AWS SAA-C03 Design High-Performing Architectures Practice Questions

Free SAA-C03 Design High-Performing Architectures practice test questions

8 questions from this domain with answers and explanations - different from the samples on the main AWS SAA-C03 page. Sign up free to practice the full set.

1. Question 1Design High-Performing Architectures

   A social media startup is building a real-time news feed feature. Each user's feed aggregates posts from hundreds of followed accounts. The application currently queries an Amazon RDS MySQL database, but as the user base grows to millions, feed generation latency has increased to several seconds. The data access pattern is read-heavy with the same popular posts being read thousands of times per second. Which caching strategy will most effectively reduce latency?

   • AAdd several Amazon RDS read replicas spread across multiple Availability Zones and route all feed read queries to those replicas to distribute the load
   • BEnable Amazon RDS Performance Insights to identify the slowest feed queries and then rewrite and index them to reduce execution time on the database
   • CMigrate the product catalog and feed data to Amazon DynamoDB using on-demand capacity mode to scale automatically with the read-heavy traffic pattern
   • DDeploy an Amazon ElastiCache for Redis cluster in front of the database and implement a cache-aside pattern for feed dataCorrect
   ✓ Correct answer: D

   Popular posts are being read thousands of times per second from the database, creating a bottleneck. ElastiCache for Redis caches frequently accessed data in memory, dramatically reducing database queries for popular posts. Using a cache-aside pattern, the application checks the cache first; on a miss, it fetches from the database and populates the cache. This reduces latency from seconds to milliseconds for cached reads while still serving fresh data when needed.

   Why the other options are wrong

   • ARead replicas distribute query load but still serve reads from disk-backed database engines, so they do not cut individual query latency as dramatically as an in-memory cache does for repeatedly read popular posts.
   • BPerformance Insights is a diagnostic tool that helps identify slow queries but does not by itself eliminate the fundamental cost of serving the same hot data thousands of times per second.
   • CDynamoDB suits simple key-value access, not the complex per-user aggregation across hundreds of followed accounts a personalized feed requires, and migrating alone does not add an in-memory hot-data cache.
2. Question 2Design High-Performing Architectures

   SpeedLane Gaming is deploying a real-time multiplayer game backend that requires sub-millisecond latency for reading player state data from a database. The data model uses key-value access patterns and must handle millions of requests per second. Which AWS database service should the architect choose?

   • AAmazon Redshift with concurrency scaling.
   • BAmazon Neptune for graph-based queries.
   • CAmazon RDS for PostgreSQL with read replicas.
   • DAmazon DynamoDB with DynamoDB Accelerator (DAX).Correct
   ✓ Correct answer: D

   DynamoDB with DAX is purpose-built for sub-millisecond, high-throughput key-value workloads. DynamoDB itself delivers single-digit millisecond responses at millions of requests per second, and DAX adds an in-memory caching cluster that reduces read latency to microseconds. This combination is the only AWS database option that meets the sub-millisecond and millions-of-RPS requirements described for a real-time gaming backend.

   Why the other options are wrong

   • AAmazon Redshift with concurrency scaling is an OLAP analytical data warehouse designed for complex SQL queries over large datasets - it is not suitable for key-value access patterns or sub-millisecond latency at millions of RPS.
   • BAmazon Neptune is a graph database optimized for traversing relationships and graph queries - it does not support key-value access patterns and is not designed for sub-millisecond gaming state lookups.
   • CAmazon RDS for PostgreSQL with read replicas can scale reads horizontally, but relational databases have connection limits and query overhead that prevent them from reliably achieving sub-millisecond latency at millions of requests per second.
3. Question 3Design High-Performing Architectures

   A read-heavy application on Amazon DynamoDB needs microsecond read latency without changing its existing DynamoDB API calls. Which solution fits?

   • AAmazon ElastiCache for Redis placed in front of the DynamoDB table.
   • BAmazon DynamoDB Accelerator (DAX), an in-memory cache for DynamoDB.Correct
   • CA DynamoDB global secondary index created to speed up the reads.
   • DAmazon CloudFront configured to cache the DynamoDB query responses.
   ✓ Correct answer: B

   DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that fronts DynamoDB and can cut read response times from milliseconds to microseconds for read-heavy workloads. It is API-compatible with DynamoDB, so applications gain caching with minimal code changes.

   Why the other options are wrong

   • AElastiCache would require application changes and manual cache management, unlike DAX.
   • CA global secondary index adds query flexibility but not microsecond in-memory caching.
   • DCloudFront caches web content at the edge and is not a DynamoDB read cache.
4. Question 4Design High-Performing Architectures

   Which statement correctly describes Amazon S3 Transfer Acceleration?

   • AIt speeds only uploads to a bucket and does not help download performance.
   • BIt replaces CloudFront for caching static website content across the globe.
   • CIt speeds both uploads and downloads over long distances using edge locations.Correct
   • DIt only accelerates data transfers between buckets in the same Region.
   ✓ Correct answer: C

   S3 Transfer Acceleration routes traffic through CloudFront edge locations and the optimized AWS backbone to speed long-distance transfers both to and from a bucket. It benefits geographically distant clients for uploads and downloads alike, not just uploads.

   Why the other options are wrong

   • ATransfer Acceleration improves both directions, not uploads only.
   • BIt accelerates S3 object transfer; it is not a general content caching replacement for CloudFront.
   • DIt accelerates long-distance client transfers, not just same-Region bucket-to-bucket copies.
5. Question 5Design High-Performing Architectures

   Which EC2 instance type is optimized for compute-intensive workloads?

   • AI-series (storage)
   • BC-series (e.g., C7g)Correct
   • CT-series (burstable)
   • DR-series (memory)
   ✓ Correct answer: B

   AWS C-series EC2 instances such as C5 and C6g are compute-optimized, providing a high ratio of vCPU to memory. They are designed for workloads that benefit from raw compute power, such as batch processing, high-performance web servers, scientific modeling, machine learning inference, and media encoding. The C in the family name stands for compute.

   Why the other options are wrong

   • AI-series instances are storage-optimized, designed for high random I/O workloads such as NoSQL databases and data warehousing that require very fast local NVMe SSD storage.
   • CT-series instances are burstable general-purpose instances that accumulate CPU credits during low usage and spend them during bursts; they are not suited for sustained compute-intensive workloads.
   • DR-series instances are memory-optimized, designed for workloads that process large in-memory datasets such as in-memory caches, real-time big data analytics, and high-performance databases.
6. Question 6Design High-Performing Architectures

   A dynamic API is delivered to worldwide users through Amazon CloudFront in front of an Application Load Balancer in a single Region. Users far from the Region still experience variable latency and occasional connection instability for the non-cacheable API traffic. The team wants improved, consistent performance and fast regional failover using AWS's global network. What should the architect add?

   • AAWS Global Accelerator with the load balancer as an endpointCorrect
   • BA longer CloudFront cache TTL for the API responses
   • CAmazon Route 53 latency-based routing to a single Region
   • DS3 Transfer Acceleration in front of the API
   ✓ Correct answer: A

   AWS Global Accelerator directs user traffic onto the AWS global network at the nearest edge and routes it to the load balancer over the AWS backbone, improving latency and connection stability for non-cacheable, dynamic traffic. Its static anycast IP addresses enable fast, automatic failover between regional endpoints. This complements CloudFront, which is best for cacheable content.

   Why the other options are wrong

   • BLonger TTLs cannot help because dynamic, non-cacheable API responses are not served from cache.
   • CLatency-based routing to a single Region provides no additional path optimization or backbone routing benefit.
   • DTransfer Acceleration optimizes uploads to S3 and is unrelated to a dynamic API behind an ALB.
7. Question 7Design High-Performing Architectures

   A high-traffic public REST API must handle large, spiky request volumes with consistent low latency, automatic scaling, built-in throttling, and response caching at the edge, without managing servers. Which combination of services best delivers this?

   • AAmazon API Gateway integrated with AWS LambdaCorrect
   • BA single large EC2 instance running the API process
   • CAmazon SQS polled by a fixed worker fleet
   • DAmazon EC2 in an Auto Scaling group without a load balancer
   ✓ Correct answer: A

   API Gateway scales automatically to handle spiky traffic, provides request throttling and optional response caching, and integrates with Lambda for serverless compute that scales with demand. There are no servers to manage and you pay per request/invocation. This directly meets the stated requirements.

   Why the other options are wrong

   • BA single EC2 instance has a hard capacity ceiling and no built-in throttling or edge caching.
   • CSQS with a fixed worker fleet is for asynchronous processing, not synchronous low-latency REST APIs.
   • DAn ASG without a load balancer cannot distribute API traffic or provide a stable endpoint with throttling.
8. Question 8Design High-Performing ArchitecturesSelect all that apply

   A streaming analytics platform must ingest millions of records per second from many producers and allow multiple independent consumer applications to process the same stream in near real time with ordered, replayable records. Which TWO design choices support these requirements with Amazon Kinesis Data Streams?

   • AUse multiple shards with a high-cardinality partition key to spread records evenlyCorrect
   • BUse enhanced fan-out so each consumer gets dedicated throughputCorrect
   • CSet the stream retention to the minimum and delete records immediately after reading
   • DUse a single shard to guarantee global ordering across the entire stream
   ✓ Correct answer: A, B

   Adding shards and using a well-distributed partition key spreads write load to reach millions of records per second while preserving per-shard ordering, and enhanced fan-out provides each registered consumer its own dedicated read throughput with low latency so multiple applications can read concurrently. Records remain replayable within the retention period.

   Why the other options are wrong

   • CMinimizing retention and deleting records prevents replay and reprocessing, which the requirement explicitly needs.
   • DA single shard caps throughput at one shard's limit and cannot support millions of records per second, even though it would give global ordering.

How Design High-Performing Architectures is tested

This domain holds 159 of the 675 questions in the SAA-C03 bank, about 24%. The mix is 140 single-answer multiple choice, 18 multiple-response and 1 ordering, so it is worth practising the formats as well as the content.

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