A data engineering team is building a new batch processing system that runs once a day for 4 hours. The system uses Amazon EMR clusters, which are configured with EC2 instances. The team wants to minimize compute costs for these predictable, short-duration workloads. Which EC2 purchasing option should they primarily leverage?
- AReserved Instances with a 1-year No Upfront payment option.
- BOn-Demand Instances for the entire 4-hour duration.
- CEC2 Instance Savings Plans with a 1-year commitment.
- DSpot Instances for worker nodes and On-Demand for master nodes.
Show answer & explanationAnswer & explanation
Correct answer: D. Spot Instances for worker nodes and On-Demand for master nodes.
For a short-duration, predictable batch workload, Spot Instances are the most cost-effective for the worker nodes which are typically fault-tolerant. Master nodes, which are critical and not fault-tolerant, should use On-Demand to ensure job completion without interruption. This hybrid approach optimizes cost significantly while maintaining reliability.
Why the other options are wrong
- A. Reserved Instances are for continuous, long-term workloads, not for 4-hour daily runs. The commitment would be wasted for idle time.
- B. On-Demand is the most expensive and doesn't leverage cost savings for this workload type.
- C. Savings Plans provide discounts for consistent compute usage over time, but for a short daily burst, the commitment might not be fully utilized compared to Spot savings.
EC2 Spot Instances for EMR
Leveraging EC2 Spot Instances for Amazon EMR clusters, particularly for worker nodes, can significantly reduce compute costs. This is effective because EMR is designed to be fault-tolerant, allowing for worker nodes to be interrupted and replaced without failing the entire job, especially suitable for batch processing.
- Significant cost savings (up to 90%) for worker nodes.
- EMR's fault tolerance handles Spot interruptions.
- Master nodes typically use On-Demand for stability.
Memory trick: EMR's Spot-on strategy: cheap workers, stable master.