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

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 IAM Identity Center:

IAM Identity Centerprovides centralized access management for multiple AWS accounts within an organization and integrates seamlessly with existing identity providers (IdPs) throughSAML 2.0 federation.

It allows users to authenticate using their existing IdP credentials and gain access to AWS resources without the need to create and manage separate IAM users in each account.

IAM Identity Centeralso simplifies provisioning and de-provisioning users, as it can automatically synchronize users and groups from the external IdP to AWS, ensuring secure and managed access.

Integration with Existing IdP:

The solution involves configuringIAM Identity Centerto connect to the company's IdP using SAML. This setup allows employees to log in with their existing credentials, reducing the complexity of managing separate AWS credentials.

Once connected,IAM Identity Centerhandles authentication and authorization, granting users access to the AWS accounts based on their assigned roles and permissions.

Why the Other Options Are Incorrect:

Option A: Creating separateIAM usersfor each employee is not scalable or efficient. Managing thousands of IAM users across multiple AWS accounts introduces unnecessary complexity and operational overhead.

Option B: Using AWSroot userswith synchronized passwords is a security risk and goes against AWS best practices. Root accounts should never be used for day-to-day operations.

Option D:AWS Resource Access Manager (RAM)is used for sharing AWS resources between accounts, not for federating access for users across accounts. It doesn’t provide a solution for authentication via an external IdP.

AWS References:

AWS IAM Identity Center

SAML 2.0 Integration with AWS IAM Identity Center

By setting upIAM Identity Centerand connecting it to the existing IdP, the company can efficiently manage access for thousands of employees across multiple AWS accounts with a high degree of operational efficiency and security. Therefore,Option Cis the best solution.

Amazon S3 Standard-IA: This storage class is designed for data that is accessed less frequently but requires rapid access when needed. It offers lower storage costs compared to S3 Standard while still providing high availability and durability.

Access Patterns: Since the files are frequently accessed in the first 30 days and rarely accessed afterward, transitioning them to S3 Standard-IA after 30 days aligns with their access patterns and reduces storage costs significantly.

Lifecycle Policy: Implementing a lifecycle policy to transition the files to S3 Standard-IA ensures automatic management of the data lifecycle, moving files to a lower-cost storage class without manual intervention. Deleting the files after 4 years further optimizes costs by removing data that is no longer needed.

The requirement is to provide granular, scalable access to thousands of tables and columns in a data lake across many users and departments, with the least operational overhead.

AWS Lake Formation supports tag-based access control (TBAC) using LF-tags (Lake Formation tags), which allows you to assign tags to tables, columns, and databases. You can then define permissions on resources by specifying tags rather than managing permissions for individual resources. This approach is highly scalable and efficient when dealing with a growing number of tables and columns. By associating IAM roles to departments and granting access based on LF-tags, you dramatically reduce the operational burden as new tables or columns are added; you only need to assign the appropriate tags.

Amazon Athena can directly query data in S3 with Lake Formation providing fine-grained access control.

AWS Documentation Extract:

"With LF-tag-based access control, you can grant permissions to resources based on tags, making it easy to manage access at scale, especially in environments with large and dynamic numbers of resources."

"LF-tags provide a scalable way to manage permissions for large numbers of resources without having to define permissions individually for each table or column."

(Source: AWS Lake Formation documentation, Access Control, Tag-Based Access Control)

Other options:

A: Would require managing explicit permissions for each table and column as the environment grows, increasing operational overhead.

B & D: Involve significant duplication of resources (clusters) and do not scale as efficiently as a centralized data lake with tag-based access.

AmazonS3 with the Standard storage classis the best solution:

Encryption: SSE-S3 ensures server-side encryption of the data, meeting compliance requirements.

Immediate access: The Standard storage class provides low-latency and high-throughput access to data.

Multi-location storage: Cross-Region replication ensures data is stored in multiple AWS Regions for redundancy.

Why Other Options Are Not Ideal:

Option B:

Amazon EFS is more costly and suited for file systems rather than object storage.Not cost-effective.

Option C:

Amazon EBS is block storage and not optimized for object storage like PDFs. Backup schedules do not ensure immediate availability.Not suitable.

Option D:

S3 Glacier Flexible Retrieval is designed for archival, not immediate access.Does not meet access requirements.

AWS References:

Amazon S3 Standard Storage:AWS Documentation - S3 Storage Classes

Amazon S3 Cross-Region Replication:AWS Documentation - Cross-Region Replication

AWS Encryption Options:AWS Documentation - S3 Encryption

To improve scalability and availability, EC2 Auto Scaling across multiple Availability Zones with an Application Load Balancer ensures resilient infrastructure. Migrating to Amazon Aurora MySQL with reader endpoints reduces read latency by offloading read traffic to replicas in otherAZs, while also increasing high availability.

Private subnets require outbound internet access to download updates, but they must not have public IPs or direct inbound access.

The recommended AWS solution is to create a NAT gateway in a public subnet. Private subnet route tables are updated to route internet-bound traffic (0.0.0.0/0) to the NAT gateway. The NAT gateway then uses the internet gateway attached to the VPC to communicate with the internet.

Option B (NAT instances) is an older approach and less scalable/maintainable than NAT gateways. Option C (egress-only internet gateway) is for IPv6 outbound-only traffic, not IPv4. Option D is invalid because NAT gateways must be deployed in public subnets.

AWS S3 Multi-Region Access Points enable customers to use a single global endpoint for S3 bucket access across multiple AWS Regions, providing automatic routing to the nearest Region. This reduces public network congestion by directing user data to the closest S3 bucket and supports high availability with active-active configuration.

Cross-Region Replication ensures data is replicated between buckets in different Regions, meeting the failover and resilience requirements with minimal management overhead.

Option D aligns best with AWS’s recommended approach to resilient, low-latency, and simplified multi-Region S3 access.

Option A lacks the global endpoint and automatic failover. Option B incorrectly describes Multi-Region Access Points configuration and suggests global endpoints per Region, which is contradictory. Option C’s cross-account replication adds complexity and does not provide a single global endpoint.