SAA-C03 Design High-Performing Architectures Practice Test 9 — 15 Questions

Question 1

Based on the exhibit, which EBS volume type should the team use to meet the performance need at lower cost than overprovisioning capacity?

Accepted Answer

Use gp3 and provision the needed IOPS independently of volume size.. The team needs to meet performance requirements at lower cost than overprovisioning capacity. gp3 allows you to provision baseline performance of 3,000 IOPS and 125 MiB/s throughput for any volume size, and you can independently increase IOPS up to 16,000 and throughput up to 1,000 MiB/s without needing to increase volume size. This avoids the cost of overprovisioning large gp2 volumes to achieve higher IOPS, which are tied to volume size (3 IOPS per GiB).

Answer

Use sc1 because it is optimized for infrequent access and large objects.

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Use st1 because it provides high throughput for streaming data.

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Use standard magnetic storage because it is compatible with all EC2 instances.

Question 2

An ECS service runs on EC2 capacity. During peak traffic, tasks frequently wait for available container instances. The team wants faster scale-out for the underlying EC2 capacity when tasks increase. What is the best first architectural step?

Accepted Answer

Use an ECS capacity provider (or Auto Scaling integration) to scale the EC2 instances based on ECS demand.. An ECS capacity provider (or Auto Scaling integration) directly links ECS task-level demand to EC2 instance scaling. When tasks are pending due to insufficient container instances, the capacity provider triggers a scale-out event on the Auto Scaling group, adding EC2 instances to accommodate the workload. This is the most efficient architectural step to reduce placement delays during peak traffic.

Answer

Tune the container health check settings so tasks stop failing and stay running.

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Pin all tasks to a single Availability Zone to reduce placement overhead.

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Switch the tasks to run only on Fargate so EC2 scaling is no longer relevant.

Question 3

A system uses multiple AWS Lambda functions behind different event sources. One Lambda occasionally spikes and causes other Lambdas to be throttled due to shared concurrency limits. Which setting best helps ensure the important Lambda keeps capacity during spikes?

Accepted Answer

Set Reserved Concurrency for the important Lambda function.. Reserved Concurrency guarantees a set number of concurrent executions for a specific Lambda function, isolating it from the account-level concurrency pool. This ensures that the important function always has capacity available, even when other functions spike and consume the shared pool. Without this setting, all functions compete for the same 1,000 concurrent executions (default regional limit), and a spike in one can throttle others.

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Increase the function timeout so throttling is less likely.

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Enable Provisioned Concurrency for every Lambda in the account.

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Reduce the number of IAM policies attached to the Lambda roles.

Question 4

Based on the exhibit, which Amazon EFS performance mode is the best fit for this workload?

Accepted Answer

Use General Purpose performance mode for low-latency access.. The General Purpose performance mode is the best fit for this workload because it provides the lowest latency for file operations, which is critical for latency-sensitive applications such as web serving, content management, and development environments. EFS General Purpose mode is optimized for workloads where consistent low-latency access is required, making it the default and recommended choice for most use cases.

Answer

Use Max I/O performance mode to optimize for the highest possible latency tolerance.

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Use One Zone storage class to increase metadata speed.

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Use Provisioned Throughput mode because it is the only performance mode available.

Question 5

A new feature stores user events in DynamoDB. Each event must be fetched by user_id and sorted by event_time. The team expects many different users and wants to avoid a single hot partition. Which partition key design is best?

Accepted Answer

Use user_id as the partition key and event_time as the sort key.. Using user_id as the partition key evenly distributes writes across partitions, avoiding hot spots, while event_time as the sort key enables efficient retrieval of events for a specific user in chronological order. DynamoDB's query operation can then fetch all events for a given user_id sorted by event_time without scanning.

Answer

Use a constant partition key value (for example, partition_key='events') and store user_id as an attribute.

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Use event_time as the partition key and user_id as an attribute to query later.

Answer

Use a randomly generated UUID as the partition key and query by user_id using a full table scan.

Question 6

Based on the exhibit, which AWS feature should the team use to minimize network latency between EC2 instances that exchange messages very frequently?

Accepted Answer

Use a cluster placement group to place instances close together.. A cluster placement group is the correct choice because it places EC2 instances in a low-latency, high-bandwidth network within a single Availability Zone. This minimizes network latency between instances that exchange messages very frequently, as the instances are physically close together and can communicate using up to 10 Gbps of network throughput for most instance types.

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Use a spread placement group to maximize instance separation across hardware.

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Use a partition placement group to distribute instances across many partitions.

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Use multiple Auto Scaling groups to spread traffic across more subnets.

Question 7

A web service runs on an Auto Scaling group (ASG). The team updates configuration (AMIs, environment variables) in a Launch Template and wants new instances created during scale-out to use the latest Launch Template version. What should the architect do?

Accepted Answer

Set the ASG to use the latest Launch Template version and optionally start an instance refresh for existing instances.. The ASG can be configured to use the latest version of a Launch Template by specifying the `$Latest` version alias. This ensures that any new instances launched during scale-out automatically use the most recent template configuration (e.g., updated AMI, environment variables). Additionally, an Instance Refresh can be triggered to roll the update across existing instances, aligning them with the same latest template version without manual intervention.

Answer

Leave the ASG attached to the previous Launch Template version so scale-out is stable.

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Manually SSH into each new instance and reconfigure it after it launches.

Answer

Move the configuration changes into a security group rule so the ASG updates them automatically.

Question 8

A team runs a stateless web app on Amazon EC2 behind an Application Load Balancer. During traffic spikes, new EC2 instances take several minutes to finish bootstrapping before they can receive traffic. Which Auto Scaling configuration most directly reduces the time until additional capacity is available?

Accepted Answer

Use an Auto Scaling warm pool so pre-initialized instances are ready to enter service.. An Auto Scaling warm pool allows you to maintain a pool of pre-initialized instances that are ready to quickly enter the target group and start serving traffic. Instead of waiting for new instances to boot and configure during a scale-out event, the warm pool provides instances that have already completed bootstrapping, drastically reducing the time to additional capacity.

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Increase the ALB target group deregistration delay.

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Reduce the Auto Scaling group minimum size to one instance.

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Replace the Application Load Balancer with a Network Load Balancer.

Question 9

A company runs a stateless application tier behind an Application Load Balancer. Match each observed scaling pattern on the left to the best Auto Scaling strategy or metric on the right.

Accepted Answer

Steady increase: Step scaling. Steady increase is best handled by step scaling for gradual adjustments; sudden spikes use simple scaling for immediate action; cyclical patterns benefit from scheduled scaling; consistent low traffic may not need scaling; unpredictable bursts are managed by target tracking to maintain a metric; gradual decrease uses simple scaling to reduce capacity.

Answer

Steady increase: Simple scaling

Answer

Unpredictable bursts: Scheduled scaling

Question 10

A compute workload uses temporary scratch space for intermediate results (reproducible), and it can tolerate data loss if the instance is terminated. The workload benefits from very high local I/O throughput. Which storage option is the best fit for the scratch data?

Accepted Answer

Instance store for local temporary files that can be lost when the instance stops.. Instance store volumes provide very high local I/O throughput because they are physically attached to the host server, making them ideal for temporary scratch data that is reproducible and can tolerate loss. Since the workload explicitly accepts data loss on instance termination and does not require persistence across reboots, instance store is the best fit for this use case.

Answer

Amazon EBS General Purpose (gp3) volumes to persist intermediate results across reboots.

Answer

Amazon EFS for a shared file system between multiple instances.

Answer

Amazon S3 for scratch data so it is always durable and accessible from anywhere.

Question 11

A retail analytics app uses Amazon RDS for PostgreSQL. Read traffic is growing, and the database CPU spikes mainly due to SELECT-heavy workloads. Writes are less frequent, and the app can tolerate eventually consistent reads for the reports. What is the most appropriate AWS-native way to improve read performance with minimal application changes?

Accepted Answer

Create an RDS read replica and point the reporting queries to the replica endpoint.. Creating an RDS read replica is the most appropriate AWS-native solution because it offloads SELECT-heavy workloads from the primary database instance to a read-only copy, reducing CPU spikes on the primary. The application can tolerate eventually consistent reads for reports, which is exactly the consistency model of RDS read replicas (typically sub-second replication lag). This requires minimal application changes—only updating the reporting queries to point to the replica endpoint—and fully leverages PostgreSQL's built-in replication capabilities.

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Switch the cluster to DynamoDB without redesigning the data model.

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Enable S3 event notifications to trigger a Lambda function after each write to the database.

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Replace the RDS instance class with a smaller size to reduce cost and improve performance.

Question 12

A media company uses CloudFront in front of an S3 bucket origin for video thumbnails. They want to prevent users from bypassing CloudFront and accessing the S3 bucket directly, while still allowing CloudFront to fetch objects. What is the best option?

Accepted Answer

Use CloudFront Origin Access Control (OAC) or Origin Access Identity (OAI) and update the bucket policy to allow only CloudFront.. CloudFront Origin Access Control (OAC) or Origin Access Identity (OAI) allows you to restrict direct access to an S3 bucket by configuring the bucket policy to grant read permissions only to the CloudFront distribution's service principal. This ensures that users can only retrieve thumbnails through CloudFront, leveraging its caching and security features, while blocking any direct S3 requests.

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Keep the bucket public and rely on signed cookies for all thumbnail requests.

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Enable S3 static website hosting so users access thumbnails directly from the S3 website endpoint.

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Set S3 bucket permissions to allow all IAM users and block access only by using a WAF rule at CloudFront.

Question 13

Based on the exhibit, what is the best change to improve read performance without increasing write latency on the primary database?

Accepted Answer

Create an RDS read replica and direct the reporting queries to the replica endpoint.. Creating an RDS read replica offloads read-heavy reporting queries from the primary database instance, improving read performance without increasing write latency on the primary. The replica operates asynchronously, so writes on the primary are not blocked or delayed by the reporting workload.

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Convert the DB instance to Multi-AZ so the primary can serve more reads.

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Increase the primary instance class to a larger size and keep all traffic on one writer.

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Migrate the reporting workload to DynamoDB to gain faster reads.

Question 14

Based on the exhibit, which storage design best supports the application servers' shared working directory requirement?

Accepted Answer

Mount Amazon EFS on every EC2 instance and use it as the shared workspace.. Amazon EFS provides a fully managed, NFS-based shared file system that can be mounted concurrently on multiple EC2 instances across multiple Availability Zones. This directly satisfies the requirement for a shared working directory where all application servers can read and write files simultaneously without additional synchronization overhead.

Answer

Attach one gp3 EBS volume to each instance and synchronize the files with cron jobs.

Answer

Store the artifacts in S3 and have each node read them directly from S3 as a filesystem.

Answer

Use instance store on each instance because it provides the fastest local file access.

Question 15

Based on the exhibit, which design change is the best way to reduce the observed read latency for this DynamoDB-backed service?

Accepted Answer

Add a DynamoDB Accelerator (DAX) cluster in front of the table and send repeated read traffic through it.. Adding a DynamoDB Accelerator (DAX) cluster in front of the table reduces read latency by providing an in-memory cache for repeated read traffic. DAX delivers microsecond response times for eventually consistent reads, which directly addresses the observed latency issue without requiring application-level caching or table redesign.

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Increase the on-demand table limits so DynamoDB can automatically absorb more traffic.

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Create a global secondary index on tenantId to distribute the load across more partitions.

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Move the dashboard data into S3 and use Lambda functions to read it on demand.