SAA-C03 Design High-Performing Architectures • Complete Question Bank
Complete SAA-C03 Design High-Performing Architectures question bank — all 0 questions with answers and detailed explanations.
Current deployment summary: - 48 EC2 instances run a tightly coupled simulation engine. - Instances are spread across us-east-1a and us-east-1b. - Each worker exchanges small TCP messages every 5-10 ms with all other workers. - Measured east-west RTT: 4.9 ms average, 17.2 ms p95. - The application owner states that the workload can run in a single Availability Zone if that improves performance. - No external clients access the cluster directly.
Database storage review: - Current volume type: gp2 - Peak Read/Write IOPS observed: 9,700 - VolumeQueueLength increases during busy periods - ReadLatency reaches 8-12 ms - Requirement: provision about 10,000 IOPS without buying much extra capacity
EFS usage summary: - 25 EC2 workers mounted to one file system - Mostly small metadata reads and writes - Each request needs very low file system latency - No requirement for massive concurrent throughput across thousands of clients
CloudWatch summary for app servers: - Average CPUUtilization: 24% - Average MemoryUtilization: 91% - Average NetworkIn/Out: low - Current instance type: m6i.large - User reports: application slows when more sessions are active
CloudWatch metrics for Lambda function 'image-resize': - Average Duration: 220 ms - P95 Init Duration after idle: 1,400 ms - ConcurrentExecutions: 15 average, 60 during campaign launches - Throttles: 0 - User complaint: first upload after inactivity feels slow
Application topology: - 12 EC2 instances in one Region - Instances process small jobs and send frequent messages to each other - Observed inter-node latency: 2.8 ms to 4.1 ms - Requirement: lowest possible latency between application nodes
Drag a concept onto its matching description — or click a concept then click the description.
Scale the Auto Scaling group on ALB RequestCountPerTarget.
Scale on SQS queue depth using a custom CloudWatch metric.
Use scheduled scaling to add capacity before the recurring surge.
Use target tracking on EC2 CPUUtilization.
ALB and ASG snapshot (15-minute peak): - RequestCountPerTarget: 1,920 - TargetResponseTime p95: 2.9 seconds - HTTPCode_Target_5XX_Count: 0 EC2 application metrics from CloudWatch agent: - CPUUtilization: 33% - MemoryUtilization: 46% - NetworkIn/Out: steady Application logs: [WARN] worker queue depth reached 5,000 [INFO] rejecting requests after thread pool saturation Current Auto Scaling policy: - Target tracking on CPUUtilization = 55%
CloudFront behavior summary for path pattern /static/*: - Allowed methods: GET, HEAD - Cache policy: forwards all query strings - Origin request policy: forwards all cookies and the Authorization header - Average cache hit ratio: 11% Sample request log lines: GET /static/app.js?v=18&userId=123 Cookie: session=abcd GET /static/app.js?v=18&userId=987 Cookie: session=xyzt GET /static/logo.svg?v=18&locale=en Cookie: session=mnop Origin responses: - All objects are identical for every viewer - Objects are versioned only by the v query parameter
Amazon RDS for PostgreSQL metrics during the end-of-day report window: - CPUUtilization: 24% - ReadLatency: 118 ms - WriteLatency: 7 ms - DiskQueueDepth: 0.4 - FreeStorageSpace: stable Application notes: - Report queries are read-only and run for 20 to 30 minutes - The operational API continues to perform writes during the report window - Business accepts slightly stale report data if write performance stays unchanged
Deployment notes for a media-processing Auto Scaling group: - 6 EC2 instances across 2 Availability Zones - Each node compiles project artifacts and writes them to /workspace/output - Other nodes must immediately see the same files for the next pipeline stage - Files must persist when an instance is replaced or scaled in/out - Logs show failures such as: [ERROR] missing artifact: /workspace/output/frame_2048.png [WARN] local copy not found after instance termination
DynamoDB metrics and access pattern: - Table mode: on-demand - ConsumedReadCapacityUnits: steady, no throttling overall - SuccessfulRequestLatency: p95 = 34 ms - Hot partition key detected: tenant#42 consumes 92% of read traffic during peak Application notes: - Requests repeatedly fetch the same dashboard items for up to 60 seconds - Reads are eventually consistent and the application can tolerate brief cache staleness - Writes are infrequent and do not dominate the workload
Drag a concept onto its matching description — or click a concept then click the description.
Use CloudFront Origin Access Control and allow only the distribution in the bucket policy.
Use versioned object filenames or hashed asset names with a long TTL.
Exclude the tracking query string from the cache key with a cache policy.
Use CloudFront signed URLs or signed cookies.
fio benchmark on the selected EC2 family: - Device: /dev/nvme1n1 - 4 KiB random read IOPS: 710,000 - Average latency: 0.18 ms - Sequential throughput: 2.8 GiB/s Workload notes: - Workers download source video files from S3 - They generate temporary frame extracts and intermediate artifacts locally - Final MP4 outputs are uploaded to S3 immediately after processing - If an instance terminates, the job is retried from the original source file
Drag a concept onto its matching description — or click a concept then click the description.
Scale the Auto Scaling group on ALB RequestCountPerTarget.
Scale on SQS queue depth using a custom CloudWatch metric.
Use scheduled scaling to add capacity before the recurring surge.
Use target tracking on EC2 CPUUtilization.
ALB and ASG snapshot (15-minute peak): - RequestCountPerTarget: 1,920 - TargetResponseTime p95: 2.9 seconds - HTTPCode_Target_5XX_Count: 0 EC2 application metrics from CloudWatch agent: - CPUUtilization: 33% - MemoryUtilization: 46% - NetworkIn/Out: steady Application logs: [WARN] worker queue depth reached 5,000 [INFO] rejecting requests after thread pool saturation Current Auto Scaling policy: - Target tracking on CPUUtilization = 55%
fio benchmark on the selected EC2 family: - Device: /dev/nvme1n1 - 4 KiB random read IOPS: 710,000 - Average latency: 0.18 ms - Sequential throughput: 2.8 GiB/s Workload notes: - Workers download source video files from S3 - They generate temporary frame extracts and intermediate artifacts locally - Final MP4 outputs are uploaded to S3 immediately after processing - If an instance terminates, the job is retried from the original source file
DynamoDB metrics and access pattern: - Table mode: on-demand - ConsumedReadCapacityUnits: steady, no throttling overall - SuccessfulRequestLatency: p95 = 34 ms - Hot partition key detected: tenant#42 consumes 92% of read traffic during peak Application notes: - Requests repeatedly fetch the same dashboard items for up to 60 seconds - Reads are eventually consistent and the application can tolerate brief cache staleness - Writes are infrequent and do not dominate the workload
CloudFront behavior summary for path pattern /static/*: - Allowed methods: GET, HEAD - Cache policy: forwards all query strings - Origin request policy: forwards all cookies and the Authorization header - Average cache hit ratio: 11% Sample request log lines: GET /static/app.js?v=18&userId=123 Cookie: session=abcd GET /static/app.js?v=18&userId=987 Cookie: session=xyzt GET /static/logo.svg?v=18&locale=en Cookie: session=mnop Origin responses: - All objects are identical for every viewer - Objects are versioned only by the v query parameter
Drag a concept onto its matching description — or click a concept then click the description.
Use CloudFront Origin Access Control and allow only the distribution in the bucket policy.
Use versioned object filenames or hashed asset names with a long TTL.
Exclude the tracking query string from the cache key with a cache policy.
Use CloudFront signed URLs or signed cookies.
Amazon RDS for PostgreSQL metrics during the end-of-day report window: - CPUUtilization: 24% - ReadLatency: 118 ms - WriteLatency: 7 ms - DiskQueueDepth: 0.4 - FreeStorageSpace: stable Application notes: - Report queries are read-only and run for 20 to 30 minutes - The operational API continues to perform writes during the report window - Business accepts slightly stale report data if write performance stays unchanged
Deployment notes for a media-processing Auto Scaling group: - 6 EC2 instances across 2 Availability Zones - Each node compiles project artifacts and writes them to /workspace/output - Other nodes must immediately see the same files for the next pipeline stage - Files must persist when an instance is replaced or scaled in/out - Logs show failures such as: [ERROR] missing artifact: /workspace/output/frame_2048.png [WARN] local copy not found after instance termination
CloudWatch metrics for Lambda function 'image-resize': - Average Duration: 220 ms - P95 Init Duration after idle: 1,400 ms - ConcurrentExecutions: 15 average, 60 during campaign launches - Throttles: 0 - User complaint: first upload after inactivity feels slow
CloudWatch summary for app servers: - Average CPUUtilization: 24% - Average MemoryUtilization: 91% - Average NetworkIn/Out: low - Current instance type: m6i.large - User reports: application slows when more sessions are active
EFS usage summary: - 25 EC2 workers mounted to one file system - Mostly small metadata reads and writes - Each request needs very low file system latency - No requirement for massive concurrent throughput across thousands of clients
Application topology: - 12 EC2 instances in one Region - Instances process small jobs and send frequent messages to each other - Observed inter-node latency: 2.8 ms to 4.1 ms - Requirement: lowest possible latency between application nodes
Database storage review: - Current volume type: gp2 - Peak Read/Write IOPS observed: 9,700 - VolumeQueueLength increases during busy periods - ReadLatency reaches 8-12 ms - Requirement: provision about 10,000 IOPS without buying much extra capacity
CloudFront access log sample: 2026-04-18T09:12:41Z LAX1 1234 Miss GET d111111abcdef8.cloudfront.net /app/v42/main.8f3d2.js 200 - Mozilla/5.0 Authorization=Bearer eyJhbGciOi... 2026-04-18T09:12:42Z LAX1 1235 Miss GET d111111abcdef8.cloudfront.net /app/v42/vendor.9c1a0.css 200 - Mozilla/5.0 Authorization=Bearer eyJhbGciOi... Distribution behavior summary: - Origin: S3 bucket - Cache policy: legacy default - Origin request policy: forwards all headers, cookies, and query strings - Objects are immutable after release and have content-hash file names
Load-test observations: - DynamoDB table type: on-demand - Primary access pattern: GetItem for 200 hot keys - p95 latency without cache: 17-24 ms - p95 latency under burst: 31 ms and rising - Sample application note: "A few seconds of staleness is acceptable for dashboards and recommendations" - CloudWatch: ConsumedReadCapacityUnits spikes during refresh cycles
Aurora cluster summary: - 1 writer instance: db.r6g.large - 2 reader instances: db.r6g.large - Writer CPU avg: 82% / p95 91% - Reader CPU avg: 18% / p95 26% - Database connections: 480 total, all established to the cluster writer endpoint - Query sample: 72% SELECT, 22% INSERT/UPDATE, 6% administrative queries
Lambda logs: REPORT RequestId: 9d6b... Duration: 184.27 ms Billed Duration: 185 ms Memory Size: 1024 MB Max Memory Used: 612 MB Init Duration: 812.43 ms Traffic pattern: - Low traffic outside weekdays 09:00-09:15 UTC - Predictable spike every weekday - Function language: Python 3.12 - No need to keep spare capacity all day
Protocol and traffic notes: - Transport: TCP over port 9000 - Payload: custom binary messages, not HTTP - Requirement: preserve source IP address at the target - Requirement: minimize latency and jitter - Targets: EC2 instances in private subnets across 3 AZs - Current proxy layer adds ~12 ms overhead and breaks client IP logging
fio benchmark from the current volume: - 4 KiB random read IOPS target: 22,000 - 4 KiB random write IOPS target: 18,000 - 99th percentile latency target: < 2 ms - Current volume: gp3, 12,000 provisioned IOPS - Observed latency during peak: 3.8-5.4 ms - Data must remain attached to one EC2 instance and persist after stop/start
Network test results: - Average node-to-node RTT: 180-240 microseconds - Jitter spikes during busy periods: up to 4 ms - Workload type: cluster-style analytics with frequent small messages - Requirement: lowest possible latency among peers - Deployment note: all 10 instances are currently in separate subnets within one AZ
Benchmark summary from current fleet: - Current instances: c6i.2xlarge - Average CPU during processing: 88%-96% - Disk and network utilization remain below 30% - Application runtime on test ARM build: 11% faster than x86 build - Engineering note: binaries are already compatible with ARM64 - Business goal: lower cost while keeping or improving throughput
CloudWatch metrics for the Auto Scaling group (5-minute period): - CPUUtilization: 28% average - NetworkIn: 190 MB/min average, no saturation - GroupDesiredCapacity: 4 - ALBRequestCountPerTarget: 4,800 during peaks - TargetResponseTime p95: 2.7 seconds during peaks ALB access log sample: 2026-04-28T09:02:11Z app/prod-alb 203.0.113.10:443 10.0.1.21:8080 0.000 2.698 0.000 200 200 1843 1920 "GET https://app.example.com/search?q=aws HTTP/1.1"
Table schema: - TableName: EventStore - PartitionKey: tenantId (String) - SortKey: eventTime (Number) CloudWatch metrics during promotion: - WriteThrottleEvents: increasing steadily - ConsumedWriteCapacityUnits: near provisioned limit - SuccessfulRequestLatency p95: 14 ms Sample traffic distribution: - tenantId=ACME: 82% of writes, 79% of reads - all other tenants combined: 18% of writes, 21% of reads Application note: - Queries must continue to support tenant-scoped lookups by time range.
Aurora cluster configuration: - 1 writer instance - 1 reader instance - Application JDBC string: jdbc:mysql://cluster-writer.endpoint.example.com:3306/orders CloudWatch metrics (peak hour): - DBWriterCPUUtilization: 84% - DBReaderCPUUtilization: 17% - DatabaseConnections: steady - ReadLatency p95: 38 ms - WriteLatency p95: 9 ms Application trace sample: SELECT order_id, status, total FROM orders WHERE customer_id=? ORDER BY created_at DESC LIMIT 20
CloudFront distribution settings excerpt: - Cache policy: custom - Headers included in cache key: Authorization, CloudFront-Viewer-Country - Query strings included in cache key: all - Cookies included in cache key: none Origin request sample: GET /app.8f3a2c1.js?v=20260428 HTTP/1.1 Host: d123.cloudfront.net Authorization: Bearer eyJhbGciOi... User-Agent: Mozilla/5.0 CloudFront analytics: - CacheHitRate: 18% - OriginFetches: spike immediately after each deploy - Origin bytes out: high for unchanged JS and CSS files
DynamoDB access pattern report: - TableName: SessionState - Read pattern: GetItem on the same 500 keys during active sessions - Read frequency: 1.2 million reads/minute during peak periods - Cacheability: yes, stale data up to 5 seconds is acceptable CloudWatch metrics: - ConsumedReadCapacityUnits: 92% of provisioned limit - SuccessfulRequestLatency p95: 7.5 ms - ThrottledRequests: intermittent during peaks Application note: - Writes are comparatively rare and do not need multi-Region replication.
Lambda monitoring and deployment notes: - Function: checkout-api-prod - Current alias: live - Invocations per day: low except weekdays 09:00-09:15 UTC - REPORT log sample at 09:00 UTC: Init Duration: 842.31 ms Duration: 128.42 ms Billed Duration: 1000 ms - REPORT log sample at 09:05 UTC: Init Duration: 0.00 ms Duration: 121.77 ms Traffic pattern: - Spikes are predictable and last about 15 minutes - No need to keep high concurrency all day
Topology notes: - 12 x Amazon EC2 c6i.large instances - All instances run in us-east-1a - Current network path between nodes averages 0.9 ms and occasionally spikes above 2 ms - Workload logs: "gossip sync lag detected" and "broadcast step exceeded SLA" - Requirement: minimize latency and jitter between nodes, not maximize fault isolation
Amazon CloudWatch metrics for the instance volume: - VolumeType: gp2 - VolumeSize: 1 TiB - ReadOps: 9,000-11,000 sustained - WriteOps: 8,000-10,000 sustained - BurstBalance: 0% for long periods - VolumeQueueLength: elevated during peak use - VolumeReadLatency p95: 23 ms - VolumeWriteLatency p95: 19 ms Application note: - The working set is random and latency-sensitive - The storage requirement is persistent block storage attached to one instance
Drag steps to the numbered slots on the right, or tap a step then tap a slot.
Drag steps to the numbered slots on the right, or tap a step then tap a slot.