SAA-C03 Design High-Performing Architectures Practice Test 13 — 15 Questions

Question 1

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?

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

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.

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

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

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

Question 2

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.

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

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

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

Question 3

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.. 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.

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

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

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

Question 4

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.. 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.

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

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

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

Question 5

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 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.

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

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

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

Question 6

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.. 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.

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

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

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

Question 7

Based on the exhibit, an application repeatedly reads the same DynamoDB items with extremely low latency requirements. The business can tolerate data that is a few seconds stale. Which architecture change best improves read performance?

Accepted Answer

Add a DynamoDB Accelerator (DAX) cluster in front of the table.. Adding a DynamoDB Accelerator (DAX) cluster provides an in-memory cache that can reduce read latencies to microseconds for frequently accessed items, while still allowing for eventual consistency and tolerating a few seconds of staleness. DAX is specifically designed for this use case, handling cache hits without any application code changes and offloading read traffic from the DynamoDB table.

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Increase the table's sort key cardinality while keeping the same read pattern.

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Switch the table to provisioned mode with auto scaling disabled.

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Move the session data to Amazon EFS so the application can read it from shared files.

Question 8

Based on the exhibit, a serverless API on AWS Lambda experiences a predictable cold-start penalty every weekday at 09:00 UTC when a marketing campaign begins. The team wants the first requests to stay fast while minimizing extra cost during quiet periods. What is the best approach?

Accepted Answer

Enable provisioned concurrency on the published version and schedule it to scale up shortly before the spike.. Provisioned concurrency pre-warms a specified number of Lambda execution environments so that incoming requests do not incur a cold start. By scheduling the provisioned concurrency to scale up just before the 09:00 UTC spike and scale down afterward, the team eliminates the cold-start penalty during the campaign while minimizing cost during quiet periods. This directly addresses the predictable, time-bound traffic pattern without requiring code changes or over-provisioning.

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Increase the Lambda timeout so cold starts have more time to complete.

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Move the function behind an Application Load Balancer to improve warm-up behavior.

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Increase the function memory to the maximum value and leave concurrency unchanged.

Question 9

Based on the exhibit, a distributed analytics workload runs on 12 EC2 instances in one Availability Zone. The nodes exchange thousands of small messages per second and require the lowest possible intra-cluster latency and jitter. Which EC2 placement strategy is the best fit?

Accepted Answer

Cluster placement group, because it places instances physically close together in one Availability Zone.. A cluster placement group is the best choice because it places all 12 EC2 instances in a single Availability Zone within the same high-bandwidth, low-latency logical segment of the network. This minimizes the physical distance and network hops between nodes, achieving the lowest possible intra-cluster latency and jitter required for the thousands of small messages exchanged per second.

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Spread placement group, because it places each instance on distinct underlying hardware.

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Partition placement group, because it isolates nodes across rack partitions.

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Move the workload behind an Application Load Balancer so node-to-node traffic is balanced more efficiently.

Question 10

Based on the exhibit, a single EC2 instance hosts a latency-sensitive cache that performs sustained random reads and writes to persistent block storage. The current EBS volume is a general-purpose SSD, but BurstBalance is repeatedly depleted and p95 I/O latency has risen above 20 ms. The workload needs more than 16,000 sustained IOPS. Which change is the best fix?

Accepted Answer

Replace the volume with an io2 EBS volume and provision the required IOPS.. The workload requires more than 16,000 sustained IOPS with low latency, and the gp2 volume's burst credits are exhausted, causing high latency. An io2 Block Express or io2 volume can be provisioned with the exact IOPS needed (up to 256,000 IOPS) and provides consistent single-digit millisecond latency, making it the best fix for this latency-sensitive, sustained I/O workload.

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Move the data to Amazon S3 so the instance can read and write objects directly.

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Keep gp2 and increase the instance size to a compute-optimized family.

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Enable Amazon EFS with bursting throughput mode for the cache data.

Question 11

A media company serves versioned JavaScript and CSS files from Amazon S3 through CloudFront. After each release, the cache hit ratio drops sharply because the same distribution also fronts a personalized API path, and the current cache policy forwards cookies, all query strings, and several headers to every origin request. The static assets already use content-hashed filenames. Which two changes will most directly improve cache hit ratio for the static assets without changing the application behavior? Select two.

Accepted Answer

Create a dedicated cache behavior for the static asset path that excludes cookies, query strings, and unneeded headers from the cache key.. Creating a dedicated cache behavior for the static asset path (e.g., /static/*) allows you to configure a cache policy that excludes cookies, query strings, and unneeded headers from the cache key. Since the static assets use content-hashed filenames, they are immutable and do not vary by user-specific attributes. By removing these variables from the cache key, CloudFront can serve the same cached object to all users, drastically improving the cache hit ratio.

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Increase the size of the S3 bucket’s underlying storage to absorb more origin traffic.

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Add Lambda@Edge logic to append a timestamp to every asset request so updates are always fetched immediately.

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Disable compression so CloudFront can treat each object as a separate cache entry.

Question 12

A retail analytics table stores events in Amazon DynamoDB with partition key tenantId and sort key eventTime. During a promotion, one tenant generates most writes and repeatedly polls the same latest-status items, causing throttling on a single partition key and high latency on reads. The business can tolerate read results that are a few seconds stale. Which two changes will most effectively reduce throttling and latency? Select two.

Accepted Answer

Introduce write sharding by adding a bounded random suffix to the hot tenant partition key and fan out reads across the shards.. Write sharding distributes the hot tenant's writes across multiple partitions by appending a bounded random suffix to the partition key, preventing a single partition from throttling. Reads then fan out across all shards and aggregate results, which is acceptable since the business tolerates a few seconds of staleness. This directly addresses the single-partition bottleneck without changing the overall data model.

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Keep the same key design and increase only the table’s provisioned RCUs and WCUs.

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Replace the table reads with a Scan operation to distribute the load across all partitions.

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Move the table to another Availability Zone so the hot tenant uses a different storage node.

Question 13

A distributed analytics engine runs 12 EC2 instances in one Availability Zone. The nodes exchange thousands of tiny messages per second and must keep jitter as low as possible. The current design launches the instances across multiple placement groups and uses general-purpose burstable instances. Which two changes will most directly lower east-west network latency and variability? Select two.

Accepted Answer

Move all instances into a cluster placement group.. A cluster placement group provides a low-latency, high-bandwidth network connection by placing instances in a single Availability Zone within the same logical rack or cluster. This minimizes the physical distance and network hops between instances, directly reducing east-west latency and jitter for the thousands of tiny messages per second.

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Spread the instances across three Availability Zones for better fault tolerance.

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Front the nodes with an Application Load Balancer to balance the internal messages.

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Store the messages on EBS volumes so the nodes avoid network communication.

Question 14

A serverless checkout API uses AWS Lambda behind API Gateway. Every weekday at 09:00 UTC, marketing triggers a predictable surge. The first few minutes after each surge show cold-start latency, but traffic volume is forecastable and the business wants stable p95 latency. Which two changes should the team implement? Select two.

Accepted Answer

Publish a Lambda version and attach provisioned concurrency to an alias that points to that version.. Provisioned concurrency keeps a specified number of Lambda execution environments initialized and ready to respond immediately, eliminating cold starts for predictable traffic patterns. By publishing a Lambda version and attaching provisioned concurrency to an alias pointing to that version, the team ensures that the surge at 09:00 UTC is handled without cold-start latency, stabilizing p95 latency.

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Increase the Lambda timeout so the function has more time to initialize during the spike.

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Double the memory size during the spike without changing the concurrency model.

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Move the function into more Availability Zones so the platform can spread cold starts across regions.

Question 15

A partner integration sends a custom binary TCP protocol to a service running on EC2 instances in private subnets. The partners require static endpoint IPs for allowlisting, and the application must see the original client source IP for rate limiting. Which two changes best fit the protocol and network requirements? Select two.

Accepted Answer

Replace the Application Load Balancer with a Network Load Balancer.. A Network Load Balancer (NLB) is required because it supports TCP traffic natively at Layer 4, which is necessary for a custom binary TCP protocol that cannot be interpreted by an Application Load Balancer (ALB) at Layer 7. Additionally, an NLB preserves the original client source IP address by default when used with targets in private subnets, meeting the requirement for rate limiting based on the client IP. Static IP addresses can be assigned to the NLB via Elastic IPs, satisfying the partner's need for static endpoint IPs for allowlisting.

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Put the service behind API Gateway REST API and use Lambda integration.

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Use CloudFront to cache the binary packets at edge locations.

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Terminate the traffic with an Amazon RDS proxy to stabilize the connections.