SAA-C03 Design High-Performing Architectures Practice Test 2 — 15 Questions

Question 1

A backend API uses an AWS Lambda function behind API Gateway. The first requests after every weekly deployment experience cold starts, causing p95 latency spikes for a few minutes. Which configuration most directly prevents those cold starts for the published version?

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

Accepted Answer

Use Lambda provisioned concurrency for the version via an alias. Provisioned concurrency initializes a specified number of Lambda execution environments ahead of time, so that when the published version is invoked via an alias, there are no cold starts. This directly addresses the latency spikes caused by cold starts after a deployment, as the function is kept warm and ready to handle requests immediately.

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Increase the Lambda memory size only, without changing how Lambda is invoked

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Enable dead-letter queues (DLQ) to retry failed cold starts

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Attach a CloudFront distribution to cache API Gateway responses for 5 minutes

Question 2

A marketing site serves versioned JavaScript and CSS files from Amazon S3 through CloudFront. Origin bandwidth costs are rising because CloudFront keeps revalidating objects and fetching too much content from the bucket. Which two changes most directly improve cache hit ratio and reduce origin load? Select two.

Accepted Answer

Use versioned object names and long cache TTLs for immutable assets.. Using versioned object names (e.g., app-v1.js, app-v2.js) combined with long cache TTLs (e.g., one year) tells CloudFront that these assets are immutable. Once cached, CloudFront never revalidates them, eliminating origin requests for unchanged files. This directly reduces origin bandwidth costs by preventing unnecessary fetches from S3.

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Forward all cookies and query strings so each request is treated as unique.

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Switch the bucket to S3 Intelligent-Tiering to reduce CloudFront origin requests.

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Add more NAT Gateways to improve the speed of CloudFront origin fetches.

Question 3

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).

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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 4

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 5

Based on the exhibit, the team wants to improve application performance without changing the code. Which EC2 instance family should they choose next?

Accepted Answer

Choose a memory-optimized instance family such as R6i to provide more RAM.. The exhibit shows a memory-constrained application (e.g., high cache miss rates or swap usage) where performance is bottlenecked by insufficient RAM. Choosing a memory-optimized instance family like R6i provides more RAM per vCPU, allowing the application to keep more data in memory and reduce disk I/O, directly improving performance without code changes.

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Choose a compute-optimized instance family such as C6i to increase CPU performance.

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Choose a storage-optimized instance family such as I4i to improve block storage throughput.

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Choose a burstable instance family such as T3 to reduce cost and improve performance.

Question 6

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.

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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.

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

Question 7

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 8

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.

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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.

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

Question 9

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 10

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 11

A media platform serves global users through Amazon CloudFront and an S3 origin. Match each requirement on the left to the CloudFront configuration or behavior on the right.

Accepted Answer

Restrict access by geography: Geo Restriction. Geo restriction limits access by geography; origin groups enable failover or load balancing; Lambda@Edge customizes content based on device; edge locations reduce latency; AWS WAF mitigates DDoS; signed URLs secure private content.

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Provide failover or load balancing: Lambda@Edge

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Secure private content: Geo Restriction

Question 12

Based on the exhibit, which storage choice best matches the workload requirements?

Accepted Answer

Use instance store NVMe for the temporary processing workspace.. Instance store NVMe volumes provide temporary, high-performance block storage directly attached to the EC2 host. For a temporary processing workspace where data does not need to persist beyond the instance lifecycle, instance store offers the lowest latency and highest throughput, making it the best match for the workload requirements.

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Use io2 EBS volumes because they provide the highest durable block storage performance.

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Use Amazon EFS for the workspace so the temporary files survive instance replacement.

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Use S3 as the working directory and read and write the intermediate files directly there.

Question 13

A company runs a stateless web API on Amazon EC2 behind an Application Load Balancer. The team notices that during business hours, the ALB starts queueing requests and the average request latency rises. They want to scale out quickly and reliably based on demand, not CPU alone. Which Auto Scaling approach best matches this requirement?

Accepted Answer

Use target tracking scaling based on ALB request count per target.. Target tracking scaling based on ALB request count per target directly aligns with the requirement to scale out based on demand (request queuing and latency) rather than CPU alone. This policy automatically adjusts the Auto Scaling group size to maintain a target value for the average number of requests per instance, which is a more reliable indicator of load for a stateless web API than CPU utilization.

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Use a fixed-size Auto Scaling group and increase capacity manually once per hour.

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Scale based only on EC2 instance memory utilization, regardless of load.

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Use step scaling with a single threshold on average network-in bytes.

Question 14

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 uses step scaling for gradual adjustments; sudden spikes are best handled by step scaling; cyclical patterns use scheduled scaling; consistent low traffic may need no scaling; unpredictable bursts use target tracking; gradual decrease uses simple scaling.

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Sudden spike: Simple scaling

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Steady increase: Simple scaling

Question 15

Based on the exhibit, which change best reduces latency during peak traffic without overprovisioning the fleet?

Accepted Answer

Change the Auto Scaling policy to target tracking on ALB RequestCountPerTarget.. Using a target tracking scaling policy on ALB RequestCountPerTarget dynamically adjusts the fleet size based on the actual load per instance, ensuring that capacity scales with demand during peak traffic without manual intervention or overprovisioning. This approach directly addresses latency caused by high request rates per instance by maintaining a target request count, which reduces response time without adding unnecessary instances during off-peak periods.

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Replace the instances with a larger instance family so each server has more headroom.

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Use scheduled scaling to add instances only during the business hours peak window.

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Replace the ALB with a Network Load Balancer to reduce request latency.