A healthcare SaaS company runs a medical imaging archiving workload in a dedicated member … — AWS Certified Solutions Architect - Professional

A healthcare SaaS company runs a medical imaging archiving workload in a dedicated member account of an AWS Organization. The architecture consists of the following components:

- A fleet of Amazon EC2 instances running inside an Auto Scaling group behind an Application Load Balancer across three Availability Zones. The instances are currently of type `c5.xlarge` (which provides $4$ vCPUs and $8$ GiB of memory). Over the past 90 days, CloudWatch metrics show average CPU utilization is at $18\%$ , while memory utilization consistently peaks at $85\%$ .
- An Amazon RDS for PostgreSQL database instance (`db.r5.8xlarge` with $32$ vCPUs and $256$ GiB of memory) configured in a Multi-AZ deployment. Database CPU utilization averages $8\%$ and write throughput is low.
- Several AWS Lambda functions used for processing metadata, triggering dynamically throughout the day.

Consolidated billing is managed from the management account. The company wants to optimize costs while ensuring no degradation in performance, durability, or availability.

Which combination of recommendations will achieve the greatest cost optimization? (Select TWO.)

Modify the Auto Scaling group launch template to use `m6g.large` instances, which provide $2$ vCPUs and $8$ GiB of memory, and recompile the application for the Graviton architecture.Answer
Purchase Compute Savings Plans in the AWS Organizations management account to maximize discount coverage across the EC2 instances in the member account and the Lambda functions.Answer
C
Purchase EC2 Instance Savings Plans in the member account for the C5 instance family to ensure the discounts are strictly locked to the application instances and cover the Lambda functions.
D
To reduce NAT Gateway costs in the member account, deploy a single NAT Gateway in one Availability Zone and update the route tables of the private subnets across all Availability Zones to route outbound internet traffic through this single NAT Gateway.
E
Consolidate outbound traffic by sharing subnets using AWS Resource Access Manager (RAM) with external third-party partner accounts outside the AWS Organization to route traffic through a single NAT Gateway, without enabling sharing with external entities in the RAM settings.

Answer

The correct recommendations are to modify the Auto Scaling group launch template to use `m6g.large` instances (requiring recompilation for Graviton) and to purchase Compute Savings Plans in the AWS Organizations management account.

The combination of using `m6g.large` instances and purchasing Compute Savings Plans is correct because it addresses the mismatched resource consumption (low CPU, high memory) of the C5 instances by migrating to a more cost-effective instance family with equivalent memory capacity. In addition, Compute Savings Plans provide the flexibility required to cover both the EC2 instance workloads and the AWS Lambda functions, and purchasing them in the management account enables sharing the discount benefits across all member accounts under consolidated billing.

Step-by-Step Solution

Analyze the EC2 CPU and memory utilization metrics.

CPU utilization is

18\%

4\text{ vCPUs} = 0.72\text{ vCPUs}

. Memory utilization peaks at

85\%

8\text{ GiB} = 6.8\text{ GiB}

This establishes that the workload is memory-bound and does not require

4

vCPUs. An instance with

2

vCPUs and

8

GiB of memory (such as `m6g.large`) is a better fit.

Evaluate the discount plans for compute workloads including serverless.

Compute Savings Plans cover both EC2 and Lambda compute usage and apply regardless of instance family changes.

This guarantees that the discounts will persist even after the migration from C5 to M6g instances, unlike EC2 Instance Savings Plans which are locked to a specific instance family.

Key Concept

Right-sizing instance configurations based on active utilization metrics and applying flexible Savings Plans at the organization level.

Alternative Method

Instead of manual resizing, AWS Compute Optimizer could be used to analyze historical utilization patterns and automatically suggest the optimal Graviton-based instance types.

Estimated Time:2m 0s

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Answer

Step-by-Step Solution

Key Concept

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Alternative Method

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