SAA-C03 Design Cost-Optimized Architectures Practice Test 10 — 15 Questions

Question 1

A company runs a SaaS application with highly unpredictable database load — it may receive zero queries for hours, then spike to thousands of queries per second briefly. The company wants to minimize database costs while handling all load levels without manual scaling. Which solution is MOST cost-effective?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Amazon Aurora Serverless v2 — scales automatically from minimum capacity during idle to maximum during spikes. Amazon Aurora Serverless v2 automatically scales database capacity based on actual load. It scales from a minimum of 0.5 ACUs during quiet periods to up to 128 ACUs during spikes within seconds. You pay only for the ACUs consumed — idle periods cost near-minimum.

Aurora Provisioned requires pre-provisioning capacity for peak load, incurring full instance costs regardless of actual utilization. Even with Auto Scaling, the primary instance has a minimum provisioned capacity that runs at full cost during idle periods.

Answer

Amazon Aurora Provisioned with Auto Scaling to add and remove read replicas

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Amazon RDS MySQL with scheduled stop/start to save costs during predictable off-hours

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Amazon DynamoDB with on-demand capacity mode — scales to any traffic level with no minimum cost

Question 2

A company runs a web application on Amazon EC2 instances behind an Application Load Balancer. The workload is predictable during business hours but has low usage at night. Which three options can reduce costs without compromising performance? (Choose three.)

Accepted Answer

Purchase Compute Savings Plans to cover the baseline EC2 usage during business hours.. To reduce costs without compromising performance for a web application with predictable peak and low usage:
1.  **Scheduled Auto Scaling:** Configuring a scheduled Auto Scaling policy allows you to automatically reduce the number of EC2 instances during known off-peak hours (e.g., nights and weekends) and scale them back up for business hours. This directly reduces hourly instance costs when demand is low without impacting performance during peak times.
2.  **Dynamic Scaling based on CPU Utilization:** Implementing a dynamic scaling policy (e.g., target tracking based on CPU utilization) ensures that the EC2 fleet automatically scales in when demand (and thus CPU usage) is low, and scales out when demand increases. This right-sizes the fleet to current needs, optimizing costs while maintaining performance.
3.  **Compute Savings Plans:** Purchasing Compute Savings Plans provides significant discounts on EC2 usage (and other compute services) in exchange for a 1- or 3-year commitment to a consistent spend. This is ideal for covering the predictable baseline workload during business hours, reducing the effective hourly cost of those instances without affecting their performance or availability.

Answer

Use EC2 Spot Instances for the entire workload to achieve the lowest possible cost.

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Replace the Application Load Balancer with a Network Load Balancer, which is cheaper per hour.

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Use a single large EC2 instance to handle all traffic, reducing the number of running instances.

Question 3

A company is using AWS for big data analytics and wants to optimize costs for its data processing pipeline. Which three design choices will help achieve this goal? (Choose three.)

Accepted Answer

Use Amazon EMR with Spot Instances for task nodes to reduce compute costs for fault-tolerant jobs.. Using Amazon EMR with Spot Instances for task nodes is correct because task nodes are typically used for fault-tolerant, stateless processing in EMR clusters. Spot Instances offer significant cost savings (up to 90% compared to On-Demand) and can be interrupted, but since task nodes can be replaced without affecting job completion, this is a cost-optimized design for big data pipelines. Amazon S3 Select is correct because it allows you to retrieve only a subset of data from an object (e.g., specific columns or rows) using SQL expressions, reducing the amount of data transferred to your processing application and lowering data transfer and processing costs. Using AWS Glue with a scheduled crawler and choosing a lower number of DPUs for smaller jobs is correct because DPUs (Data Processing Units) are the billing unit for AWS Glue jobs; selecting a lower DPU count for jobs that do not require high parallelism directly reduces costs.

Answer

Store all intermediate data on Amazon EBS io2 Block Express volumes for high performance.

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Store all data in Amazon Redshift Spectrum external tables to avoid loading data into Redshift clusters.

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Provision a fixed number of EC2 instances for processing to avoid scaling delays.

Question 4

A company is running a stateful web application on EC2 instances that processes user uploads. The architecture currently uses a Multi-AZ deployment for high availability. Which three cost-optimization strategies can be applied without sacrificing high availability? (Choose three.)

Accepted Answer

Use EC2 Auto Scaling with a mixed instances policy that includes Spot Instances for the stateless web tier, while using On-Demand for the stateful tier.. Storing uploaded files in Amazon S3 and using S3 Transfer Acceleration for uploads removes the need for local storage on EC2 instances, reducing storage costs and eliminating the cost of managing EBS volumes. This strategy does not affect high availability because S3 is inherently highly available and durable across multiple Availability Zones. Transfer Acceleration optimizes upload speed over the public internet without impacting the availability of the application.

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Use an Amazon ElastiCache cluster in a single Availability Zone to reduce costs.

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Replace Multi-AZ EC2 with a single-AZ deployment to reduce data transfer costs.

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Implement a NAT Gateway in each Availability Zone for outbound traffic to reduce data transfer costs.

Question 5

A company is designing a cost-optimized serverless architecture using AWS Lambda for a data processing workload. The workload runs multiple times per day and processes files up to 500 MB. Which three design decisions will help minimize costs? (Choose three.)

Accepted Answer

Use Amazon S3 batch operations to invoke Lambda functions in parallel, reducing overall processing time.. Optimizing the Lambda function code to reduce execution duration directly lowers costs because AWS Lambda pricing is based on the number of requests and the duration of code execution, measured in GB-seconds. By writing efficient code, you reduce the compute time, which minimizes the billable GB-seconds. Storing processed output in S3 Standard-IA is cost-effective for infrequently accessed data, as it offers lower storage costs than S3 Standard while still providing high durability and availability. Using S3 batch operations to invoke Lambda functions in parallel reduces the overall processing time by distributing the workload across multiple concurrent invocations, which can lower the total compute duration and thus the cost.

Answer

Deploy Lambda functions in multiple Regions to reduce latency for global users.

Answer

Use Lambda Provisioned Concurrency to ensure zero cold starts, improving performance.

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Allocate the maximum memory (10,240 MB) to each Lambda function to reduce execution time.

Question 6

A data analytics company stores large datasets in Amazon S3. The data is accessed frequently for the first 30 days, then accessed rarely but needs to be retrievable within 1 hour for compliance purposes for up to 3 years. After 3 years, the data must be archived for 7 years with retrieval times acceptable up to 12 hours. Which three of the following strategies would optimize storage costs? (Choose three.)

Accepted Answer

Use S3 Intelligent-Tiering for automatic cost savings based on access patterns.. The optimal cost-optimization strategy involves using S3 Intelligent-Tiering to automatically move objects between access tiers based on changing patterns, saving costs without manual lifecycle rules. Additionally, transition objects to S3 Standard-IA after 30 days to match reduced access frequency, and use a lifecycle policy to move objects to S3 Glacier Deep Archive after 3 years to meet the 12-hour retrieval requirement for the final 7-year archive. These three strategies optimize storage costs effectively.

Answer

Transition data to S3 Glacier Deep Archive immediately after upload.

Answer

Store all data in S3 One Zone-IA for the first 30 days to save on storage costs.

Question 7

Order the steps for setting up an Application Load Balancer with an EC2 target group.

Accepted Answer

Step 1: Create Application Load Balancer; Step 2: Create target group; Step 3: Configure health checks; Step 4: Register EC2 instances; Step 5: Test the load balancer. The correct sequence for setting up an Application Load Balancer with an EC2 target group is: first create the ALB to define listeners, then create a target group to handle traffic routing, configure health checks to monitor instance health, register EC2 instances into the target group, and finally test the load balancer to ensure proper operation. This order ensures all dependencies are met and follows AWS best practices.

Answer

Step 1: Create target group; Step 2: Create Application Load Balancer; Step 3: Configure health checks; Step 4: Register EC2 instances; Step 5: Test the load balancer

Answer

Step 1: Create Application Load Balancer; Step 2: Register EC2 instances; Step 3: Create target group; Step 4: Configure health checks; Step 5: Test the load balancer

Answer

Step 1: Create Application Load Balancer; Step 2: Configure health checks; Step 3: Create target group; Step 4: Register EC2 instances; Step 5: Test the load balancer

Question 8

Order the steps to set up an Amazon CloudFront distribution with an S3 origin.

Accepted Answer

Step 1: Create an S3 bucket. Step 2: Create a CloudFront distribution. Step 3: Configure cache settings. Step 4: Create an Origin Access Identity (OAI). Step 5: Update the S3 bucket policy.. S3 bucket first, then CloudFront distribution, cache settings, OAI creation, and bucket policy update.

Answer

Step 1: Create an S3 bucket. Step 2: Create a CloudFront distribution. Step 3: Create an Origin Access Identity (OAI). Step 4: Configure cache settings. Step 5: Update the S3 bucket policy.

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Step 1: Create an S3 bucket. Step 2: Create an Origin Access Identity (OAI). Step 3: Update the S3 bucket policy. Step 4: Create a CloudFront distribution. Step 5: Configure cache settings.

Answer

Step 1: Create a CloudFront distribution. Step 2: Create an S3 bucket. Step 3: Configure cache settings. Step 4: Create an Origin Access Identity (OAI). Step 5: Update the S3 bucket policy.

Question 9

CloudWatch metrics show your EC2 instances have average CPU utilization around 10% with stable performance over several weeks. The application does not require additional headroom right now. What is the most effective cost-optimization action?

Accepted Answer

Right-size the instances to a smaller size that matches the observed utilization. Right-sizing EC2 instances to match observed utilization is the most effective cost-optimization action because the current instances are over-provisioned (average CPU at 10%). By selecting a smaller instance type that aligns with the actual workload, you reduce hourly costs without impacting performance, as the application has stable behavior and no need for headroom.

Answer

Increase the Auto Scaling desired capacity to add more instances

Answer

Switch to Spot Instances immediately even though interruptions would impact users

Answer

Disable detailed monitoring to reduce CPU usage from the monitoring agent

Question 10

A marketing site serves versioned JavaScript and CSS files from Amazon S3 through CloudFront. The origin bill is rising because CloudFront keeps fetching the same files too often, and the application never changes a file at the same URL once it is published. Which two changes should you make? Select two.

Accepted Answer

Set long-lived Cache-Control headers, such as a high max-age and immutable policy, on the versioned assets.. Setting long-lived Cache-Control headers (e.g., `max-age=31536000` and `immutable`) on versioned assets tells CloudFront and browsers to cache the files aggressively. Since the application never changes a file at the same URL, this eliminates redundant origin fetches, directly reducing the origin bill.

Answer

Move the static assets to an EC2 web server behind an Application Load Balancer.

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Disable CloudFront caching so every request always reaches the origin.

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Add more viewer-facing headers to the cache key so each browser variation gets a unique cached object.

Question 11

A company has a steady, predictable workload that must run continuously (24/7) in a single AWS Region. The team wants the lowest cost option available for this steady usage, but also expects they may choose different EC2 instance families in the future (without re-buying compute discounts). Which AWS purchase option best meets these goals?

Accepted Answer

Compute Savings Plans, committed for a 1- to 3-year term in the Region. Compute Savings Plans offer the lowest cost for steady, predictable workloads while providing instance family flexibility within a Region. Unlike Reserved Instances, they automatically apply discounts to any EC2 instance family (and even Fargate/Lambda) in the chosen Region, so the company can switch instance families in the future without losing the discount. A 1- or 3-year commitment yields significant savings (up to 66%) compared to On-Demand, making it the optimal choice for this scenario.

Answer

On-Demand Instances only, because they automatically adjust to future needs

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Standard Reserved Instances tied to a single instance type and Availability Zone

Answer

EC2 Spot Instances, because they are always cheaper than savings programs

Question 12

A line-of-business application runs on EC2 instances 24/7 with predictable usage for the next year. The application will stay in the same Region, and the team does not want to manage capacity interruptions. Which two purchase options can reduce cost compared with pure On-Demand pricing? Select two.

Accepted Answer

Buy Compute Savings Plans for the expected steady usage.. Compute Savings Plans (A) offer a flexible discount (up to 66%) in exchange for a 1- or 3-year commitment to a consistent amount of compute usage (measured in $/hour), automatically applying to any EC2 instance family, region, or even AWS Fargate/Lambda. This reduces cost compared to On-Demand while avoiding capacity interruptions, as the commitment covers the predictable steady-state usage. Standard Reserved Instances (B) provide a similar discount (up to 72%) for a specific instance family in a specific region, also with a 1- or 3-year term, and guarantee capacity for the specified AZ if you choose a zonal reservation, ensuring no interruptions.

Answer

Move the fleet to Spot Instances.

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Use Dedicated Hosts to reserve physical servers for the application.

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Stay entirely on On-Demand Instances because they are already the cheapest option.

Question 13

A photo studio stores original project archives in Amazon S3. Objects are read heavily for 14 days after upload, occasionally during the next 11 months, and almost never after one year. The team wants the lowest storage cost while keeping retrieval within minutes during the first year. Which three actions are best? Select three.

Accepted Answer

Keep new objects in S3 Standard for the first 14 days.. A is correct because S3 Standard is designed for frequently accessed data with low latency and high throughput, making it ideal for the first 14 days when objects are read heavily. After this period, transitioning to S3 Standard-IA reduces storage costs while still providing millisecond retrieval for occasional access during the next 11 months.

Answer

Transition objects to S3 Glacier Flexible Retrieval after 14 days.

Answer

Disable versioning to make the lifecycle rules work correctly.

Question 14

A company processes product-image uploads in bursts. Each transform takes up to ten minutes, and every job can be retried safely from the beginning. The current EC2 worker fleet is idle most of the day. Which two changes most reduce cost and idle capacity? Select two.

Accepted Answer

Buffer jobs in Amazon SQS and let workers scale from queue depth.. Amazon SQS decouples the bursty upload workload from the worker fleet. By using SQS queue depth as the metric for an Auto Scaling policy, workers scale up only when jobs are waiting and scale down to zero during idle periods, eliminating wasted capacity. This directly reduces cost by matching compute resources to actual demand.

Answer

Keep a fixed fleet of m6i.large instances in an Auto Scaling group with a higher minimum.

Answer

Use Reserved Instances for the workers even though demand is highly bursty.

Answer

Process uploads only during a nightly window so the fleet looks busier.

Question 15

A SaaS vendor has a steady 24/7 control plane on ECS and several small event-driven tasks that currently run on a separate always-on service. Management wants the billing discount that applies across both ECS and Lambda usage without committing to a specific instance family. Which two actions are best? Select two.

Accepted Answer

Buy a Compute Savings Plan for the predictable baseline usage.. A Compute Savings Plan offers the largest discount (up to 66%) across both ECS and Lambda usage without committing to a specific instance family, which matches the requirement to cover both services flexibly. It applies to any EC2 instance, including those used by ECS, and to AWS Lambda compute, making it ideal for a mixed workload with a predictable baseline.

Answer

Buy an EC2 Instance Savings Plan tied to one instance family for all workloads.

Answer

Use Spot Instances for the control plane because it is the largest bill.

Answer

Increase the ECS desired count so Lambda can be removed.