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

Question 1

A research team runs a latency-sensitive distributed training job on Amazon EC2. They deploy 80 identical nodes that exchange small messages frequently and need low network jitter. The job must run entirely within one Availability Zone. Which placement group strategy should a solutions architect use to maximize intra-cluster network performance?

Accepted Answer

Use a cluster placement group to keep all instances in close proximity within the same Availability Zone.. A cluster placement group is the correct choice because it places all 80 EC2 instances in close physical proximity within a single Availability Zone, ensuring low-latency, high-bandwidth network connections with minimal jitter. This placement group type is specifically designed for tightly coupled, latency-sensitive workloads like distributed training that require frequent, small message exchanges, as it leverages non-blocking, high-throughput networking between instances.

Answer

Use a spread placement group to distribute instances across distinct hardware to reduce jitter.

Answer

Use a partition placement group and place each node into its own partition for uniform latency.

Answer

Do not use a placement group; rely on the default EC2 scheduling to balance latency and availability.

Question 2

A game streaming service must use UDP for real-time gameplay traffic. For external firewall allowlisting, the service requires stable, static IP addresses. The TLS handshake must be handled end-to-end by the application servers (the load balancer must not terminate TLS). Which AWS load balancing option best fits these requirements?

Accepted Answer

Use a Network Load Balancer (NLB) with a UDP listener, configure the NLB to use Elastic IP addresses for static IPs, and use TCP listeners for TLS passthrough to the application servers.. A Network Load Balancer (NLB) supports UDP listeners, which are required for real-time gameplay traffic, and can be assigned Elastic IP addresses to provide stable, static IPs for firewall allowlisting. Additionally, NLB supports TCP listeners with TLS passthrough, meaning it forwards the encrypted traffic without terminating the TLS handshake, allowing the application servers to handle end-to-end encryption as required.

Answer

Use an Application Load Balancer (ALB) with UDP listeners and configure TLS passthrough.

Answer

Use Amazon API Gateway with a WebSocket API and keepalive pings to provide UDP-like low-latency delivery.

Answer

Use a Classic Load Balancer and multiplex UDP over TCP to meet the UDP and low-latency requirements.

Question 3

A company runs an Amazon RDS for PostgreSQL database. The application performs frequent OLTP writes, but it also has a separate dashboard that runs heavy SELECT queries and is slowing down overall database performance. The writes must remain on the primary. What is the best approach to improve performance for the dashboard?

Accepted Answer

Create an RDS read replica and route the dashboard’s read-only queries to the replica endpoint. Creating an RDS read replica allows you to offload the heavy SELECT queries from the primary database instance. The replica asynchronously replicates data from the primary using PostgreSQL's streaming replication, so the dashboard can query the replica without impacting the OLTP write performance on the primary. This directly addresses the requirement that writes remain on the primary while improving dashboard query performance.

Answer

Increase instance storage throughput limits and disable synchronous replication to speed up all queries

Answer

Replace RDS with Amazon S3 because dashboards require SQL result caching

Answer

Move the primary database to a different AWS Region to reduce network latency

Question 4

A startup runs an HTTP/2 API that also supports WebSocket connections. They need path-based routing to separate microservices (for example, /api/* to Service A and /metrics/* to Service B) and want TLS terminated at the load balancer. Which AWS option best meets these requirements while maintaining high request performance?

Accepted Answer

Use an Amazon ALB with HTTP/2 support, WebSocket upgrades enabled, and listener rules for host/path-based routing.. An Application Load Balancer (ALB) natively supports HTTP/2, WebSocket upgrades, and path-based routing via listener rules. It terminates TLS at the load balancer, offloading encryption from backend services, and maintains high performance for both HTTP/2 and WebSocket traffic. This makes ALB the correct choice for the startup's requirements.

Answer

Use an Amazon NLB and configure target groups with HTTP health checks and listener rules for path-based routing.

Answer

Use Amazon API Gateway with a single backend integration and rely on the client to route requests to different microservices.

Answer

Use Amazon CloudFront without an ALB, and route requests to microservices using only custom origin headers.

Question 5

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?

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.

Answer

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

Answer

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

Answer

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

Question 6

A DynamoDB table uses this schema: partition key = customerId, sort key = timestamp. During a marketing campaign, one customer generates extremely high read traffic and the application sees ProvisionedThroughputExceeded errors even though the table’s total capacity is sufficient. What change most directly improves read distribution across partitions?

Accepted Answer

Add a salt component to the partition key by changing it to customerId#salt, where salt is derived from a hash of requestId so a single customer’s requests are spread across many partitions; keep the sort key as timestamp.. Option B is correct because adding a salt to the partition key (e.g., customerId#hash(requestId)) distributes the read-heavy customer's data across multiple physical partitions. This prevents a single hot partition from throttling requests, even when the table's total provisioned capacity is sufficient. DynamoDB's partition key determines the internal hash used for data placement, so increasing partition key cardinality directly improves read distribution.

Answer

Increase the table’s provisioned read capacity units while keeping partition key = customerId.

Answer

Remove the sort key and use timestamp as the partition key to increase cardinality.

Answer

Switch to on-demand capacity and rely on DynamoDB to automatically distribute reads across partitions.

Question 7

Based on the exhibit, what change should the team make to achieve the lowest possible network latency for the distributed workload?

Accepted Answer

Move the workload into a cluster placement group in one Availability Zone.. A cluster placement group provides the lowest possible network latency and highest throughput by placing all instances in a single Availability Zone with low-latency, non-blocking 10 Gbps or 25 Gbps network connectivity between them. This is ideal for tightly coupled, distributed workloads that require frequent inter-node communication, such as HPC or data analytics jobs.

Answer

Place the instances in a spread placement group across multiple Availability Zones.

Answer

Add an Application Load Balancer in front of the workers to reduce inter-node latency.

Answer

Increase the EC2 instance size while keeping the current multi-AZ layout.

Question 8

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.. Option A is correct because 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.

Answer

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

Answer

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

Answer

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

Question 9

An Aurora PostgreSQL cluster is experiencing high read latency because 85% of traffic consists of read-only queries. The write workload must stay on the writer instance, and the team wants to offload reads without changing the application’s core query patterns. What is the best architectural option?

Accepted Answer

Add Aurora reader instances (read replicas) and route read queries to the reader endpoint while keeping writes on the writer endpoint.. Adding Aurora reader instances (read replicas) and routing read queries to the reader endpoint offloads read traffic from the writer instance without altering application query patterns. Aurora reader endpoints automatically distribute read-only connections across all replicas, reducing latency on the writer while keeping writes on the writer instance. This directly addresses the 85% read-heavy workload without requiring application changes.

Answer

Increase the writer instance size so it can handle more reads and writes simultaneously.

Answer

Enable Multi-AZ failover only and rely on the standby to serve reads in normal operation.

Answer

Move the read workload to ElastiCache Redis while keeping DynamoDB as the SQL data source.

Question 10

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.

Answer

Use st1 because it provides high throughput for streaming data.

Answer

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

Question 11

A customer-facing application has a relational data model and needs frequent complex queries (joins and aggregations), but it also experiences a significant read-heavy workload. Which design choice best improves read performance while keeping relational features?

Accepted Answer

Add read replicas to an RDS or Aurora cluster and keep the primary for writes.. Adding read replicas to an RDS or Aurora cluster offloads read traffic from the primary instance, improving read performance for complex queries (joins and aggregations) while preserving the full relational data model and SQL capabilities. Aurora’s distributed storage layer also allows replicas to serve reads with minimal replication lag, making this the optimal choice for read-heavy workloads that require relational features.

Answer

Use DynamoDB with a single partition key and avoid indexes to keep writes simple.

Answer

Store the data in S3 and query it directly from the application without a database.

Answer

Switch the database to DynamoDB but keep using the same relational SQL queries and joins.

Question 12

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.. Option B is correct because 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.

Answer

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

Answer

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

Question 13

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.

Answer

Increase the function timeout so throttling is less likely.

Answer

Enable Provisioned Concurrency for every Lambda in the account.

Answer

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

Question 14

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.

Answer

Use One Zone storage class to increase metadata speed.

Answer

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

Question 15

Your application uses ElastiCache Redis as a cache for user profiles stored in DynamoDB. You must ensure that when a profile is updated, subsequent reads see the latest value quickly. Which cache strategy is generally the best fit for this requirement?

Accepted Answer

Use a cache-aside approach with TTL plus explicit invalidation after writes.. The cache-aside (lazy loading) pattern with TTL plus explicit invalidation ensures that after a write to DynamoDB, the stale Redis entry is removed, forcing the next read to fetch the updated profile from DynamoDB and repopulate the cache. This minimizes the window of inconsistency while keeping cache management simple and efficient for user profile workloads.

Answer

Write to DynamoDB only, and never update or invalidate the Redis cache.

Answer

Cache only for reads, and do not fetch from DynamoDB when a key is missing.

Answer

Rely on eventual consistency of Redis replication to propagate updates to all nodes.