Amazon AWS Certified Solutions Architect - Associate SAA-C03 Bundle

The option Use appropriate metric windows and cooldowns/warmup settings addresses a separate condition: a service CPU metric has periodic spikes that trigger needless rapid scaling. Scaling stabilization prevents thrashing. The actual requirement is the autoscaling group cannot launch more instances because all subnet IPs are exhausted. Recommended corrective action: Expand subnet IP capacity or placement design before further scale-out. Scale-out requires free addresses in selected subnets.

For the alternative failure a scheduled ETL job creates a predictable burst of API calls each night, the control Pre-scale capacity with scheduled actions around the ETL window is relevant: scheduled scale reduces predictable burst delays. Here the evidence instead is the autoscaling group cannot launch more instances because all subnet IPs are exhausted. The selected technical mechanism is Expand subnet IP capacity or placement design before further scale-out: scale-out requires free addresses in selected subnets.

Use backlog-per-consumer or oldest-message age scaling signals solves a different operational problem where queue lag grows despite average CPU below 20 percent. Queue lag measures processing shortage directly. It does not directly address the autoscaling group cannot launch more instances because all subnet IPs are exhausted. The case calls for Expand subnet IP capacity or placement design before further scale-out, since scale-out requires free addresses in selected subnets.

Configure Global Accelerator TCP endpoint groups and health-aware regional routing would help if an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays. Anycast traffic enters the AWS global network and reaches healthy TCP endpoints. That is not the symptom described here: static assets cause repeated long-haul requests to a regional origin. The matching response is Serve the content through CloudFront caching at edge locations, because edge caches reduce repeat request distance.

For the alternative failure an HTTP endpoint needs origin request optimization and API caching of safe responses, the control Configure caching rules only for suitable methods and authorization boundaries is relevant: hTTP cache design must avoid leaking user-specific responses. Here the evidence instead is static assets cause repeated long-haul requests to a regional origin. The selected technical mechanism is Serve the content through CloudFront caching at edge locations: edge caches reduce repeat request distance.

Enable dual-stack support on eligible load balancer or CloudFront front end solves a different operational problem where a public internet application must accept IPv6 client traffic at the edge. IPv6 entry needs an explicitly supported edge listener. It does not directly address static assets cause repeated long-haul requests to a regional origin. The case calls for Serve the content through CloudFront caching at edge locations, since edge caches reduce repeat request distance.

Configure caching rules only for suitable methods and authorization boundaries solves a different operational problem where an HTTP endpoint needs origin request optimization and API caching of safe responses. HTTP cache design must avoid leaking user-specific responses. It does not directly address an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays. The case calls for Configure Global Accelerator TCP endpoint groups and health-aware regional routing, since anycast traffic enters the AWS global network and reaches healthy TCP endpoints.

The competing option Enable dual-stack support on eligible load balancer or CloudFront front end would be useful when a public internet application must accept IPv6 client traffic at the edge. IPv6 entry needs an explicitly supported edge listener. The present issue is an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays; it is more directly addressed by Configure Global Accelerator TCP endpoint groups and health-aware regional routing. Anycast traffic enters the AWS global network and reaches healthy TCP endpoints.

The option Serve the content through CloudFront caching at edge locations addresses a separate condition: static assets cause repeated long-haul requests to a regional origin. Edge caches reduce repeat request distance. The actual requirement is an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays. Recommended corrective action: Configure Global Accelerator TCP endpoint groups and health-aware regional routing. Anycast traffic enters the AWS global network and reaches healthy TCP endpoints.

Enable dual-stack support on eligible load balancer or CloudFront front end solves a different operational problem where a public internet application must accept IPv6 client traffic at the edge. IPv6 entry needs an explicitly supported edge listener. It does not directly address dNS-based latency routing should choose the closest healthy regional endpoint. The case calls for Use Route 53 latency records and health checks, since latency-based policies route DNS responses by measured latency.

The competing option Configure Global Accelerator TCP endpoint groups and health-aware regional routing would be useful when an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays. Anycast traffic enters the AWS global network and reaches healthy TCP endpoints. The present issue is dNS-based latency routing should choose the closest healthy regional endpoint; it is more directly addressed by Use Route 53 latency records and health checks. Latency-based policies route DNS responses by measured latency.

Serve the content through CloudFront caching at edge locations would help if static assets cause repeated long-haul requests to a regional origin. Edge caches reduce repeat request distance. That is not the symptom described here: dNS-based latency routing should choose the closest healthy regional endpoint. The matching response is Use Route 53 latency records and health checks, because latency-based policies route DNS responses by measured latency.

The competing option Serve the content through CloudFront caching at edge locations would be useful when static assets cause repeated long-haul requests to a regional origin. Edge caches reduce repeat request distance. The present issue is an HTTP endpoint needs origin request optimization and API caching of safe responses; it is more directly addressed by Configure caching rules only for suitable methods and authorization boundaries. HTTP cache design must avoid leaking user-specific responses.

The option Configure Global Accelerator TCP endpoint groups and health-aware regional routing addresses a separate condition: an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays. Anycast traffic enters the AWS global network and reaches healthy TCP endpoints. The actual requirement is an HTTP endpoint needs origin request optimization and API caching of safe responses. Recommended corrective action: Configure caching rules only for suitable methods and authorization boundaries. HTTP cache design must avoid leaking user-specific responses.

For the alternative failure a public internet application must accept IPv6 client traffic at the edge, the control Enable dual-stack support on eligible load balancer or CloudFront front end is relevant: iPv6 entry needs an explicitly supported edge listener. Here the evidence instead is an HTTP endpoint needs origin request optimization and API caching of safe responses. The selected technical mechanism is Configure caching rules only for suitable methods and authorization boundaries: hTTP cache design must avoid leaking user-specific responses.

The option Configure Global Accelerator TCP endpoint groups and health-aware regional routing addresses a separate condition: an interactive non-HTTP TCP client needs faster regional connectivity without static-origin DNS cache delays. Anycast traffic enters the AWS global network and reaches healthy TCP endpoints. The actual requirement is a public internet application must accept IPv6 client traffic at the edge. Recommended corrective action: Enable dual-stack support on eligible load balancer or CloudFront front end. IPv6 entry needs an explicitly supported edge listener.

Use Route 53 latency records and health checks would help if dNS-based latency routing should choose the closest healthy regional endpoint. Latency-based policies route DNS responses by measured latency. That is not the symptom described here: a public internet application must accept IPv6 client traffic at the edge. The matching response is Enable dual-stack support on eligible load balancer or CloudFront front end, because iPv6 entry needs an explicitly supported edge listener.

For the alternative failure static assets cause repeated long-haul requests to a regional origin, the control Serve the content through CloudFront caching at edge locations is relevant: edge caches reduce repeat request distance. Here the evidence instead is a public internet application must accept IPv6 client traffic at the edge. The selected technical mechanism is Enable dual-stack support on eligible load balancer or CloudFront front end: iPv6 entry needs an explicitly supported edge listener.

Use supported enhanced networking ENA adapters and suitable instances would help if a packet-processing application requires high packets per second and low overhead. ENA improves EC2 network datapath efficiency. That is not the symptom described here: instances have high latency because the selected type has low baseline networking. The matching response is Choose instance types with adequate network performance after load testing, because eC2 bandwidth capacity differs by family and size.

For the alternative failure a storage-intensive job uses EBS volumes whose performance exceeds instance EBS throughput, the control Scale instance EBS bandwidth or rebalance volume throughput is relevant: instance throughput limits cap total EBS I/O. Here the evidence instead is instances have high latency because the selected type has low baseline networking. The selected technical mechanism is Choose instance types with adequate network performance after load testing: eC2 bandwidth capacity differs by family and size.

The competing option Co-locate tightly coupled chatty components when resilience permits would be useful when a compute-heavy worker has an expensive data transfer pattern across AZs. Cross-AZ traffic adds latency and data transfer charges. The present issue is instances have high latency because the selected type has low baseline networking; it is more directly addressed by Choose instance types with adequate network performance after load testing. EC2 bandwidth capacity differs by family and size.

For the alternative failure a storage-intensive job uses EBS volumes whose performance exceeds instance EBS throughput, the control Scale instance EBS bandwidth or rebalance volume throughput is relevant: instance throughput limits cap total EBS I/O. Here the evidence instead is a packet-processing application requires high packets per second and low overhead. The selected technical mechanism is Use supported enhanced networking ENA adapters and suitable instances: eNA improves EC2 network datapath efficiency.

Co-locate tightly coupled chatty components when resilience permits solves a different operational problem where a compute-heavy worker has an expensive data transfer pattern across AZs. Cross-AZ traffic adds latency and data transfer charges. It does not directly address a packet-processing application requires high packets per second and low overhead. The case calls for Use supported enhanced networking ENA adapters and suitable instances, since eNA improves EC2 network datapath efficiency.

The option Use a cluster placement group and compatible high-performance instances addresses a separate condition: two tightly coupled HPC workers need very low latency within one AZ. Placement groups can place supported instances close together. The actual requirement is a packet-processing application requires high packets per second and low overhead. Recommended corrective action: Use supported enhanced networking ENA adapters and suitable instances. ENA improves EC2 network datapath efficiency.

Use supported enhanced networking ENA adapters and suitable instances solves a different operational problem where a packet-processing application requires high packets per second and low overhead. ENA improves EC2 network datapath efficiency. It does not directly address two tightly coupled HPC workers need very low latency within one AZ. The case calls for Use a cluster placement group and compatible high-performance instances, since placement groups can place supported instances close together.

The competing option Choose instance types with adequate network performance after load testing would be useful when instances have high latency because the selected type has low baseline networking. EC2 bandwidth capacity differs by family and size. The present issue is two tightly coupled HPC workers need very low latency within one AZ; it is more directly addressed by Use a cluster placement group and compatible high-performance instances. Placement groups can place supported instances close together.

The option Co-locate tightly coupled chatty components when resilience permits addresses a separate condition: a compute-heavy worker has an expensive data transfer pattern across AZs. Cross-AZ traffic adds latency and data transfer charges. The actual requirement is two tightly coupled HPC workers need very low latency within one AZ. Recommended corrective action: Use a cluster placement group and compatible high-performance instances. Placement groups can place supported instances close together.

The competing option Use supported enhanced networking ENA adapters and suitable instances would be useful when a packet-processing application requires high packets per second and low overhead. ENA improves EC2 network datapath efficiency. The present issue is a compute-heavy worker has an expensive data transfer pattern across AZs; it is more directly addressed by Co-locate tightly coupled chatty components when resilience permits. Cross-AZ traffic adds latency and data transfer charges.

The option Choose instance types with adequate network performance after load testing addresses a separate condition: instances have high latency because the selected type has low baseline networking. EC2 bandwidth capacity differs by family and size. The actual requirement is a compute-heavy worker has an expensive data transfer pattern across AZs. Recommended corrective action: Co-locate tightly coupled chatty components when resilience permits. Cross-AZ traffic adds latency and data transfer charges.

Use a cluster placement group and compatible high-performance instances would help if two tightly coupled HPC workers need very low latency within one AZ. Placement groups can place supported instances close together. That is not the symptom described here: a compute-heavy worker has an expensive data transfer pattern across AZs. The matching response is Co-locate tightly coupled chatty components when resilience permits, because cross-AZ traffic adds latency and data transfer charges.

The option Choose instance types with adequate network performance after load testing addresses a separate condition: instances have high latency because the selected type has low baseline networking. EC2 bandwidth capacity differs by family and size. The actual requirement is a storage-intensive job uses EBS volumes whose performance exceeds instance EBS throughput. Recommended corrective action: Scale instance EBS bandwidth or rebalance volume throughput. Instance throughput limits cap total EBS I/O.

Use a cluster placement group and compatible high-performance instances would help if two tightly coupled HPC workers need very low latency within one AZ. Placement groups can place supported instances close together. That is not the symptom described here: a storage-intensive job uses EBS volumes whose performance exceeds instance EBS throughput. The matching response is Scale instance EBS bandwidth or rebalance volume throughput, because instance throughput limits cap total EBS I/O.

For the alternative failure a packet-processing application requires high packets per second and low overhead, the control Use supported enhanced networking ENA adapters and suitable instances is relevant: eNA improves EC2 network datapath efficiency. Here the evidence instead is a storage-intensive job uses EBS volumes whose performance exceeds instance EBS throughput. The selected technical mechanism is Scale instance EBS bandwidth or rebalance volume throughput: instance throughput limits cap total EBS I/O.