Optimizing Costs for EC2 in High-Traffic Scenarios?

Optimizing EC2 instance costs for supporting 2000 concurrent users streaming video or audio requires a combination of architecture design, instance selection, and cost-saving strategies. Here are some best practices:

1. Right-Sizing Instances • Analyze Workload: Understand the resource requirements (CPU, memory, bandwidth) for streaming to 2000 users.

2. Use Spot and Reserved Instances • Spot Instances: Leverage spot instances for non-critical, stateless components like batch transcoding or CDN origin servers. Use Spot Fleet or EC2 Auto Scaling to maintain availability. • Reserved Instances or Savings Plans: Purchase reserved instances for predictable workloads to lock in lower hourly costs. • On-Demand: Use on-demand instances only for unpredictable workloads.

3. Implement Auto Scaling • Set up Auto Scaling Groups to dynamically add or remove instances based on user demand. This ensures you're not over-provisioning during low-traffic periods.

4. Leverage Elastic Load Balancing (ELB) • Use Application Load Balancer (ALB) to distribute traffic evenly and optimize resource usage.

5. Content Delivery Network (CDN) Integration • Use Amazon CloudFront to cache and deliver content closer to users, reducing load on EC2 instances and lowering data transfer costs.

6. Enable Instance Scheduling • Schedule instances to shut down during periods of no traffic using instance scheduler tools.

7. Monitor and Optimize • Use AWS Cost Explorer, CloudWatch, and Compute Optimizer to analyze performance and identify underutilized instances. • Continuously refine instance types and adjust reservations based on usage patterns.

Tools to Explore • AWS Spot Advisor: Helps choose the best spot instance types based on availability and pricing trends. • AWS Trusted Advisor: Identifies underutilized resources and cost-saving opportunities. A mix of instance types (on-demand, spot, and reserved) and integration with AWS media services and CloudFront is a cost-effective solution for streaming use cases. Would you like further details on any of these practices?