SAA-C03 Design High-Performing Architectures Practice Test 6 — 15 Questions

Question 1

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?

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

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.

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

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

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

Question 2

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.

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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 3

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.

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Spread placement group

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Partition placement group

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Auto Scaling group with a mixed instances policy

Question 4

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 5

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 6

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 7

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 8

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 9

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 10

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 11

A media company serves versioned JavaScript and CSS files from an Amazon S3 origin through CloudFront. After each release, origin requests spike even though the files are public. Browser requests include a tracking cookie, an Authorization header, and a cache-busting query string that the site no longer needs. Which three changes will most improve the CloudFront cache hit ratio without exposing private content? Select three.

Accepted Answer

Rename each static asset with a content hash or release version in the filename before publishing.. Renaming static assets with a content hash or version in the filename ensures that each new release creates a unique object key in S3. This allows CloudFront to treat the new file as a distinct object, avoiding cache invalidation issues and enabling long-term caching of the old version. Without this, even with cache-busting query strings, CloudFront might still serve stale content or require frequent invalidations, reducing the cache hit ratio.

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Enable CloudFront compression and configure the origin to return Cache-Control: no-store for all files.

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Forward all viewer headers to the origin so CloudFront can personalize every request.

Question 12

A read-heavy document portal repeatedly queries the same product catalogue data from DynamoDB with millisecond latency requirements. Which service can reduce read latency and table load?

Accepted Answer

DynamoDB Accelerator (DAX). DynamoDB Accelerator (DAX) is a fully managed, in-memory cache for Amazon DynamoDB that delivers up to 10x read performance improvement by caching frequently accessed data. For a read-heavy workload querying the same product catalogue data, DAX reduces read latency to microseconds and offloads read requests from the DynamoDB table, lowering consumed read capacity units and table load.

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Amazon Kinesis Data Firehose

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S3 Transfer Acceleration

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AWS Glue Data Catalog

Question 13

A analytics dashboard uses RDS MySQL and receives many read-only reporting queries that slow down the primary database. What should the architect add?

Accepted Answer

RDS read replica and route reporting queries to it. Adding an RDS read replica offloads read-heavy reporting queries from the primary MySQL instance, preserving write performance. The read replica asynchronously replicates data using MySQL's native binlog replication, and routing reporting queries to its endpoint reduces contention on the primary.

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S3 lifecycle policy

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Multi-AZ standby and route reads to the standby

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A larger NAT gateway

Question 14

A latency-sensitive mobile game backend uploads large files to S3 from users around the world. Which two features can improve upload performance?

Accepted Answer

S3 multipart upload. S3 multipart upload is correct because it allows large files to be uploaded in parallel parts, which reduces the impact of network latency and improves throughput. For a latency-sensitive mobile game backend, this feature enables faster uploads by splitting the file into smaller chunks that can be uploaded concurrently, even over unstable connections.

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S3 Object Lock

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S3 Inventory

Question 15

A media archive requires consistent high IOPS for a transactional database on EC2. Which EBS volume type is most suitable?

Accepted Answer

Provisioned IOPS SSD such as io2. The scenario requires consistent high IOPS for a transactional database, which demands low-latency, predictable performance. Provisioned IOPS SSD volumes like io2 are designed specifically for such workloads, offering up to 256,000 IOPS per volume with 99.999% durability, making them the most suitable choice for consistent high IOPS.

Answer

st1 Throughput Optimized HDD

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Instance store only

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sc1 Cold HDD