A retail analytics company has deployed an application environment on AWS. The environment consists of the following components:
* A set of legacy data ingestion scripts that run continuously (24/7) on Amazon EC2 instances with stable CPU usage.
* A fleet of EC2 instances running a web application that experiences highly unpredictable traffic peaks throughout the day.
* A PostgreSQL database hosted on Amazon RDS that stores transactional data and operates around the clock.
The company wants to optimize compute costs for this environment with minimal administrative effort. Which purchasing strategy will meet these requirements most cost-effectively?
- Purchase a Compute Savings Plan to cover the EC2 instances, and purchase Amazon RDS Reserved DB Instances for the PostgreSQL database.Cevap
- BPurchase a single Compute Savings Plan with a commitment level high enough to cover both the EC2 instances and the Amazon RDS PostgreSQL database.
- CMigrate the continuous 24/7 data ingestion scripts from EC2 to AWS Lambda to eliminate idle compute costs, and use On-Demand EC2 instances for the web application.
- DMigrate the PostgreSQL database to Amazon DynamoDB configured with Provisioned Capacity Mode to handle the unpredictable transaction peaks, and purchase EC2 Reserved Instances.
Cevap
Purchase a Compute Savings Plan to cover the EC2 instances, and purchase Amazon RDS Reserved DB Instances for the PostgreSQL database.
Purchasing a Compute Savings Plan is the most effective way to cover the EC2 instances since it applies automatically to any instance family, size, or region, accommodating both the stable data ingestion instances and the unpredictable web application instances. Because Amazon RDS is not covered under Compute Savings Plans, purchasing Amazon RDS Reserved DB Instances is the correct and most cost-effective way to reduce the PostgreSQL database's 24/7 running costs.
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Compute Savings Plans vs. Database Reservations
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