3.2.3.2. Capabilities of Auto Scaling for a Variety of AWS Services (EC2 Auto Scaling groups, RDS storage auto scaling, DynamoDB, ECS capacity provider, EKS autoscalers)
First Principle: Automatically adjusting capacity to meet fluctuating demand ensures optimal performance, cost-efficiency, and continuous availability without manual intervention.
Auto scaling embodies the principles of scalability and automation, crucial for resilient cloud architectures.
AWS provides robust auto scaling capabilities across diverse services:
- EC2 Auto Scaling Groups: Dynamically add/remove EC2 instances based on metrics (e.g., CPU). Handles unpredictable traffic spikes, maintaining performance.
- RDS Storage Auto Scaling: Automatically increases database storage capacity. Prevents outages due to insufficient storage, optimizing performance.
- DynamoDB Auto Scaling: Adjusts read/write capacity units (RCUs/WCUs) to meet throughput. Ensures consistent low-latency for high-traffic NoSQL applications.
- ECS Capacity Providers: Manage underlying infrastructure capacity for ECS tasks, integrating with EC2 Auto Scaling. Simplifies container orchestration by ensuring adequate compute resources.
- EKS Autoscalers:
- Cluster Autoscaler: Adjusts worker nodes in an EKS cluster.
- Horizontal Pod Autoscaler (HPA): Scales pods within the cluster based on resource utilization. Dynamically scales Kubernetes workloads to match demand, optimizing resource utilization and cost.
Key Auto Scaling Capabilities across AWS Services:
- Compute (EC2 ASG, ECS/EKS Autoscalers): Dynamically scale instances/pods.
- Storage (RDS, DynamoDB): Automatically increase capacity based on usage.
- Cost Efficiency: Optimize resources, avoid over-provisioning.
- Operational Excellence: Automated, no manual intervention.
Scenario: A DevOps team manages several applications: a web application on EC2 instances, a database on Amazon RDS that occasionally runs out of storage, and a containerized microservice on Amazon ECS with unpredictable traffic. They need to automate scaling for all of them.
Reflection Question: How would you leverage the auto scaling capabilities of EC2 Auto Scaling groups, RDS storage auto scaling, and ECS capacity providers to ensure optimal performance, cost-efficiency, and continuous availability for this diverse set of workloads?
š” Tip: Consider the difference between reactive (metric-based) and proactive (schedule-based or predictive) scaling. How might each be applied to different workloads?