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Zorluk: OrtaCost-Optimized Compute Selection and Purchasing Strategies

An enterprise runs a containerized web application on Amazon Elastic Container Service (Amazon ECS) with AWS Fargate. The application consists of two main microservices:

1. A core transactional service that runs continuously 24/724/7 and requires a stable baseline of 88 tasks.
2. A non-urgent data processing worker service that processes jobs from an Amazon SQS queue. The workload for this worker service is highly unpredictable, can be delayed if necessary, and the application code is designed to tolerate task interruptions.

The application database is hosted on Amazon RDS for MySQL.

Which two strategies should a solutions architect recommend to minimize compute costs for this architecture? (Select TWO.)

  1. Purchase a Compute Savings Plan to cover the baseline Fargate tasks running the core transactional service.Cevap
  2. Use AWS Fargate Spot capacity providers to run the tasks for the non-urgent data processing worker service.Cevap
  3. C
    Purchase a Compute Savings Plan to cover both the Amazon ECS tasks and the Amazon RDS database instances.
  4. D
    Migrate the continuously running core transactional service to AWS Lambda to eliminate idle task costs.
  5. E
    Use AWS Cost Explorer reports monthly to reactively scale down the background worker service tasks during traffic spikes.

Cevap

Purchase a Compute Savings Plan to cover the baseline Fargate tasks running the core transactional service, and use AWS Fargate Spot capacity providers to run the tasks for the non-urgent data processing worker service.
To achieve a cost-optimized compute architecture on AWS Fargate, steady-state baseline workloads should leverage Compute Savings Plans, which offer significant discounts in exchange for a commitment to a consistent amount of compute usage. For interruption-tolerant, non-urgent workloads, AWS Fargate Spot is the most cost-effective option as it provides spare capacity at a steep discount.

Adım Adım Çözüm

1
Analyze compute requirement profiles.
The core transactional service requires a continuous baseline of 88 tasks, while the data processing service is unpredictable and interruption-tolerant.
Identifying the stability and tolerance of workloads dictates the appropriate compute purchasing models.
2
Select the cost-optimized purchasing strategy for baseline tasks.
Commitment-based Compute Savings Plans are selected to cover the core Fargate tasks.
Compute Savings Plans provide significant discounts compared to On-Demand rates for steady-state workloads and apply to AWS Fargate.
3
Select the cost-optimized purchasing strategy for unpredictable, interruption-tolerant tasks.
AWS Fargate Spot capacity provider is selected.
Fargate Spot provides up to a 70%70\% discount for workloads that can handle interruptions, matching the characteristics of the worker service.

Anahtar Kavram

Selecting cost-optimized compute purchasing strategies (Compute Savings Plans for steady-state Fargate workloads and AWS Fargate Spot for interruption-tolerant, non-urgent workloads).
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Cost-Optimized Compute Selection and Purchasing Strategies