VividArchive is migrating its video digitization and rendering platform to AWS. The platform has two primary workloads:
1. A continuous, predictable digitization process that runs 24/7 to archive historical tapes.
2. Sudden, unpredictable requests from news agencies for high-definition rendering, which requires massive compute capacity for brief periods.
Which two strategies will help the company minimize its Total Cost of Ownership (TCO) by aligning AWS billing models with these workload characteristics? (Select TWO.)
- Deploying the digitization workload on Amazon EC2 instances covered by a Savings Plan to benefit from commitment-based discountsAnswer
- Scaling the rendering capacity dynamically using Amazon EC2 Auto Scaling and On-Demand instances to match peak demandsAnswer
- CPurchasing On-Demand instances with a five-year upfront payment to secure the lowest rates for the unpredictable rendering spikes
- DTightly coupling the digitization and rendering services onto a single high-capacity EC2 instance to minimize cross-service networking fees
- EProvisioning a fixed fleet of instances sized to the historical peak demand of rendering requests to guarantee zero latency
Answer
Deploying the digitization workload on Amazon EC2 instances covered by a Savings Plan, and scaling the rendering capacity dynamically using Amazon EC2 Auto Scaling and On-Demand instances.
The correct strategies leverage the core cloud economics principles of elasticity and commitment-based pricing. The baseline, predictable tape digitization workload runs continuously, which makes it a perfect candidate for Savings Plans or Reserved Instances to lower the cost per hour. Conversely, the unpredictable spikes in video rendering demands are best handled through dynamic scaling using On-Demand instances, ensuring the company only pays for compute resources when they are actively processing requests.
Step-by-Step Solution
Key Concept
Matching pricing models and elasticity to workload predictability
Estimated Time:1m 30s