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

Understanding the Requirement: The company needs to mitigate DDoS attacks on its website, which uses AWS Global Accelerator to route traffic to an Application Load Balancer (ALB).

Analysis of Options:

AWS WAF on Global Accelerator: Allows for centralized protection and can block traffic based on rate-based rules, effectively mitigating DDoS attacks with minimal implementation effort.

Lambda Function and VPC Network ACL: Requires custom implementation and ongoing management, increasing complexity and effort.

AWS WAF on ALB: Provides protection but involves additional configuration and management at the ALB level.

CloudFront Distribution in front of Global Accelerator: Adds unnecessary complexity and changes the current traffic flow setup.

Best Solution:

AWS WAF on Global Accelerator: This provides the required protection with the least implementation effort, ensuring effective DDoS mitigation and maintaining the existing architecture.

Understanding the Requirement: The company needs to enable communication between VPCs across multiple AWS Regions with minimal administrative effort.

Analysis of Options:

VPC Peering: Managing multiple VPC peering connections across regions is complex and difficult to scale, leading to significant administrative overhead.

AWS Direct Connect Gateways: Primarily used for creating private connections between AWS and on-premises environments, not for inter-VPC communication across regions.

AWS Transit Gateway: Simplifies VPC interconnections within a region and supports Transit Gateway peering for cross-region connectivity, reducing administrative complexity.

AWS PrivateLink: Used for accessing AWS services and third-party services over a private connection, not for inter-VPC communication.

Best Solution:

AWS Transit Gateway with Transit Gateway Peering: This option provides a scalable and efficient solution for managing VPC communications both within a single region and across multiple regions with minimal administrative overhead.

Understanding the Requirement: The order processing system requires multiple independent validation steps, each handled by separate Lambda functions, with each function accessing only the subset of order information it needs. The system should be loosely coupled to accommodate future changes.

Analysis of Options:

Amazon SQS with a new Lambda function for transformation: This involves additional complexity in creating and managing multiple SQS queues and an extra Lambda function for data transformation.

Amazon SNS with message filtering: While SNS supports message filtering, it is more suited for pub/sub messaging patterns rather than event-driven processing requiring fine-grained control over the data sent to each function.

Amazon EventBridge with input transformers: EventBridge is designed for event-driven architectures, allowing for fine-grained control with input transformers that can modify and filter the event data sent to each target Lambda function, ensuring each function receives only the necessary information.

SQS with synchronous Lambda invocations: This approach adds unnecessary complexity with synchronous invocations and is not ideal for an event-driven, loosely coupled architecture.

Best Solution:

Amazon EventBridge with input transformers: This option provides the most flexible, scalable, and loosely coupled architecture, enabling each Lambda function to receive only the required subset of data.

Requirement Analysis: The application needs near real-time access to data, persistence, and minimal operational overhead.

ElastiCache for Redis: Provides in-memory data storage with persistence, supporting fast access and durability.

Operational Overhead: Managed service reduces the burden of setup, maintenance, and scaling.

Implementation:

Deploy an ElastiCache for Redis cluster.

Configure Redis to persist data to disk using AOF (Append-Only File) or RDB (Redis Database Backup) snapshots.

Conclusion: ElastiCache for Redis meets the requirements for fast access, data persistence, and low operational overhead.

References

Amazon ElastiCache:ElastiCache for Redis Documentation

Understanding the Requirement: The company wants to improve caching to enhance website performance while ensuring that stale content is not served for more than a few minutes after a deployment.

Analysis of Options:

Set CloudFront TTL: Setting a short TTL (e.g., 2 minutes) ensures that cached content is refreshed frequently, reducing the risk of serving stale content.

S3 Bucket TTL: This would not control the cache duration for the CloudFront distribution.

Cache-Control Private: This directive is for controlling caching by private caches (e.g., browsers) and is not applicable for CloudFront.

Lambda@Edge: While this can add headers dynamically, it adds complexity and operational overhead.

Cache-Control max-age and CloudFront Invalidation: Setting a longer max-age for objects ensures they are cached longer, reducing load on the origin. Invalidation ensures that updated content is refreshed immediately after deployment.

Best Combination of Caching Methods:

Set the CloudFront default TTL to 2 minutes: This balances caching and freshness of content.

Add a Cache-Control max-age directive of 24 hours and use CloudFront invalidation: This ensures efficient caching while providing a mechanism to clear outdated content immediately after a deployment.

Requirement Analysis: Need quick, cost-effective, and consistent access to on-premises network services from multiple AWS accounts.

AWS Transit Gateway: Centralizes and simplifies network management by connecting VPCs and on-premises networks.

Direct Connect Integration: Assigning DX to the transit gateway ensures consistent and high-performance connectivity.

Operational Overhead: Minimal because Transit Gateway simplifies routing and management.

Implementation:

Set up AWS Transit Gateway.

Connect new AWS accounts to the Transit Gateway.

Route traffic through Transit Gateway to on-premises servers via Direct Connect.

Conclusion: This solution provides a scalable, cost-effective, and low-overhead method to meet connectivity requirements.

References

AWS Transit Gateway:AWS Transit Gateway Documentation

 This solution meets the requirements with the least operational overhead because it uses AWS services that are fully managed and scalable. The EventBridge rule can detect the DeleteKey operation from the AWS KMS API and trigger the Systems Manager Automation runbook, which can execute a predefined workflow to cancel the key deletion. The EventBridge rule can also publish an SNS message to the topic that sends an email notification to the administrators. This way, the company can prevent the accidental deletion of KMS keys and notify the administrators of any attempts to delete them.

Option A is not a valid solution because AWS Config rules are used to evaluate the configuration of AWS resources, not to cancel the deletion of KMS keys. Option B is not a valid solution because it requires creating and maintaining a custom Lambda function that has logic to prevent KMS key deletion, which adds operational overhead. Option D is not a valid solution because it only notifies the administrators of the DeleteKey operation, but does not cancel it.

Understanding the Requirement: The company needs a container solution that can scale across on-premises, hybrid, and cloud environments, with a load balancer for HTTP traffic.

Analysis of Options:

Fargate Launch Type and ECS Anywhere: Using Fargate for cloud-based containers and ECS Anywhere for on-premises containers provides a unified management experience across environments without needing to manage infrastructure.

Application Load Balancer: Suitable for HTTP traffic and can distribute requests to the ECS services, ensuring scalability and performance.

Network Load Balancer: Typically used for TCP/UDP traffic, not specifically optimized for HTTP traffic.

EC2 Launch Type for ECS and ECS Anywhere with Fargate: Involves managing infrastructure for EC2 instances, increasing operational overhead.

Best Combination of Solutions:

ECS with Fargate Launch Type and ECS Anywhere: This provides flexibility and scalability across hybrid environments with minimal operational overhead.

Application Load Balancer: Optimized for HTTP traffic, ensuring efficient load distribution and scaling for the ECS services.

Understanding the Requirement: The application running on EC2 instances in private subnets needs to securely connect to an Amazon SQS queue without exposing traffic to the public internet.

Analysis of Options:

Interface VPC Endpoint in Private Subnets: Allows private, secure connectivity to SQS without using the public internet.Configuring security groups ensures controlled access from EC2 instances.

Interface VPC Endpoint in Public Subnets: Not necessary for private EC2 instances and exposes additional security risks.

Gateway Endpoint: Gateway endpoints are not supported for SQS; they are used for services like S3 and DynamoDB.

NAT Gateway with IAM Role: Increases costs and complexity compared to using an interface VPC endpoint directly.

Best Solution:

Interface VPC Endpoint in Private Subnets: This option ensures secure, private connectivity to SQS, meeting the requirement with minimal complexity and optimal security.

Requirement Analysis: The company wants to identify cost optimizations for EC2 instances, the Auto Scaling group, and EBS volumes with high operational efficiency.

AWS Compute Optimizer: This service provides actionable recommendations to help optimize your AWS resources, including EC2 instances, Auto Scaling groups, and EBS volumes.

Cost Recommendations: Compute Optimizer analyzes the utilization of resources and provides specific recommendations for rightsizing or optimizing the configurations.

Operational Efficiency: Using Compute Optimizer automates the process of identifying cost-saving opportunities, reducing the need for manual analysis.

Implementation:

Enable AWS Compute Optimizer for your AWS account.

Review the recommendations provided for EC2 instances, Auto Scaling groups, and EBS volumes.

Conclusion: This solution provides a comprehensive, automated approach to identifying cost optimizations with minimal operational effort.

References

AWS Compute Optimizer:AWS Compute Optimizer Documentation

Understanding the Requirement: The application is stateful and requires at least two EC2 instances to be running at all times, with a highly available and fault-tolerant architecture.

Analysis of Options:

Minimum capacity of two with instances in separate AZs: Ensures high availability by distributing instances across multiple AZs, fulfilling the requirement of always having two instances running.

Minimum capacity of four: Provides redundancy but is more than what is required and increases cost without additional benefit.

Spot Instances: Not suitable for a stateful application requiring guaranteed availability, as Spot Instances can be terminated at any time.

Combination of On-Demand and Spot Instances: Mixing instance types might provide cost savings but does not ensure the required availability for a stateful application.

Best Solution:

Minimum capacity of two with instances in separate AZs: This setup ensures high availability and meets the requirement with the least cost and complexity.

Understanding the Requirement: The company needs to keep daily EBS snapshots for 1 month and retain monthly snapshots for 7 years due to new regulations.

Analysis of Options:

S3 Glacier Deep Archive: Moving snapshots to S3 Glacier Deep Archive involves additional complexity and might not be the most straightforward approach for EBS snapshots.

EBS Snapshots Archive: This is a cost-effective solution designed specifically for long-term storage of EBS snapshots.

Standard Tier for 7 Years: Keeping snapshots in the standard tier for 7 years is more expensive and does not optimize costs.

EBS Direct APIs to S3: This involves additional operational overhead and is not the most cost-effective approach compared to using EBS Snapshots Archive.

Best Solution:

EBS Snapshots Archive: Adding a policy to move monthly snapshots to the EBS Snapshots Archive for long-term retention is the most cost-effective and administratively simple solution.

Understanding the Requirement: The company needs to copy files generated by an on-premises application to AWS without modifying the application code. The files are stored on an SMB file share and require a low-latency connection to the application servers.

Analysis of Options:

Amazon Elastic File System (EFS): EFS is designed for Linux-based workloads and does not natively support SMB file shares.

Amazon FSx for Windows File Server: FSx supports SMB file shares but would require changes to the application or additional infrastructure to connect on-premises systems.

AWS Snowball: Suitable for large data transfers but not for continuous, low-latency file copying.

AWS Storage Gateway: Provides a hybrid cloud storage solution, supporting SMB file shares and enabling seamless copying of files to AWS without requiring changes to the application.

Best Solution:

AWS Storage Gateway: This service meets the requirement for a low-latency, seamless file transfer solution from on-premises to AWS without modifying the application code.

Understanding the Requirement: The company needs to design a scalable and serverless solution for a near-real-time streaming application that experiences high latency due to large amounts of incoming data. The job processing takes about 30 minutes.

Analysis of Options:

Amazon Kinesis Data Firehose: Provides a fully managed service for real-time data streaming and ingestion, allowing for seamless data delivery to destinations such as Amazon S3, Redshift, and Elasticsearch.

AWS Lambda with AWS Step Functions: While suitable for orchestration and lightweight processing, Lambda might not handle long-running jobs (max 15 minutes execution limit) efficiently.

AWS DMS: Primarily used for database migration, not for real-time data ingestion in this context.

Amazon EC2 in Auto Scaling Group: Provides scalability but involves managing servers, which is not serverless and adds operational overhead.

AWS Fargate with ECS: Offers a serverless compute engine for containers, allowing easy scaling and management without managing the underlying infrastructure.

Best Solution:

Amazon Kinesis Data Firehose: For ingesting the streaming data efficiently.

AWS Fargate with ECS: For processing the data in a scalable and serverless manner.

AWS Outposts is a fully managed service that delivers AWS infrastructure and services to virtually any on-premises or edge location for a consistent hybrid experience. AWS Outposts supports Amazon EKS, which is a managed service that makes it easy to run Kubernetes on AWS and on-premises. By installing an AWS Outposts rack in the company’s data center, the company can run containers in a Kubernetes environment using Amazon EKS and other AWS managed services, while keeping the data locally in the company’s data center and meeting the compliance requirements. AWS Outposts also provides a seamless connection to the local AWS Region for access to a broad range of AWS services.

Option A is not a valid solution because AWS Local Zones are not deployed in the company’s data center, but in large metropolitan areas closer to end users. AWS Local Zones are owned, managed, and operated by AWS, and they provide low-latency access to the public internet and the local AWS Region. Option B is not a valid solution because AWS Snowmobile is a service that transports exabytes of data to AWS using a 45-foot long ruggedized shipping container pulled by a semi-trailer truck. AWS Snowmobile is not designed for running containers or AWS managed services on-premises, but for large-scale data migration. Option D is not a valid solution because AWS Snowball Edge Storage Optimized is a device that provides 80 TB of HDD or 210 TB of NVMe storage capacity for data transfer and edge computing. AWS Snowball Edge Storage Optimized does not support Amazon EKS or other AWS managed services, and it is not suitable for running containers in a Kubernetes environment.

A service control policy (SCP) is a type of policy that you can use to manage permissions in your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization, allowing you to ensure your accounts stay within your organization’s access control guidelines. SCPs are available only in an organization that has all features enabled. SCPs do not grant permissions; instead, they specify the maximum permissions for an organization or organizational unit (OU). SCPs limit permissions that identity-basedpolicies or resource-based policies grant to entities (users or roles) within the account, but do not grant permissions to entities. You can use SCPs to restrict the actions that the root user in an account can perform. You can also use SCPs to prevent users or roles in any account from creating or modifying certain AWS resources, such as EC2 instances with public IP addresses or IAM resources with inline policies or “". For example, you can create an SCP that denies the ec2:RunInstances action if the request includes the AssociatePublicIpAddress parameter set to true. You can also create an SCP that denies the iam:PutUserPolicy and iam:PutRolePolicy actions if the request includes a policy document that contains "”. By attaching these SCPs to your organization or OUs, you can prevent the deployment of AWS CloudFormation stacks that violate these rules.

AWS Control Tower proactive controls are guardrails that enforce preventive policies on your accounts and resources. Proactive guardrails are implemented as AWS Organizations service control policies (SCPs) and AWS Config rules. However, AWS Control Tower does not provide a built-in proactive guardrail to block EC2 instances with public IP addresses or IAM resources with inline policies or “*”. You would have to create your own custom guardrails using AWS CloudFormation templates and SCPs, which is essentially the same as option D. Therefore, option A is not correct.

AWS Control Tower detective controls are guardrails that detect and alert on policy violations in your accounts and resources. Detective guardrails are implemented as AWS Config rules and Amazon CloudWatch alarms. Detective guardrails do not block or remediate noncompliant resources; they only notify you of the issues. Therefore, option B is not correct.

AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. AWS Config continuously monitors and records your AWS resource configurations and allows you to automate the evaluation of recorded configurations against desired configurations. AWS Config rules are customizable, AWS Lambda functions that AWS Config invokes to evaluate your AWS resource configurations. You can use AWS Config rules to check for compliance with your policies, such as ensuring that EC2 instances have public IP addresses disabled or IAM resources do not have inline policies or “*”. However, AWS Config rules alone cannot prevent the deployment of AWS CloudFormation stacks that violate these policies; they can only report the compliance status. You would need to use another service, such as AWS Systems Manager Session Manager, to run automation scripts to delete or modify the noncompliant resources. This would require additional configuration and permissions, and may not be the most efficient or secure way to enforce your policies. Therefore, option C is not correct.

Understanding the Requirement: The company needs to migrate applications to AWS, maintaining isolated networks while allowing communication with a shared services VPC and among the applications.

Analysis of Options:

Software VPN Tunnels: This approach involves high administrative overhead and complexity in managing multiple VPN connections.

VPC Peering: While suitable for smaller numbers of VPCs, it becomes complex and hard to manage at scale with over 100 applications.

Direct Connect: Primarily used for high-bandwidth, low-latency connections to on-premises networks, not inter-VPC communication.

Transit Gateway: Simplifies network management by acting as a central hub, allowing easy routing and scalability as more applications are migrated.

Best Solution:

Transit Gateway: This provides a scalable, efficient solution with minimal administrative overhead for managing network connections between multiple VPCs and the shared services VPC.

Understanding the Requirement: The company wants to migrate an application to AWS, increase its availability, and use AWS WAF in the architecture.

Analysis of Options:

Auto Scaling group with ALB and WAF: This option provides high availability by distributing instances across multiple Availability Zones. The ALB ensures even traffic distribution, and AWS WAF provides security at the application layer.

Cluster placement group with ALB and WAF: Cluster placement groups are for low-latency networking within a single AZ, which does not provide the high availability across AZs.

Two EC2 instances with ALB and WAF: This setup provides some availability but does not scale automatically, missing the benefits of an Auto Scaling group.

Auto Scaling group with WAF directly: AWS WAF cannot be directly connected to an Auto Scaling group; it needs to be attached to an ALB, CloudFront distribution, or API Gateway.

Best Solution:

Auto Scaling group with ALB and WAF: This configuration ensures high availability, scalability, and security, meeting all the requirements effectively.

Understanding the Requirement: Senior leadership wants a custom dashboard displaying NAT gateway costs daily, starting from the beginning of the current month.

Analysis of Options:

QuickSight with DataSync: While QuickSight is suitable for dashboards, DataSync is not designed for querying and analyzing data reports.

QuickSight with Athena: QuickSight can visualize data queried by Athena, which is designed to analyze data directly from S3.

CloudWatch with DataSync: CloudWatch is primarily for monitoring metrics, not for creating detailed cost analysis dashboards.

CloudWatch with Athena: Similarly, using CloudWatch with Athena does not align well with the requirement for a visual dashboard.

Best Solution for Visualization and Querying:

Amazon QuickSight with Athena: This combination allows for powerful data visualization and querying capabilities. QuickSight can create dynamic dashboards, while Athena efficiently queries the cost and usage report data stored in S3.

Understanding the Requirement: The application running in a private subnet needs to store and retrieve data from S3 without data traveling over the public internet.

Analysis of Options:

NAT Gateway: Allows private subnets to access the internet but incurs additional costs and still routes traffic through the public internet.

AWS Storage Gateway: Provides hybrid cloud storage solutions but is not the most cost-effective for direct S3 access from within the VPC.

S3 Interface Endpoint: Provides private access to S3 but is generally used for specific use cases where more granular control is required, which might be overkill and more expensive.

S3 Gateway Endpoint: Provides private, cost-effective access to S3 from within the VPC without routing traffic through the public internet.

Best Solution:

S3 Gateway Endpoint: This option meets the requirements for secure, private access to S3 from a private subnet most cost-effectively.