A software company is deploying a corporate training platform on AWS. The platform requires a backend service to process employee learning telemetry, which must run continuously hours a day, days a week (). Additionally, the platform stores user progress and quiz results in a database. This database experiences highly unpredictable, sharp spikes in traffic when training modules are assigned to large teams. The company wants to design a highly cost-optimized solution for both compute and database resources. Which combination of services and purchasing strategies will meet these requirements at the lowest cost?
- Run the backend service on AWS Fargate covered by a -year Compute Savings Plan, and use Amazon DynamoDB in on-demand capacity mode for the database.Cevap
- BRun the backend service on AWS Fargate covered by a -year Compute Savings Plan, and use Amazon DynamoDB in provisioned capacity mode for the database.
- CRun the backend service on AWS Lambda, and use Amazon DynamoDB in on-demand capacity mode for the database.
- DRun the backend service on AWS Fargate, and use Amazon RDS for PostgreSQL for the database, covering both the Fargate tasks and the RDS instance under a single -year Compute Savings Plan.
Cevap
Run the backend service on AWS Fargate covered by a -year Compute Savings Plan, and use Amazon DynamoDB in on-demand capacity mode for the database.
Running the backend service on AWS Fargate with a Compute Savings Plan provides significant cost savings for steady-state, continuous compute workloads. Utilizing Amazon DynamoDB in on-demand capacity mode is the most cost-effective database choice because it automatically handles sudden, unpredictable traffic spikes without manual intervention or the need to pay for idle provisioned capacity.
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Anahtar Kavram
Matching compute hosting models and purchasing strategies with workload patterns, and understanding the billing scopes of AWS Savings Plans and DynamoDB capacity modes.