SAA-C03 Exam Dumps - AWS Certified Solutions Architect - Associate (SAA-C03)

For secure communication between Lambda and an RDS DB instance, AWS documentation recommends placing the Lambda functions inside the same VPC and controlling traffic using security groups.

Lambda should have a dedicated security group with outbound access to the VPC CIDR range, and the DB instance’s security group should explicitly allow inbound connections from the Lambda security group. This follows the " least privilege " principle while avoiding public exposure.

Options A and B expose the DB to unnecessary risk. Option D is insecure because it bypasses security groups.

The issue described in the question, where incoming traffic seems to favor one EC2 instance, is often caused by session affinity (also known as sticky sessions) being enabled on the Application Load Balancer (ALB). When session affinity is enabled, the ALB routes requests from the same client to the same EC2 instance. This can cause an imbalance in traffic distribution, leading to performance bottlenecks on certain instances while others remain underutilized.

To resolve this issue, disabling session affinity ensures that the ALB distributes incoming traffic evenly across all EC2 instances, allowing better load distribution and reducing latency. The ALB will rely on its round-robin or least outstanding requests algorithm (depending on the configuration) to distribute traffic more evenly across instances.

Option B (Network Load Balancer): The NLB is designed for Layer 4 (TCP) traffic and low latency use cases, but it is not needed here as the problem is with load balancing logic at the application layer (Layer 7). The ALB is more appropriate for HTTP/HTTPS traffic.

Option C (Increase EC2 Instances): Adding more EC2 instances does not solve the root issue of uneven traffic distribution.

Option D (Health Check Frequency): Adjusting health check frequency won ' t address the imbalance caused by session affinity.

AWS References:

Application Load Balancer Sticky Sessions

AWS guidance for global, highly available, low-latency applications using a relational database recommends:

Amazon CloudFront with Amazon S3 for static content to cache data at edge locations globally and minimize latency for static assets.

A regional application tier deployed close to users using managed container services such as Amazon ECS on AWS Fargate, which removes the need to manage servers and scales automatically, reducing operational overhead.

A relational database tier using Amazon Aurora global database, which is purpose-built for globally distributed applications. Aurora global database provides a primary cluster in one Region with low-latency read replicas in secondary Regions and fast cross-Region replication, enabling low-latency reads and high availability for global users.

Option A uses only a single Region, which does not meet the “global users with low latency” requirement.

Option C uses RDS and DMS-based replication, which requires more management and does not provide Aurora’s integrated global database features.

Option D replaces the relational database with DynamoDB, which violates the requirement that the application interacts with a relational database.

This solution usesCloudFrontto serve the website securely over HTTPS usingAWS Certificate Manager (ACM)for SSL certificates.Origin Access Control (OAC)ensures that only CloudFront can access the S3 bucket directly.AWS WAFwith an IP set rule restricts access to the website, allowing only the on-premises IP address.Route 53is used to create an alias record pointing to the CloudFront distribution. This setup ensures secure, private access to the website with low administrative overhead.

Option A and B: S3 bucket policies and access points do not provide HTTPS support, nor do they offer the same level of security as CloudFront with WAF.

Option D: Signed URLs are more suitable for temporary, expiring access rather than a permanent solution for on-premises employees.

AWS References:

Amazon CloudFront with Origin Access Control

Amazon S3 Access Grantsis designed to providefine-grained, prefix-level accessto S3 data for users and groups, including identities coming from a corporate directory or IAM Identity Center. AWS documentation explains that S3 Access Grants can map users or groups to specific S3 locations and vend temporary credentials, which makes it far more scalable than building separate IAM users, role-sharing workflows, or presigned URLs for every vendor. IAM Identity Center adds centralized user lifecycle and identity administration. This combination is especially strong when different vendors need access todifferent datasetsin the same data lake. It is also more maintainable and secure than issuing permanent IAM credentials. For auditing, the environment can still rely on AWS logging controls while using Access Grants for access distribution.

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

The requirements focus on cost optimization, automatic lifecycle management, and throughput scaling based on file system size. Amazon EFS provides two throughput modes: bursting and provisioned. Bursting throughput automatically scales with the size of the file system, which directly aligns with the company’s needs.

Option C is correct because it combines two essential features. First, configuring lifecycle management to transition files from Standard to Infrequent Access (IA) after 30 days reduces storage costs for infrequently accessed data. Second, enabling automatic transition back to Standard storage upon access ensures that performance-sensitive reporting workloads are not negatively affected when older files are read.

Using bursting throughput mode allows throughput to grow naturally as the file system size increases, eliminating the need to manually manage or pay for fixed throughput levels. This is ideal for workloads with variable access patterns.

Option A incorrectly specifies provisioned throughput, which is designed for predictable, high-throughput workloads and incurs additional cost. Option B ignores lifecycle transitions. Option D does not account for automatic return to Standard storage, which could lead to suboptimal performance for accessed files.

Therefore, C provides the best balance of performance, cost efficiency, and minimal operational overhead.

This solution is the most cost-effective and efficient way to break down costs per application.

Tagging Resources: By tagging all AWS resources with a specific key (e.g., " cost " ) and a value representing the application ' s name, you can easily identify and categorize costs associated with each application. This tagging strategy allows for granular tracking of costs within AWS.

Activating Cost Allocation Tags: Once tags are applied to resources, you need to activate cost allocation tags in the AWS Billing and Cost Management console. This ensures that the costs associated with each tag are included in your billing reports and can be used for cost analysis.

AWS Cost Explorer: Cost Explorer is a powerful tool that allows you to visualize, understand, and manage your AWS costs and usage over time. You can filter and group your cost data by the tags you’ve applied to resources, enabling you to easily see the cost breakdown for each application. Cost Explorer also supports generating regular reports, which can be scheduled and emailed to stakeholders.

Why Not Other Options?:

Option A (AWS Budgets): AWS Budgets is more focused on setting cost and usage thresholds and monitoring them, rather than providing detailed cost breakdowns by application.

Option B (Load Cost and Usage Reports into RDS): This approach is less cost-effective and involves more operational overhead, as it requires setting up and maintaining an RDS instance and running SQL queries.

Option D (AWS Billing and Cost Management Console): While you can download bills, this method is more manual and less dynamic compared to using Cost Explorer with activated tags.

AWS References:

AWS Tagging Strategies- Overview of how to use tagging to organize and track AWS resources.

AWS Cost Explorer- Details on how to use Cost Explorer to analyze costs.

AWS Transit Gateway is the correct architecture for connecting a very large number of VPCs in a scalable hub-and-spoke model. VPC peering between more than 1,000 VPCs would create an unmanageable mesh of peering connections and route table updates. VPN tunnels are intended for encrypted connectivity over external networks, not for efficient VPC-to-VPC communication at this scale. A Direct Connect gateway is used for connecting on-premises networks to AWS and is not the right mechanism for attaching every VPC through public VIFs. Transit Gateway supports VPC attachments and centralized route tables, which makes it the operationally scalable and high-performing choice for communication among many VPCs.