SAP-C02 Exam Dumps - AWS Certified Solutions Architect - Professional

Cross-zone load balancing enables traffic to be distributed evenly across all registered instances in all enabled Availability Zones. However, this also increases data transfer charges between Availability Zones. By turning off cross-zone load balancing, the serviceprovider applications can reduce inter-Availability Zone data transfer costs. Similarly, by using the Availability Zone-specific endpoint service, the service consumer applications can ensure that they connect to the nearest service provider application in the same Availability Zone, avoiding cross-Availability Zone data transfer charges. References:

https://docs.aws.amazon.com/elasticloadbalancing/latest/network/load-balancer-target-groups.html#cross-zone-load-balancing

https://docs.aws.amazon.com/vpc/latest/userguide/vpce-interface.html#vpce-interface-dns

Set Up EventBridge Event Bus:

Step 1: Open the Amazon EventBridge console and create a custom event bus. This bus will be used to handle user deletion events.

Step 2: Name the event bus appropriately (e.g.,user-deletion-bus).

Post Events on User Deletion:

Step 1: Modify the central user service to post an event to the custom EventBridge event bus whenever a user is deleted.

Step 2: Ensure the event includes relevant details such as the user ID and any other necessary metadata.

Create EventBridge Rules for Microservices:

Step 1: For each microservice that needs to delete user data, create a new rule in EventBridge that triggers on the user deletion event.

Step 2: Define the event pattern to match the user deletion event. This pattern should include the event details posted by the central user service.

Invoke Microservice Logic:

Step 1: Configure the EventBridge rule to invoke a target, such as an AWS Lambda function, which contains the logic to delete the user data from the microservice ' s data store.

Step 2: Each microservice should have its Lambda function or equivalent logic to handle the deletion of user data upon receiving the event.

Using Amazon EventBridge ensures a scalable, reliable, and decoupled approach to handle the deletion of user data across multiple microservices. This setup allows each microservice to independently process user deletion events without direct dependencies on other services.

References

AWS EventBridge Documentation

DynamoDB Streams and AWS Lambda Triggers

Implementing the Transactional Outbox Pattern with EventBridge Pipes​(AWS Documentation)​​(Amazon Web Services, Inc.)​​(Amazon Web Services, Inc.)​​(AWS Documentation)​​(AWS Cloud Community)​.

The core issue is high latency when serving images during traffic spikes. The current design resizes images dynamically and caches them locally inside ECS containers. With AWS Fargate, containers are ephemeral and scale in and out based on load. Local container caches are not shared across tasks, so cache hit rates drop during scaling events, forcing repeated image resizing. This increases CPU usage, startup latency, and response times under load.

The lowest operational overhead and most effective solution is to offload image delivery entirely from the application layer and use edge caching. Amazon CloudFront is designed to cache static content at edge locations close to end users, dramatically reducing latency and backend load. Amazon S3 is a durable, highly scalable object store that is well suited for serving static assets such as images.

Option A moves image delivery to a CloudFront + S3 architecture. By pre-scaling images and storing them in S3, the application no longer performs on-demand image resizing during requests. CloudFront caches the images at edge locations, so subsequent requests are served directly from the edge with minimal latency. The ALB remains the origin for dynamic content, while image requests are routed to the S3 origin using cache behaviors. This approach is fully managed, highly scalable, and requires minimal changes to the application logic once images are pre-generated.

Option B introduces ElastiCache, which adds operational overhead and complexity. The application must manage cache keys, eviction, and failure scenarios. ElastiCache is better suited for low-latency data access patterns rather than large static objects like images, and it does not provide global edge caching.

Option C adds unnecessary complexity by introducing an Aurora database as part of the caching layer. Databases are not designed to manage cache metadata for static assets at scale, and this design increases operational overhead without improving latency compared to CloudFront.

Option D is not appropriate because API Gateway caching is intended for API responses, not for efficient delivery of large static binary objects such as images. Replacing the ALB with API Gateway also introduces request size, payload, and cost considerations and does not provide global edge caching comparable to CloudFront for image delivery.

Therefore, using Amazon CloudFront with Amazon S3 for pre-scaled images provides the lowest latency, highest scalability, and least operational overhead.

B:https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode.html#HowItWorks.requests

D:https://aws.amazon.com/blogs/compute/robust-serverless-application-design-with-aws-lambda-dlq/c

The correct answers are C and D. The IAM user appears to have read-only S3 permissions, but AWS authorization is the result of multiple policy layers. In AWS Organizations, a service control policy can set the maximum permissions available to principals in member accounts. If an OU-level SCP denies or does not allow S3 actions, the IAM user’s read-only policy will not be enough. A permissions boundary can also restrict the maximum permissions an IAM user can exercise, even if an identity-based policy appears to allow access. Bucket policies can affect access to specific buckets and objects, but the symptom says no buckets are listed in the console, which points more strongly to identity-side effective permission limits. ACLs are legacy resource controls and are not the primary place to troubleshoot this issue. (AWS Documentation)

===============