SAA-C03 Design High-Performing Architectures Practice Test 8 — 15 Questions

Question 1

A static website stores assets in S3 and is delivered through CloudFront. Analytics show low cache hit ratio, many origin fetches for the same JavaScript bundles, and elevated S3 GET request costs. Most requests include unnecessary cookies, and the text assets are uncompressed. Which changes should the team make? Select three.

Accepted Answer

Configure a CloudFront cache policy that excludes unnecessary cookies and headers from the cache key.. Option A is correct because a CloudFront cache policy that excludes unnecessary cookies and headers from the cache key prevents CloudFront from creating multiple cache entries for the same object based on varying cookie values. This increases the cache hit ratio by ensuring that identical JavaScript bundles are served from the edge cache rather than triggering separate origin fetches for each unique request, thereby reducing S3 GET request costs.

Answer

Switch the origin to an Application Load Balancer so CloudFront can cache the assets more effectively.

Answer

Disable caching so viewers always retrieve the newest version directly from S3.

Question 2

A latency-sensitive telemetry service uses a custom TCP protocol on EC2 instances in private subnets. The service must preserve the client source IP for rate limiting, avoid HTTP header inspection, and keep per-request overhead as low as possible. Which changes should the team make? Select three.

Accepted Answer

Use a Network Load Balancer in front of the service.. Option A is correct because a Network Load Balancer (NLB) operates at Layer 4 and preserves the client source IP by default when instances are registered as targets. This allows the telemetry service to use the original IP for rate limiting without requiring HTTP header inspection, which is critical for a custom TCP protocol. NLB also introduces minimal latency and low per-request overhead, making it ideal for latency-sensitive workloads.

Answer

Use an Application Load Balancer because path-based routing improves throughput for binary protocols.

Answer

Expose the service through API Gateway because it supports raw TCP and UDP pass-through.

Question 3

A customer portal uses Amazon Aurora MySQL. The application currently sends all SELECT queries to the writer instance endpoint. During traffic spikes, read latency increases, and the team wants the cluster to survive a writer failover without manual endpoint changes for the application. Which changes should the team make? Select three.

Accepted Answer

Replace the hard-coded DB instance endpoint with the Aurora reader endpoint for read traffic.. Option A is correct because the Aurora reader endpoint automatically distributes read-only connections across all available Aurora Replicas, including the writer instance if it is configured to accept reads. This eliminates the need for manual endpoint changes during a failover, as the reader endpoint remains constant while the underlying instances change.

Answer

Keep sending all traffic to the writer endpoint because it always has the freshest data.

Answer

Replace Aurora with a single larger RDS instance and continue using the same read pattern.

Question 4

A serverless checkout API runs on AWS Lambda behind API Gateway. Traffic spikes are predictable every weekday at 09:00 UTC, and p95 latency jumps for the first few minutes after each deployment because execution environments are cold. The team wants to reduce this startup impact without changing the API contract. Which changes should they make? Select three.

Accepted Answer

Configure provisioned concurrency on the production Lambda alias during the busy windows.. Provisioned concurrency initializes a specified number of execution environments in advance, so when traffic spikes at 09:00 UTC, the Lambda function is already warm and can serve requests without cold start latency. This directly addresses the p95 latency jump after deployment without altering the API contract.

Answer

Replace provisioned concurrency with reserved concurrency because reserved concurrency keeps instances warm.

Answer

Increase the function timeout so the first request has more time to warm up.

Question 5

A low-latency market-data engine runs 10 EC2 instances that exchange small messages thousands of times per second. The team wants the lowest possible network latency and jitter, and they can tolerate single-AZ placement for this tier because another layer handles disaster recovery. Which changes should they make? Select three.

Accepted Answer

Use a cluster placement group for the instances.. A cluster placement group is designed for low-latency, high-throughput scenarios by ensuring instances are in close proximity within a single Availability Zone, which minimizes network latency and jitter. This directly meets the requirement for the lowest possible network latency and jitter for the market-data engine.

Answer

Use a spread placement group to maximize low-latency communication across the fleet.

Answer

Distribute the instances across multiple Availability Zones to reduce intra-cluster latency.

Question 6

Multiple EC2 instances need a shared filesystem so they can concurrently read and write the same files (for example, user uploads and rendered assets). The instances are in different Availability Zones and must mount the filesystem using NFS. Which AWS storage service best fits?

Accepted Answer

Amazon EFS. Amazon EFS is a fully managed NFS file system that supports concurrent read/write access from multiple EC2 instances across different Availability Zones. It uses the NFSv4.1 protocol, making it the only AWS storage service that provides a shared POSIX-compliant filesystem mountable via NFS for multi-AZ workloads.

Answer

Amazon S3

Answer

Amazon EBS gp3 volumes

Answer

Instance store on EC2

Question 7

A latency-sensitive trading workload runs on 6 EC2 instances. You must distribute the instances so they do NOT share the same underlying hardware rack, reducing the risk of correlated rack-level faults. Which EC2 placement group strategy best meets this requirement?

Accepted Answer

Spread placement group. A Spread placement group is the correct choice because it ensures each EC2 instance is placed on distinct underlying hardware (different racks), eliminating shared fault domains. This directly meets the requirement to avoid correlated rack-level failures for latency-sensitive trading workloads.

Answer

Cluster placement group

Answer

Partition placement group

Answer

No placement group, rely on the default scheduler

Question 8

A team wants to run containerized services with AWS-managed orchestration and autoscaling. They do NOT require Kubernetes compatibility. Which AWS service choice is most appropriate to meet these goals?

Accepted Answer

Amazon ECS. Amazon ECS is the most appropriate choice because it provides AWS-managed container orchestration and autoscaling without requiring Kubernetes compatibility. ECS integrates natively with AWS services like Application Auto Scaling and CloudWatch to automatically scale container tasks based on metrics such as CPU or memory utilization, meeting the team's requirements directly.

Answer

Amazon EKS

Answer

An EC2 Auto Scaling group only

Answer

Amazon SQS as the compute layer

Question 9

Your web application runs on EC2 instances behind an Application Load Balancer (ALB). During traffic spikes, p95 response time increases, but average CPU utilization remains below 40%. The current Auto Scaling policy scales based on average CPU%. What should you change to improve performance during spikes?

Accepted Answer

Scale on a request-driven metric such as ALB RequestCount per target (or target-group request rate). The p95 response time is increasing during traffic spikes while CPU utilization remains low, indicating that the bottleneck is not compute capacity but rather request handling or connection overhead. By scaling on ALB RequestCountPerTarget, you directly target the metric causing latency—each target's request load—rather than an indirect metric like CPU. This ensures that new instances are launched precisely when individual targets are overwhelmed by requests, reducing queueing delays and improving response times.

Answer

Keep scaling on CPU% to avoid over-scaling

Answer

Disable scaling and manually increase capacity during business hours

Answer

Scale only when network packet drops fall below a threshold

Question 10

A company serves public JavaScript and CSS files from S3 using CloudFront. After a frontend change, customers report a low CloudFront cache hit ratio. Requests now include an Authorization header, but these assets do not require authentication. The CloudFront distribution is configured such that Authorization is included in the cache key. Which change best maximizes cache reuse?

Accepted Answer

Use a CloudFront Cache Policy that excludes Authorization from the cache key. Option B is correct because excluding the Authorization header from the cache key ensures that all users, regardless of their authentication token, receive the same cached object. Since the static assets (JavaScript/CSS) do not require authentication, including Authorization in the cache key creates multiple cache entries for the same file, drastically reducing the cache hit ratio. A CloudFront cache policy that omits Authorization from the cache key maximizes reuse while still allowing the header to be forwarded to the origin if needed.

Answer

Include the Authorization header in the cache key so responses vary correctly

Answer

Disable caching and always fetch from S3

Answer

Forward all headers and cookies to the origin to improve correctness

Question 11

An application repeatedly reads the same DynamoDB items with very low latency requirements. The application can tolerate slightly stale data (for example, within a few seconds). You want to improve read latency without changing the existing DynamoDB table schema. Which service is the best choice?

Accepted Answer

Amazon DAX. Amazon DAX (DynamoDB Accelerator) is an in-memory cache that sits between your application and DynamoDB, providing microsecond read latency for frequently accessed items. Since the application can tolerate slightly stale data (within seconds), DAX's default TTL-based caching is ideal because it reduces read pressure on DynamoDB while serving cached results with significantly lower latency than direct DynamoDB reads.

Answer

Amazon S3 Transfer Acceleration

Answer

Amazon EFS

Answer

AWS CloudTrail for data plane reads

Question 12

A web application uses an Amazon Aurora DB cluster. The workload is becoming read-heavy, and the application team wants to increase read throughput without changing the database schema. They can adjust the application to route reads differently. What should they do?

Accepted Answer

Add Aurora read replicas and route read queries to the cluster reader endpoint. Adding Aurora read replicas and routing read queries to the cluster reader endpoint is the correct approach because Aurora replicas share the same underlying storage volume as the primary instance, so they can serve read traffic with minimal replication lag. The reader endpoint automatically load-balances connections across all available replicas, increasing aggregate read throughput without requiring any schema changes.

Answer

Switch the cluster to Multi-AZ with a longer failover target clock

Answer

Move all reads to the writer endpoint to reduce connection overhead

Answer

Disable automated backups to reduce storage overhead and speed reads

Question 13

A multi-tenant event system writes and reads data in DynamoDB. One tenant generates most of the traffic, causing throttling on a single partition key value, and the dashboards repeatedly read the most recent items for that tenant. Which two changes should the team make to improve performance? Select two.

Accepted Answer

Shard the hot tenant’s writes across multiple partition key values so traffic is spread across partitions.. Option A is correct because sharding the hot tenant's writes across multiple partition key values (e.g., by appending a random suffix or a timestamp-based suffix) distributes the write traffic across multiple physical partitions, avoiding throttling on a single partition. This is a common DynamoDB design pattern for mitigating hot keys, as each partition has its own throughput limits (e.g., up to 3,000 RCU or 1,000 WCU for a partition). By spreading writes, the system can achieve higher aggregate throughput without hitting per-partition limits.

Answer

Switch the table to on-demand capacity mode so DynamoDB automatically removes partition limits.

Answer

Use a larger sort key attribute to increase the maximum write throughput for the tenant.

Answer

Move the table to a single larger provisioned throughput setting and keep the same key design.

Question 14

A distributed analytics platform runs on 12 EC2 instances in one Availability Zone. The nodes exchange a very high volume of east-west messages and the team wants the lowest possible network latency between instances. Which two changes should the architect make first? Select two.

Accepted Answer

Place the instances in a cluster placement group so AWS keeps them physically close together.. A cluster placement group is the correct choice because it ensures EC2 instances are placed in a single Availability Zone and are physically close together, which minimizes network latency and maximizes throughput for high-volume east-west traffic. This is the lowest-latency placement group option available, as it groups instances within a single rack or cluster of racks, reducing the number of network hops.

Answer

Spread the instances across multiple Availability Zones to reduce the chance of correlated failure.

Answer

Use a spread placement group so each instance lands on different underlying hardware.

Answer

Move the workload to burstable T-series instances to absorb short traffic spikes economically.

Question 15

A marketing site serves versioned JavaScript and CSS from an Amazon S3 origin through Amazon CloudFront. After each release, the cache hit ratio drops sharply because clients keep sending request headers and query strings that are not needed for asset retrieval. Which two changes should improve cache efficiency the most? Select two.

Accepted Answer

Create a CloudFront cache policy that excludes unnecessary headers, query strings, and cookies from the cache key.. Option A is correct because CloudFront cache policies allow you to explicitly control which headers, query strings, and cookies are included in the cache key. By excluding unnecessary ones (e.g., User-Agent, random query parameters), you prevent cache fragmentation and ensure that identical assets served with different request metadata map to the same cached object, dramatically improving the cache hit ratio.

Answer

Move the S3 origin behind an Application Load Balancer so CloudFront can cache responses more effectively.

Answer

Store the objects in Amazon S3 Standard-IA so repeated requests are cheaper.

Answer

Lower the CloudFront TTL to zero so viewers always receive the newest content immediately.