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5.2.1. Scaling Compute (EC2, Lambda, Containers)

šŸ’” First Principle: Scaling compute dynamically adjusts resource capacity for EC2 instances, Lambda functions, and containers, ensuring consistent application performance and cost-efficiency under fluctuating demand.

Scenario: You need to scale a web application that runs on EC2 instances and also has a backend composed of Lambda functions and ECS containers. All components experience unpredictable traffic.

For SysOps Administrators, managing the compute layer's scalability is central to maintaining application performance and controlling costs. AWS offers various services for dynamic scaling.

Key Strategies for Scaling Compute:
  • Amazon EC2 Auto Scaling:
    • Concept: Automatically adjusts the number of EC2 instances in an Auto Scaling Group based on demand (metrics like CPU utilization, network I/O, or custom application metrics).
    • Benefits: Handles unpredictable traffic spikes, maintains performance, optimizes costs by scaling in during lulls.
    • Configuration: Define Launch Templates and Scaling Policies (Target Tracking, Simple/Step, Scheduled).
  • AWS Lambda:
    • Concept: Serverless compute scales automatically in response to event triggers (API Gateway requests, S3 events, DynamoDB Streams).
    • Benefits: Scales from zero to thousands of concurrent executions instantly, pay-per-use billing.
    • Configuration: Managed automatically by AWS; Provisioned Concurrency for latency-sensitive functions.
  • Containers (Amazon ECS, Amazon EKS):
    • Concept: Orchestration services scale the number of running tasks/pods (instances of your containerized application).
    • Benefits: Efficient resource utilization, consistent application delivery.
    • Configuration: ECS Services with Auto Scaling policies, AWS Fargate for serverless containers. Kubernetes Horizontal Pod Autoscaler for EKS.

āš ļø Common Pitfall: Not configuring appropriate scaling policies (e.g., only scaling out, not scaling in), leading to over-provisioning and unnecessary costs.

Key Trade-Offs: Granular control (EC2) versus operational simplicity and automatic scaling (Lambda, Fargate).

Reflection Question: How does dynamically scaling compute resources across EC2 Auto Scaling Groups, Lambda functions, and ECS containers (e.g., with Fargate) fundamentally ensure consistent application performance and cost-efficiency under fluctuating demand?