Amazon Web Services Updated SAA-C03 Exam Questions and Answers by aaryan

Comprehensive and Detailed 250 to 300 words of Explanation (AWS documentation-based, no links):

Routing requests to the “appropriate microservices” implies Layer 7 (HTTP/HTTPS) routing such as host-based or path-based rules (for example, /customers to one service and /orders to another). In EKS, the most direct and cost-efficient way to provide this style of routing is to use Kubernetes Ingress with the AWS Load Balancer Controller to provision an Application Load Balancer (ALB). An ALB natively supports HTTP/HTTPS request routing features (paths, hosts, headers), which map cleanly to microservices patterns and reduce the need for additional infrastructure components.

A Network Load Balancer (NLB) (Option A) is primarily Layer 4 and is best for TCP/UDP/TLS pass-through and ultra-high performance. It does not provide the same native HTTP path-based routing behavior required to steer requests between microservices based on URL structure, so it often forces you to add another routing layer (like an in-cluster ingress gateway), which can increase cost and operational complexity.

Option C is not an appropriate request routing mechanism; Lambda is compute, not an ingress/routing layer for EKS. Option D (API Gateway) can front services, but for simple microservice routing into EKS it typically adds per-request costs and additional configuration compared with using an ALB that is purpose-built for HTTP load balancing and routing. API Gateway is a great fit for API management features (throttling, usage plans, keys, transformations), but those are not requirements here.

Therefore, B is the most cost-effective and architecturally aligned solution for HTTP routing across EKS-hosted microservices using managed AWS-native ingress integration.

A Network Load Balancer operates at Layer 4 (TCP/UDP/TLS) and is optimized for high performance and static IP use cases. While NLB target groups can perform health checks, they are typically oriented around basic reachability and do not provide the same application-layer (Layer 7) visibility as an Application Load Balancer (ALB). The problem statement says the NLB is “not detecting HTTP errors,” which indicates the health signal needs to be based on an HTTP endpoint that can reflect application correctness (for example, returning specific HTTP status codes).

Replacing the NLB with an ALB enables true HTTP/HTTPS health checks against a URL path, including interpretation of HTTP response codes. This is the cleanest managed approach to detect application-layer failure modes that still allow TCP connections but produce bad HTTP responses. Once the ALB detects targets as unhealthy, the target group health status can be used by an Auto Scaling group to take action. With appropriate health check configuration (and, commonly, using ELB health checks as a signal), Auto Scaling can replace unhealthy instances automatically, improving availability without custom scripts.

Option A is misleading: NLB does not provide the same HTTP-aware request routing and rich L7 features; even if an NLB health check is configured, it does not address the broader need for application-layer detection and remediation as directly as ALB. Option B violates the “no custom scripts” requirement. Option D reacts to UnhealthyHostCount, but if the NLB isn’t marking hosts unhealthy for HTTP error cases, the metric won’t reliably trigger replacement; it also still depends on the NLB’s limited visibility into HTTP failures.

Therefore, C best meets the requirement by shifting to ALB for application-layer health checks and using Auto Scaling to replace unhealthy instances automatically.

The combination of these solutions provides an efficient and automated way to migrate data while preserving metadata and ensuring cleanup:

Create a new S3 bucket with versioning enabled(Option A) to preserve object metadata like version IDs during migration.

UseS3 batch operations(Option B) to efficiently copy data from specific prefixes in the source bucket to the destination bucket, ensuring minimal overhead.

Use an S3 Lifecycle policy(Option F) to automatically delete the data from the source bucket after it has been migrated, reducing manual intervention.

Option C (CopyObject API): This approach would require more manual scripting and effort.

Option D (Same-Region Replication): SRR is designed for ongoing replication, not for one-time migrations.

Option E (DataSync): DataSync adds more complexity than necessary for this task.

AWS References:

S3 Batch Operations

S3 Lifecycle Policies

Amazon S3 Access Points simplify managing data access for shared datasets in S3 by allowing the creation of distinct access policies for different applications or users. Each access point has its own policy and can be managed independently. This method avoids overloading a single bucket policy and helps remain within policy size limits.

Option D provides a scalable and operationally efficient solution by offloading individual access controls from a central bucket policy to individually managed access points, which is ideal for environments with many consuming applications.