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

Question 1

A web application uses an Amazon Aurora DB cluster for a read-heavy workload. The team wants to increase read throughput without changing the database schema or rewriting application data access patterns. Which two changes should they make? Select two.

Accepted Answer

Add Aurora Replicas to scale out read traffic across multiple database instances.. Adding Aurora Replicas (Option A) directly increases read throughput by distributing read-only queries across multiple database instances, which is ideal for a read-heavy workload. Sending read queries to the Aurora reader endpoint (Option B) ensures that these queries are load-balanced across all available replicas, offloading the writer instance and improving overall performance without requiring schema or application changes.

Answer

Point all queries to the writer endpoint so Aurora can balance reads and writes internally.

Answer

Enable Multi-AZ standby for the cluster to increase the number of read-only connections.

Answer

Move the database to a single larger instance class instead of adding replicas.

Question 2

A CPU-bound batch rendering service runs on EC2. The application is Linux-based, compatible with ARM64, and the team wants the best throughput per dollar without changing the workload's architecture. Which two instance-family choices should the team consider first? Select two.

Accepted Answer

A compute-optimized family, because it is designed for workloads that spend most of their time on CPU.. Option A is correct because compute-optimized families (e.g., C5, C6g) are designed for workloads that spend most of their time on CPU, such as batch rendering. Option B is correct because Graviton-based instances (e.g., C6g, M6g) use ARM64 architecture, which is compatible with the workload and often delivers better price-performance for compute-intensive tasks, maximizing throughput per dollar without architectural changes.

Answer

A memory-optimized family, because extra RAM always increases compute throughput.

Answer

A storage-optimized family, because local storage bandwidth is the main factor for rendering performance.

Answer

A burstable family, because CPU credits make sustained rendering faster during long runs.

Question 3

A single EC2 instance hosts a low-latency database cache that writes a large random working set to block storage. The application needs sustained high IOPS and low latency, and the storage must remain attached to the instance while it runs. Which two design choices best meet the requirement? Select two.

Accepted Answer

Use an io2 Block Express EBS volume for the highest sustained IOPS and low-latency performance.. Option A is correct because io2 Block Express EBS volumes are designed for mission-critical workloads requiring sustained high IOPS and low latency. They offer up to 256,000 IOPS per volume with sub-millisecond latency, making them ideal for a low-latency database cache that writes a large random working set to block storage. The storage remains attached to the EC2 instance while it runs, meeting the requirement for persistent block-level storage.

Answer

Use an S3 bucket as the backing store because object storage scales automatically.

Answer

Choose a cold HDD-based volume so the cache has durable low-cost storage.

Answer

Use the root volume from a T-series instance because burst credits can absorb the write spikes.

Question 4

Based on the exhibit, a media company serves versioned JavaScript and CSS files from an Amazon S3 origin through CloudFront. After a frontend release, the cache hit ratio dropped sharply even though the file names are versioned. The application team says the browser requests include the same Authorization header on every asset request because the frontend and API share one domain. What should the solutions architect do to improve CloudFront cache hit ratio without changing the application authentication model for the API?

Accepted Answer

Create a CloudFront cache policy that excludes Authorization, cookies, and unnecessary query strings from the cache key.. The sharp drop in cache hit ratio is caused by the Authorization header being included in the cache key, which makes each request unique even though the file names are versioned. By creating a CloudFront cache policy that excludes the Authorization header (and unnecessary cookies/query strings) from the cache key, CloudFront can serve cached responses to requests with different Authorization headers, restoring the cache hit ratio without altering the application's authentication model for the API.

Answer

Enable S3 Transfer Acceleration on the bucket so CloudFront fetches objects faster from the origin.

Answer

Switch the origin from S3 to an Application Load Balancer so CloudFront can cache dynamic responses more effectively.

Answer

Configure CloudFront to forward every viewer header to the origin so the origin can decide whether the content is cacheable.

Question 5

Based on the exhibit, a retail analytics service repeatedly reads the same DynamoDB items during an active campaign. The business can tolerate data that is a few seconds stale, but the application must minimize latency and reduce pressure on DynamoDB. A load test shows that 80% of reads target only 200 item keys. What should the solutions architect implement?

Accepted Answer

Add a DynamoDB Accelerator (DAX) cluster in front of the table and point the application to the DAX endpoint.. DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache designed specifically for DynamoDB. It reduces read latency from single-digit milliseconds to microseconds and offloads repeated reads from the table, which directly addresses the requirement to minimize latency and reduce pressure on DynamoDB. Since the business can tolerate stale data (DAX default TTL is 5 minutes, but can be configured lower), DAX is ideal for the 80% of reads hitting only 200 hot keys.

Answer

Switch the table to provisioned capacity with auto scaling so DynamoDB can handle the repeated reads more efficiently.

Answer

Create a global table in a second Region and read from the replica Region to lower latency.

Answer

Move the hot items into Amazon ElastiCache for Redis and keep the remaining data in DynamoDB.

Question 6

Based on the exhibit, an application runs on Amazon Aurora MySQL. The writer instance is frequently near 85% CPU while the reader instance is under 20% CPU. Application traces show that most of the database traffic is read-only SELECT queries, but the code currently sends all queries to the writer endpoint. What should the solutions architect recommend to improve performance with the smallest functional change?

Accepted Answer

Point read-only database traffic to the Aurora reader endpoint and keep writes on the writer endpoint.. Option B is correct because the Aurora reader endpoint distributes read-only traffic across all available reader instances, offloading the writer instance and reducing its CPU utilization. Since the application traces show most traffic is read-only SELECT queries, this change requires only modifying the connection string for reads while keeping writes on the writer endpoint, making it the smallest functional change.

Answer

Increase the writer instance size and keep all traffic on the writer endpoint.

Answer

Convert the cluster to a Multi-AZ RDS PostgreSQL deployment to get automatic failover and better read performance.

Answer

Enable cross-Region read replicas so SELECT queries are routed to a remote Region for improved performance.

Question 7

Based on the exhibit, a serverless checkout API is implemented in AWS Lambda and deployed in one Region. The function has a cold-start time of 700-900 ms on the first request after idle periods. Marketing launches a predictable traffic spike every weekday at 09:00 UTC, and the p95 latency target is under 150 ms during the first five minutes of the spike. What should the solutions architect do to meet the latency target while controlling cost?

Accepted Answer

Configure provisioned concurrency and scale it up before the predictable spike begins.. Provisioned concurrency pre-warms a specified number of execution environments so that the Lambda function has zero cold-start latency when invoked. By scheduling the provisioned concurrency to scale up before the 09:00 UTC spike, the function can serve the first requests within the 150 ms p95 latency target, while the scheduled scaling down after the spike controls cost by releasing unused capacity.

Answer

Increase the Lambda memory size and leave concurrency at the default value.

Answer

Put the Lambda function behind an Application Load Balancer so the load balancer absorbs the initialization delay.

Answer

Set reserved concurrency to the expected peak so Lambda will pre-create execution environments.

Question 8

Based on the exhibit, a trading platform exposes a custom binary TCP protocol to partner systems. The service must preserve the original client source IP for rate limiting, support TLS pass-through to the application, and minimize network latency. The team also wants a simple architecture that can scale across multiple Availability Zones. What load balancing option should the solutions architect choose?

Accepted Answer

Network Load Balancer with TCP listeners and target groups in the private subnets.. A Network Load Balancer (NLB) with TCP listeners is the correct choice because it preserves the original client source IP address (via the Proxy Protocol header or direct preservation in the TCP flow), supports TLS pass-through (no decryption at the load balancer), and minimizes latency by operating at Layer 4. It also scales across multiple Availability Zones with simple target groups in private subnets, meeting all stated requirements.

Answer

Application Load Balancer with path-based routing and HTTP/2 enabled.

Answer

Amazon API Gateway REST API integrated directly with the EC2 instances.

Answer

CloudFront in front of the EC2 instances to cache and terminate the client connections.

Question 9

Based on the exhibit, a media rendering job runs on a single EC2 instance and writes a large working set of metadata to block storage. The workload performs sustained random reads and writes and must keep latency consistently low for the entire run. The instance may be stopped and started between jobs, and the data must persist. Which storage choice best meets the requirements?

Accepted Answer

Provisioned IOPS SSD EBS volume (io2).. The workload requires sustained low-latency random reads and writes to block storage, and the data must persist across instance stop/start cycles. Provisioned IOPS SSD EBS volumes (io2) are block-level storage designed for high-performance, low-latency workloads with consistent IOPS, and they persist independently of the EC2 instance lifecycle.

Answer

Amazon S3 with multipart uploads because it provides durable object storage and high throughput.

Answer

Amazon EFS because it can be mounted by EC2 and supports persistent file access.

Answer

Amazon FSx for Windows File Server because it offers durable storage and low latency.

Question 10

Based on the exhibit, a low-latency analytics platform runs 10 EC2 instances in the same Availability Zone. The nodes exchange a very high volume of east-west messages and must experience the lowest possible network latency and jitter. A separate operations team also wants to reduce the risk that all nodes land on the same physical hardware rack. Which placement strategy should the solutions architect use?

Accepted Answer

Cluster placement group. A cluster placement group is the correct choice because it provides the lowest possible network latency and jitter by ensuring all 10 EC2 instances are placed in close proximity within a single Availability Zone, enabling non-blocking, high-bandwidth communication. This is ideal for high-volume east-west traffic, as it maximizes network performance for tightly coupled workloads like analytics platforms.

Answer

Spread placement group

Answer

Partition placement group

Answer

Auto Scaling group with a mixed instances policy

Question 11

Based on the exhibit, a batch-processing service runs on Amazon EC2. The workload is Linux-based, can run on ARM64, and is CPU-bound during its nightly processing window. The team wants the best throughput per dollar without changing the application logic. Which EC2 instance family should the solutions architect recommend?

Accepted Answer

C7g instances based on AWS Graviton processors. The C7g instances are based on AWS Graviton processors (ARM64 architecture), which offer up to 25% better performance per dollar compared to x86-based instances for CPU-bound workloads. Since the workload is Linux-based, can run on ARM64, and is CPU-bound, the C7g family provides the best throughput per dollar without requiring any application logic changes.

Answer

R7i instances because more memory will improve CPU-bound job throughput.

Answer

M7a instances because general-purpose families are always the safest performance choice.

Answer

T3 instances because burstable instances can handle occasional nighttime spikes at lower cost.

Question 12

Based on the exhibit, a web application runs on an Amazon EC2 Auto Scaling group behind an Application Load Balancer. During traffic surges, the average CPU utilization stays below 35%, but request latency increases sharply and the ALB access logs show far more requests per target than expected. Which change is the best way to improve scaling behavior?

Accepted Answer

Configure target tracking scaling on ALB RequestCountPerTarget for the Auto Scaling group.. Option C is correct because the issue is that request latency increases sharply and the ALB logs show far more requests per target than expected, indicating that the Auto Scaling group is not scaling based on the actual load per instance. By configuring target tracking scaling on ALB RequestCountPerTarget, the Auto Scaling group will launch new instances when the average number of requests per target exceeds a defined threshold, directly addressing the root cause of high request volume per instance. This approach ensures scaling is driven by the actual workload distribution rather than CPU utilization, which remains low due to the application being I/O-bound or network-bound.

Answer

Lower the CPU target tracking threshold so the Auto Scaling group launches more instances sooner.

Answer

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

Answer

Increase the ALB idle timeout so requests can wait longer before timing out.

Question 13

Based on the exhibit, a DynamoDB-backed event processing system is throttling during a promotion. The table uses tenantId as the partition key and eventTime as the sort key. One tenant accounts for most of the write traffic, and the application must preserve fast lookups for that tenant without relying on a single hot partition. What change is the best fix?

Accepted Answer

Add a sharding suffix to the partition key, such as tenantId#shardId, and query across the tenant's shards.. Option A is correct because adding a sharding suffix (e.g., tenantId#shardId) to the partition key distributes write traffic for the hot tenant across multiple partitions, eliminating the single-partition bottleneck while preserving fast lookups by querying across all shards for that tenant. DynamoDB's partition key determines physical storage; without sharding, all writes for the hot tenant land on one partition, causing throttling even if the table has sufficient total capacity.

Answer

Enable DynamoDB Streams so the table can process writes more quickly.

Answer

Switch the table to on-demand capacity mode and keep the same key design.

Answer

Add a global secondary index on eventTime and query the index instead of the base table.

Question 14

Based on the exhibit, an Amazon Aurora MySQL application is read-heavy, but the database writer is nearing CPU limits while the reader instance is mostly idle. The application currently sends all queries to the writer endpoint. Which change should you make first to increase read throughput?

Accepted Answer

Change the application to send read-only queries to the Aurora reader endpoint.. The correct answer is B because the Aurora reader endpoint is specifically designed to distribute read-only traffic across all available reader instances, offloading the writer and increasing read throughput. Since the reader instance is idle, directing read queries to the reader endpoint immediately reduces CPU load on the writer without requiring any architectural changes.

Answer

Keep using the writer endpoint so Aurora can route the reads automatically.

Answer

Convert the cluster to a single-AZ deployment so network hops are reduced.

Answer

Add an Amazon DynamoDB Accelerator (DAX) cluster in front of Aurora.

Question 15

Based on the exhibit, a static asset distribution site uses Amazon CloudFront with an S3 origin. The assets are versioned by filename, but the cache hit ratio remains low after each release. Which CloudFront change is the best way to improve cache reuse without changing the origin objects?

Accepted Answer

Remove Authorization and unnecessary query strings from the CloudFront cache key.. Option B is correct because removing Authorization headers and unnecessary query strings from the CloudFront cache key ensures that multiple requests for the same versioned asset (e.g., style.v2.css) share a single cached object, regardless of user-specific headers or irrelevant query parameters. This directly increases the cache hit ratio without modifying the origin objects, as CloudFront will serve the same cached response for identical cache keys.

Answer

Keep the current cache key and increase the S3 bucket's storage class.

Answer

Disable the CloudFront cache so every request is served directly from S3.

Answer

Switch the origin from Amazon S3 to an Application Load Balancer.