use Spot where acceptable, and schedule scaling during off-peak