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

Question 1

Based on the exhibit, which AWS feature should the team use to minimize network latency between EC2 instances that exchange messages very frequently?

Accepted Answer

Use a cluster placement group to place instances close together.. A cluster placement group is the correct choice because it groups EC2 instances within a single Availability Zone with low-latency, high-bandwidth networking, achieving single-digit millisecond latency between instances. This is ideal for applications that exchange messages very frequently, as it minimizes network hops and maximizes throughput.

Answer

Use a spread placement group to maximize instance separation across hardware.

Answer

Use a partition placement group to distribute instances across many partitions.

Answer

Use multiple Auto Scaling groups to spread traffic across more subnets.

Question 2

A new feature stores user events in DynamoDB. Each event must be fetched by user_id and sorted by event_time. The team expects many different users and wants to avoid a single hot partition. Which partition key design is best?

Accepted Answer

Use user_id as the partition key and event_time as the sort key.. Using `user_id` as the partition key ensures each user's events are stored in a separate partition, distributing the workload evenly and avoiding hot partitions. Adding `event_time` as the sort key allows DynamoDB to efficiently retrieve events for a given user in sorted order using a Query operation, which is both fast and cost-effective.

Answer

Use a constant partition key value (for example, partition_key='events') and store user_id as an attribute.

Answer

Use event_time as the partition key and user_id as an attribute to query later.

Answer

Use a randomly generated UUID as the partition key and query by user_id using a full table scan.

Question 3

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 gp3 volume type allows you to provision baseline performance of 3,000 IOPS and 125 MiB/s regardless of volume size, and you can independently increase IOPS up to 16,000 and throughput up to 1,000 MiB/s without needing to add more storage capacity. This decoupling of performance from size means you can meet the required IOPS at a lower cost compared to gp2, where performance scales with volume size and often forces overprovisioning of capacity to achieve the needed IOPS.

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 4

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.. 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 direct and efficient architectural step to reduce the wait time for available container instances 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 5

Your company currently uses an Application Load Balancer (ALB) in front of a service that receives a large number of TCP and UDP packets (including UDP-based telemetry). During load tests, you need to support both TCP and UDP traffic at high throughput while keeping stable IP endpoints for a downstream firewall allowlist. Which change best meets these requirements?

Accepted Answer

Switch to a Network Load Balancer (NLB) configured for TCP/UDP, and use Elastic IPs to provide stable endpoint IP addresses for allowlisting.. A Network Load Balancer (NLB) operates at Layer 4 and can handle both TCP and UDP traffic natively, unlike an ALB which only supports HTTP/HTTPS and cannot forward UDP packets. By assigning Elastic IPs to the NLB, you provide stable, static IP endpoints that can be added to a downstream firewall allowlist, meeting both the protocol and throughput requirements.

Answer

Keep the ALB and add an AWS WAF Web ACL to improve throughput and add static IP support.

Answer

Replace the ALB with an API Gateway REST API to support UDP because API Gateway can forward UDP packets.

Answer

Use an Auto Scaling group with multiple EC2 instances and no load balancer to avoid any networking bottlenecks.

Question 6

A serverless API built with AWS Lambda serves latency-sensitive requests. The team observes intermittent slow responses during traffic ramp-ups and expects some users to hit the API immediately after a period of inactivity. Which configuration best reduces cold-start latency during these ramp-ups?

Accepted Answer

Enable Lambda provisioned concurrency on a published alias used by the API, and set a minimum provisioned concurrency greater than zero.. Lambda provisioned concurrency keeps a specified number of execution environments initialized and ready to respond immediately, eliminating cold starts for those invocations. By setting a minimum provisioned concurrency greater than zero on the alias used by API Gateway, the function remains warm even after periods of inactivity, ensuring consistent low latency during traffic ramp-ups.

Answer

Increase the Lambda function’s memory setting; cold starts will always be eliminated regardless of traffic patterns.

Answer

Switch the Lambda runtime to a newer language version and remove any VPC configuration so the function never cold starts.

Answer

Set an API Gateway stage variable to "warm" the function at request time, which forces immediate initialization.

Question 7

A media processing pipeline uses EBS-backed storage for an application that performs sustained random I/O with low latency requirements. During peak processing windows, the team sees increased read latency and occasional timeouts at the application layer. They need predictable, high IOPS performance rather than best-effort throughput. Which EBS configuration choice is most appropriate?

Accepted Answer

Use io1 or io2 EBS volumes configured with a high provisioned IOPS value, and attach them to EBS-optimized instances.. Io1 and io2 volumes are provisioned IOPS SSD volumes designed for sustained, predictable high IOPS performance, which directly addresses the application's need for low-latency random I/O during peak loads. Attaching them to EBS-optimized instances ensures dedicated network bandwidth for EBS traffic, eliminating contention and preventing timeouts.

Answer

Use gp2 volumes and rely on burst credits to handle peak random I/O latency requirements.

Answer

Use standard HDD (st1) volumes, because they provide high throughput and will reduce latency automatically.

Answer

Use S3 instead of EBS for random I/O latency reduction without changing the application.

Question 8

Your mobile app writes events to a single DynamoDB table with partition key = customerId and sort key = eventTime. During a promotional campaign, one tenant ("ACME") generates far more traffic than others. CloudWatch shows sustained throttling (ProvisionedThroughputExceeded) and elevated p99 latency only for that tenant. The workload pattern cannot be changed to a completely different schema, but you can change how items are partitioned. Which design change is most likely to reduce the hot-partition throttling while keeping efficient reads for ACME?

Accepted Answer

Change the partition key to a salted key such as customerId + shard number, and include the eventTime ordering using the sort key.. Salting the partition key by appending a shard number (e.g., customerId + random digit) distributes ACME's writes across multiple partitions, eliminating the hot partition. The sort key still preserves eventTime ordering, so queries for a specific customer can be parallelized across shards and merged client-side or via a composite sort key pattern, maintaining efficient reads.

Answer

Use the same partition key (customerId), but increase the table’s provisioned capacity for that tenant.

Answer

Switch to on-demand capacity mode and keep the partition key unchanged.

Answer

Enable Global Tables so that reads are served from a nearby replica for ACME.

Question 9

A marketing team uses CloudFront with an S3 origin to serve a single-page web app. After a release, CloudFront cache hit ratio dropped sharply. The app requests the same static JS and CSS assets, but each request includes a unique tracking query parameter (for example, ?utm_source=campaign123, campaign456, etc.). You want CloudFront to cache those assets efficiently even when the tracking query parameter changes. What should you do?

Accepted Answer

Update the CloudFront cache policy so the cache key ignores the tracking query parameter, while still using the path and other essential headers.. CloudFront's cache key determines whether a request is served from the cache or forwarded to the origin. By configuring a cache policy that ignores the tracking query parameter (e.g., utm_source), CloudFront treats all requests for the same asset path as identical, regardless of the unique tracking parameter. This allows the same JS and CSS files to be cached once and served for all campaign variations, restoring the cache hit ratio.

Answer

Create a cache policy that forwards the query string to the origin and varies the cache key by all query parameters.

Answer

Enable S3 origin access control and keep the existing default cache policy, because origin access changes caching behavior automatically.

Answer

Set the CloudFront Time-to-Live (TTL) to 0 seconds to ensure the origin always serves the latest asset content.

Question 10

You run a web application on an EC2 Auto Scaling group behind an Application Load Balancer (ALB). During scheduled traffic spikes, new instances launch but customers occasionally see 5xx errors for the first few minutes after scale-out. Operational logs show instances need ~4 minutes to warm up (load caches and initialize dependencies). ALB target health becomes healthy only after this warm-up. Which change most directly improves performance during spikes by reducing the time to serve traffic after scaling?

Accepted Answer

Use an Auto Scaling warm pool so instances are pre-initialized and ready to register quickly when the ASG scales out.. B is correct because a warm pool pre-initializes instances (e.g., loading caches and dependencies) before they are added to the Auto Scaling group. When the ASG scales out, these pre-warmed instances can be quickly moved into service, bypassing the ~4-minute warm-up delay and reducing the window for 5xx errors.

Answer

Configure a larger ALB deregistration delay so that old targets remain longer before termination.

Answer

Increase the number of desired instances immediately without using scaling policies, and then rely on manual reconfiguration.

Answer

Switch from ALB to NLB so instances become reachable sooner without waiting for health checks.

Question 11

A distributed system needs extremely low network latency between a set of EC2 instances running the same workload. The team wants the instances to be placed as close together as AWS allows to reduce round-trip time. Which placement strategy should the architect use?

Accepted Answer

Use a Cluster placement group for the instances that must communicate frequently over low latency.. A Cluster placement group is the correct choice because it places instances in a single Availability Zone within the same rack or logical cluster, providing the lowest possible network latency and maximum throughput (up to 10 Gbps for single-flow traffic) between instances. This is ideal for tightly coupled, latency-sensitive workloads like HPC or real-time distributed systems.

Answer

Use a Spread placement group across multiple Availability Zones to maximize fault tolerance.

Answer

Use the default placement strategy without specifying a placement group.

Answer

Use a placement group of type Partition to ensure independent failure of each instance.

Question 12

A web API runs on an Auto Scaling group (ASG) behind an Application Load Balancer (ALB). During traffic spikes, users experience request timeouts even though CPU stays below 40%. After investigation, you find the ASG often has too few healthy targets to handle the current request rate. Which change will best improve responsiveness during spikes?

Accepted Answer

Create a target tracking scaling policy using an ALB metric such as RequestCountPerTarget or TargetResponseTime.. The issue is that the ASG has too few healthy targets to handle the request rate, even though CPU is low. A target tracking scaling policy based on RequestCountPerTarget or TargetResponseTime directly aligns scaling with the ALB's view of demand, ensuring the ASG adds instances when request rates spike, regardless of CPU utilization. This addresses the root cause—insufficient capacity to serve incoming requests—rather than relying on a metric (CPU) that does not reflect the bottleneck.

Answer

Keep the ASG scaling policy based on CPU utilization, but increase the ASG min capacity by 50%.

Answer

Enable EC2 detailed monitoring for one-minute granularity and keep CPU scaling.

Answer

Switch to scaling based on the ASG network out bytes metric only, ignoring ALB response metrics.

Question 13

A DynamoDB-backed event processing system experiences throttling during a promotion. All events are written and read using the same partition key value (tenantId = "ACME"). The workload is time-ordered per tenant, and the application can tolerate slight reordering across partitions. Which design change will most directly increase throughput and reduce hot-partition throttling?

Accepted Answer

Change the partition key to include an additional sharding attribute derived from a hash of eventId.. Adding a sharding attribute derived from a hash of eventId allows writes and reads to be distributed across multiple partition keys, breaking the single hot partition caused by using tenantId='ACME' for all operations. DynamoDB's throughput is limited per partition, so distributing the load across many partitions directly reduces throttling without changing the application's tolerance for slight reordering.

Answer

Increase the table's provisioned capacity (read/write units) to handle the promotion peak.

Answer

Enable DAX caching for all reads but keep the same partition key and item layout.

Answer

Switch the table to eventually consistent reads for queries to lower read throttling.

Question 14

A team serves static assets from an S3 origin through CloudFront. Cache hit ratio is low. Analytics show that requests include an Authorization header (even though the assets are public) and the cache key currently varies on that header, causing CloudFront to treat the same asset as different cache entries. What is the best change to improve cache hit ratio without breaking access controls?

Accepted Answer

Modify the CloudFront cache policy so the cache key does not include the Authorization header.. The low cache hit ratio is caused by the Authorization header being included in the CloudFront cache key, which creates separate cache entries for the same object even though the assets are public. By modifying the cache policy to exclude the Authorization header, CloudFront will treat all requests for the same asset as identical, dramatically improving the cache hit ratio without affecting access controls because the assets are already public.

Answer

Keep Authorization in the CloudFront cache key, but increase the origin response minimum TTL to 1 day.

Answer

Switch the S3 origin from the current bucket to a website endpoint to enable automatic caching headers.

Answer

Enable CloudFront to forward all headers to S3 so origin can decide caching behavior per request.

Question 15

A containerized service fleet running on EC2 instances needs to share user-uploaded files and access them with low latency. The workload is bursty: sometimes dozens of instances concurrently read the same directory for short periods, and then traffic drops. Which Amazon EFS configuration best matches these performance needs?

Accepted Answer

Use Amazon EFS General Purpose performance mode and Throughput mode set to Bursting.. The workload is bursty with concurrent reads of the same directory, which favors the General Purpose performance mode for its strong consistency and lower latency per operation. The Bursting Throughput mode is ideal for bursty traffic as it allows the file system to accumulate burst credits during idle periods and consume them during high-demand spikes, matching the described pattern without incurring additional costs.

Answer

Use Amazon EFS Max I/O performance mode with Throughput mode set to Provisioned.

Answer

Use Amazon EFS General Purpose performance mode with Throughput mode set to Provisioned.

Answer

Use Amazon EFS Max I/O performance mode with Throughput mode set to Bursting.