SAA-C03 Exam Dumps - Amazon Web Services AWS Certified Associate Questions and Answers

AWS Budgets supports budget actions that can automatically apply controls when a threshold is reached. In this case, because the accounts are non-production, it is appropriate to enforce a hard control by applying an SCP to the OU to deny additional usage and to stop running EC2 instances through a notification-driven workflow. AWS documentation describes AWS Budgets as the service for setting cost thresholds and taking automated actions, which makes it more appropriate than Cost Explorer reporting, CloudWatch alarms, or Cost Anomaly Detection for direct budget enforcement. Since the requirement is to prevent the team from exceeding the project budget, the budget-action-based control is the strongest solution.

Amazon RDSMulti-AZ DB cluster deploymentensures high availability by automatically replicating data across multiple Availability Zones (AZs), and it supports failover in case of a failure in one AZ. This setup also provides increased capacity for read workloads by allowing read scaling with reader instances in different AZs. This solution offers the most operational efficiency with minimal manual intervention.

Option A (DynamoDB): DynamoDB is not suitable for a relational database workload, which requires a PostgreSQL engine.

Option B (RDS with Multi-AZ): While this provides high availability, it doesn ' t offer read scaling capabilities.

Option D (Cross-Region Read Replicas): This adds complexity and is not necessary if the requirement is high availability within a single region.

AWS References:

Amazon RDS Multi-AZ DB Cluster

The performance issue occurs because reporting queries compete with production traffic on the same primary database instance. The best-practice AWS solution is to offload read-heavy workloads to a separate database endpoint.

Option C adds an Amazon RDS read replica, which asynchronously replicates data from the primary instance. By redirecting reporting queries to the replica endpoint, the primary database can focus on transactional workloads, significantly improving application performance and customer experience.

Read replicas are specifically designed for this use case: scaling read capacity and isolating reporting or analytics queries. This solution requires minimal changes to the reporting job (endpoint update only) and avoids overprovisioning the primary database.

Option A (RDS Proxy) improves connection management but does not reduce query load or isolate reporting traffic. Option B is invalid because Multi-AZ does not scale reads and is not configurable across three AZs for a single instance. Option D increases instance size but does not address the underlying contention between workloads and increases cost unnecessarily.

Therefore, C is the most efficient and scalable solution to minimize reporting impact while maintaining high performance and availability.

Amazon CloudFront can usemultiple originsin one distribution, including anAmazon S3 bucketfor static content and anApplication Load Balancerfor dynamic content. That lets the company reduce latency globally for both content types while keeping a single front door for users. AWS documentation specifically notes that CloudFront supports both S3 origins and load balancer origins, and a single distribution can include multiple origins. Route 53 can then alias the company’s domain to the CloudFront distribution. The Global Accelerator options are unnecessary here because CloudFront already addresses the performance need for both static and dynamic web delivery in this architecture.

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This solution offers the least operational overhead while meeting the security and global availability requirements:

Amazon CloudFront and S3: Hosting the static frontend on S3 and serving it via CloudFront provides low-latency global distribution, high availability, and security. S3 is a cost-effective and serverless option for hosting static assets, and CloudFront ensures that the application is cached closer to the users, reducing latency globally.

AWS Lambda and API Gateway: Refactoring the microservices to use Lambda functions with API Gateway allows for a fully serverless, scalable, and highly available backend. This reduces the need for managing EC2 instances, as Lambda automatically scales to meet demand and only charges for the actual usage.

RDS for MySQL: Migrating the MySQL database from an EC2 instance to Amazon RDS significantly reduces operational overhead. RDS manages backups, patching, and scaling, and it offers high availability options (e.g., Multi-AZ).

Option AandDinvolve using EC2 Reserved Instances for the database, which requires more operational maintenance than using RDS.

Option Csuggests using a Network Load Balancer with Lambda, which adds unnecessary complexity for this use case.

AWS References:

Amazon S3 and CloudFront Integration

AWS Lambda with API Gateway

Amazon RDS for MySQL

Comprehensive and Detailed Step-by-Step Explanation:

The goal is totransfer 500 GB dailyfrom multiple global locationsquicklyintoa single S3 bucketwhile keeping operational complexity low.

Option A:✅

Turn on S3 Transfer Acceleration on the destination S3 bucket. Use multipart uploads to directly upload site data to the destination S3 bucket.

S3 Transfer Acceleration (S3-TA)allowsfasterglobal uploads by routing traffic throughAmazon CloudFront’s globally distributed edge locations.

Multipart uploadsimprove efficiency bybreaking large filesinto smaller parts, transferring them in parallel.

Low operational complexity: No need for additional resources or manual replication.

Why is this best?It ensureshigh-speed transferswhileminimizing complexity.

To track costs associated with different teams within a single AWS account, the company should implement user-defined cost allocation tags.

Tagging Resources with CostCenter: Assign the CostCenter tag to all resources, specifying the appropriate value for each team. This practice enables the organization to categorize and track AWS costs effectively.

Activating the CostCenter Tag: After tagging resources, activate the CostCenter tag in the AWS Billing and Cost Management console. Activation is necessary for the tags to appear in cost allocation reports and AWS Cost Explorer.

By following these steps, the company can generate detailed billing reports that break down costs by team, facilitating better cost management and accountability.

Edge-optimized API endpointsroute requests through CloudFront, reducing latency for global users.

Option Acorrectly implements edge-optimization, caching, and compression to minimize latency.

Options B and Ddo not use edge optimization, leading to higher latency for global users.

Reserved concurrency inOptions C and Dimproves backend scaling but does not address global latency directly.

The SELECT INTO OUTFILE S3 feature allows you to export Amazon Aurora MySQL data directly to Amazon S3 with minimal operational overhead. This method is efficient and cost-effective for archiving historical data.

You can configure S3 Lifecycle rules to transition the exported data to lower-cost storage (e.g., S3 Glacier or S3 Standard-IA) and eventually delete it after 5 years.

No need for additional ETL tools like Glue or DataBrew unless complex transformations are required.

Amazon EBS io2 Block Express volumes are designed to deliver sub-millisecond latency and up to 256,000 IOPS per volume, with durability and high availability. This makes io2 Block Express the recommended choice for workloads requiring very high and predictable IOPS, such as enterprise databases and high-transaction-rate applications.

Reference Extract:

" EBS io2 Block Express volumes deliver up to 256,000 IOPS and sub-millisecond latency, supporting high-performance, high-durability workloads. "

Source: AWS Certified Solutions Architect – Official Study Guide, EBS Performance section.

The correct design is to useRoute 53 failover records, with theprimary record pointing to the ALB and associated with a health check, and thesecondary record pointing to the static website. Route 53 failover routing is designed to return the primary resource when it is healthy and automatically return the secondary resource when the primary becomes unhealthy. The health check is attached to the primary failover record so Route 53 knows when to fail over. You do not need a Lambda function to switch records manually, because Route 53 provides built-in DNS failover. The secondary record does not need its own health check for this pattern. That is whyC and Eare the right combination. (AWS Documentation)

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AWS Transit Gateway simplifies network connectivity by acting as a hub that can connect VPCs and on-premises networks through VPN or Direct Connect. It provides scalability and reduces administrative overhead by eliminating the need to manage complex peering relationships as the number of accounts and VPCs grows.

Amazon S3 supports one Lifecycle configuration per bucket that can contain multiple rules. Lifecycle rules can include filters, including object size filters: ObjectSizeGreaterThan and ObjectSizeLessThan. You can combine rules so that one targets large objects and another provides a default expiration. Here, configure Rule 1 with a size filter ObjectSizeGreaterThan = 1 TB and Expiration = 2 days (48 hours) to purge very large videos early. Configure Rule 2 with Expiration = 7 days without a size filter to serve as a catch-all maximum retention for all objects. Options B and D are invalid because S3 does not allow multiple Lifecycle configurations per bucket. Option C cannot distinguish large files; it would delete all files at the same schedule without honoring the 48-hour policy for > 1 TB objects. This single configuration with two rules meets both retention targets with minimal overhead and full S3-native capability.

ECS with Fargate: Allows containerized workloads to scale rapidly without managing underlying servers, handling unpredictable growth effectively.

RDS for Relational Data: Manages large relational datasets efficiently while supporting high availability.

SQS for Decoupling: Ensures message processing occurs in a specific order, decoupling application components and allowing independent evolution.

AWS ECS with Fargate Documentation,AWS SQS Documentation

AWS best practice is to use IAM roles with instance profiles for EC2 instances so that applications obtain temporary credentials automatically and do not need to store access keys.

To honor the principle of least privilege, each microservice should have an IAM role that grants only the specific permissions it needs.

Therefore, creating individual IAM roles per microservice and attaching them via instance profiles (Option D) both minimizes long-term credential management and applies least privilege cleanly.

Why others are not correct:

A: Using IAM users with access keys in code is insecure and high-overhead (key rotation, secret management).

B: A single broad role violates least privilege because every microservice gets more permissions than it needs.

C: Separate accounts per microservice is extreme over-segmentation and significantly increases operational complexity.

Amazon EFS is the correct answer because it provides aPOSIX-compliant, shared file systemthat multiple ECS tasks and instances can mount concurrently. AWS documents EFS as a managed NFS file system built for shared access and elastic growth, which fits the requirement for log and configuration sharing across Linux containers.Elastic throughputis the best cost-conscious choice when access patterns can vary, because throughput scales automatically without manual provisioning. S3 is object storage and does not provide native POSIX file system behavior. EBS is block storage and is not the right answer for shared, highly available multi-container access across a distributed environment. FSx for Lustre is optimized for specialized high-performance workloads, not general shared configuration and log storage.

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The least operational overhead approach is to use AWS Directory Service with AWS Managed Microsoft AD and establish a trust relationship with the existing on-premises Microsoft Active Directory. This pattern lets employees continue using their existing corporate credentials while AWS operates the directory infrastructure (patching, monitoring, availability, and domain controller management), reducing the burden compared to building and maintaining custom federation components. With a trust in place, identities and group memberships from the on-premises directory can be used for authentication and authorization workflows in AWS.

To provide role-based access to AWS resources and the AWS Management Console, users should assume IAM roles that grant permissions based on job function. IAM roles with appropriate trust policies enable temporary credentials and least-privilege access without creating long-lived IAM users for every employee. This aligns with AWS best practices of centralized identity management and using roles for access control.

Option B is not a standard direct integration pattern: IAM does not “LDAP bind” directly to on-premises AD for console access. Option C can work (custom identity broker + STS) but increases operational overhead because the company must build, secure, operate, and maintain the broker, including availability, updates, and incident response. Option D is not the typical solution for employee console federation from AD; Amazon Cognito is primarily aimed at customer identity and application sign-in, not as the primary mechanism for workforce console access to AWS accounts.

Therefore, A provides the required federation with the smallest operational footprint while supporting role-based access control.

AWS Config is a service designed to assess, audit, and evaluate the configurations of AWS resources. It continuously monitors and records your AWS resource configurations and allows you to automate the evaluation of recorded configurations against desired configurations. By starting a configuration recorder, AWS Config will capture changes to supported resource types as configuration items—without the need to modify any of the existing resources. This provides a full history of configuration changes and is specifically intended for exactly this use case.

AWS Documentation Extract:

“AWS Config provides a detailed view of the configuration of AWS resources in your AWS account. This includes how the resources are related to one another and how they were configured in the past so you can see how the configurations and relationships change over time.”

“You can start the configuration recorder, which will record the configuration changes of the supported resources in your AWS account.”

(Source: AWS Config documentation, What is AWS Config?)

Other options:

B: CloudFormation drift detection only works for resources created and managed by CloudFormation and requires stacks.

C: Amazon Detective is used for analyzing and investigating security findings, not for resource configuration tracking.

D: AWS Audit Manager is used for automating evidence collection to help with audits, not for tracking resource configurations.

Amazon ECS on AWS Fargate with Amazon EFS is the best match because it combines managed container orchestration with shared persistent storage. AWS documentation explains that Amazon EFS volumes can be used with Amazon ECS so tasks can access the same persistent file system regardless of where they run. AWS also notes that EFS volumes are useful for horizontally scaled containerized applications that need shared storage, low latency, and high throughput. Lambda is a poor fit here because Lambda invocations have a maximum timeout of 15 minutes, while the question states processing can take up to 1 hour. Instance store volumes on ECS EC2 are local to the host and do not provide the centralized persistent repository the workload needs. Fargate plus EFS best satisfies performance, duration, and operational efficiency.

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