SAA-C03 Amazon Web Services AWS Certified Solutions Architect - Associate (SAA-C03) Free Practice Exam Questions (2025 Updated)

By using an SQS queue and Lambda, the solutions architect can decouple the API front end from the processing microservices and improve the overall scalability and availability of the system. The SQS queue acts as a buffer, allowing the API front end to continue accepting user requests even if the processing microservices are experiencing high workloads or are temporarilyunavailable. The Lambda function can then retrieve requests from the SQS queue and write them to DynamoDB, ensuring that all user requests are stored and processed. This approach allows the company to scale the processing microservices independently from the API front end, ensuring that the API remains available to users even during periods of high demand.

This solution meets the requirements of a serverless solution, encryption, replication, and SQL analysis with the least operational overhead. Amazon Athena is a serverless interactive query service that can analyze data in S3 using standard SQL. S3 Cross-Region Replication (CRR) can replicate encrypted objects to an S3 bucket in another Region automatically. Server-side encryption with AWS KMS multi-Region keys (SSE-KMS) can encrypt the data at rest using keys that are replicated across multiple Regions. Creating a new S3 bucket can avoid potential conflicts with existing data or configurations.

Option B is incorrect because Amazon RDS is not a serverless solution and it cannot query data in S3 directly. Option C is incorrect because server-side encryption with Amazon S3 managed encryption keys (SSE-S3) does not use KMS keys and it does not support multi-Region replication. Option D is incorrect because Amazon RDS is not a serverless solution and it cannot query data in S3 directly. It is also incorrect for the same reason as option C.

**AWS PrivateLink provides private connectivity between VPCs, AWS services, and your on-premises networks, without exposing your traffic to the public internet**. AWS PrivateLink makes it easy to connect services across different accounts and VPCs to significantly simplify your network architecture. Interface **VPC endpoints**, powered by AWS PrivateLink, connect you to services hosted by AWS Partners and supported solutions available in AWS Marketplace. https://aws.amazon.com/privatelink/

Reserved is cheaper than on demand the company has. And it's meet the availabilty (HA) requirement as to spot instance that can be disrupted at any time. PRICING BELOW. On-Demand: 0% There’s no commitment from you. You pay the most with this option. Reserved : 40%-60%1-year or 3-year commitment from you. You save money from that commitment. Spot 50%-90% Ridiculously inexpensive because there’s no commitment from the AWS side.

https://aws.amazon.com/about-aws/whats-new/2017/10/aws-waf-now-supports-geographic-match/

This solution meets the requirements of a customer-facing application that has a clearly defined access pattern throughout the year and a variable number of reads and writes that depend on the time of year. Amazon DynamoDB is a fully managed NoSQL database service that can handle any level of request traffic and data size. DynamoDB auto scaling can automatically adjust the provisioned read and write capacity based on the actual workload. DynamoDB on-demand backups can create full backups of the tables for data protection and archival purposes. DynamoDB Streams can capture a time-ordered sequence of item-level modifications in the tables for audit purposes.

Option B is incorrect because Amazon Redshift is a data warehouse service that is designed for analytical workloads, not for customer-facing applications. Option C is incorrect because Amazon RDS with Provisioned IOPS can provide consistent performance for relational databases, but it may not be able to handle unpredictable spikes in traffic and data size. Option D is incorrect because Amazon Aurora MySQL with auto scaling can provide high performance and availability for relational databases, but it does not support audit logging as a parameter.

https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/monitor-ami-events.html#:~:text=For%20example%2C%20you%20can%20create%20an%20EventBridge%20rule%20that%20detects%20when%20the%20AMI%20creation%20process%20has %20completed%20and%20then%20invokes%20an%20Amazon%20SNS%20topic%20to%20send%20an%20email%20notification%20to%20you.

Creating an Amazon EventBridge (Amazon CloudWatch Events) rule for the CreateImage API call and configuring the target as an Amazon Simple Notification Service (Amazon SNS) topic to send an alert when a CreateImage API call is detected will meet the requirements with the least operational overhead. Amazon EventBridge is a serverless event bus that makes it easy to connect applications together using data from your own applications, integrated Software as a Service (SaaS) applications, and AWS services. By creating an EventBridge rule for the CreateImage API call, the company can set up alerts whenever this operation is called within their account. The alert can be sent to an SNS topic, which can then be configured to send notifications to the company's email or other desired destination.

This approach ensures that the order creation and payment processing steps are separate and atomic. By sending the order information to an SQS FIFO queue, the payment service can process the order one at a time and in the order they were received. If the payment service is unable to process an order, it can be retried later, preventing the creation of multiple orders. The deletion of the message from the queue after it is processed will prevent the same message from being processed multiple times.

AWS CloudFormationallows for the automated, repeatable setup of infrastructure, reducing human error and ensuring consistency.AWS Configprovides the ability to track changes in the infrastructure, ensuring that all changes are logged and auditable, which satisfies the requirement for tracking incremental changes.

Option A and C (AWS Organizations): AWS Organizations manage multiple accounts, but they are not designed for infrastructure setup or change tracking.

Option D (Service Catalog): Service Catalog is used for deploying products, not for setting up infrastructure or tracking changes.

AWS References:

AWS Config

AWS CloudFormation

Cluster Placement Group: This type of placement group is designed to provide low-latency network performance and high throughput by grouping instances within a single Availability Zone. It is ideal for applications that require tightly coupled node-to-node communication.

Configuration:

When launching EC2 instances, specify the option to launch them in a cluster placement group.

This ensures that the instances are physically located close to each other, reducing latency and increasing network throughput.

Benefits:

Low-Latency Communication: Instances in a cluster placement group benefit from enhanced networking capabilities, enabling low-latency communication.

High Network Throughput: The network performance within a cluster placement group is optimized for high throughput, which is essential for HPC workloads.

https://aws.amazon.com/blogs/compute/building-loosely-coupled-scalable-c-applications-with-amazon-sqs-and-amazon-sns/

https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-dead-letter-queues.html

AWS Control Tower: Provides a managed service to set up and govern a secure, multi-account AWS environment based on AWS best practices. It automates the setup of AWS Organizations and applies security controls (guardrails).

Networking Account:

Create a centralized networking account that includes a VPC with both private and public subnets.

This centralized VPC will manage and control the networking resources.

AWS Resource Access Manager (AWS RAM):

Use AWS RAM to share the subnets from the networking account with the other workload accounts.

This allows different workload accounts to utilize the shared networking resources without the need to manage their own VPCs.

Operational Efficiency: Using AWS Control Tower simplifies the setup and governance of multiple AWS accounts, while AWS RAM facilitates centralized management of networking resources, reducing operational overhead and ensuring consistent security and compliance.

AWS Site-to-Site VPN: This provides a secure and encrypted connection between an on-premises environment and AWS. It is a cost-effective solution suitable for low bandwidth and small traffic needs.

Quick Setup:

Site-to-Site VPN can be quickly set up by configuring a virtual private gateway on the AWS side and a customer gateway on the on-premises side.

It uses standard IPsec protocol to establish the VPN tunnel.

Cost-Effectiveness: Compared to AWS Direct Connect, which requires dedicated physical connections and higher setup costs, a Site-to-Site VPN is less expensive and easier to implement for smaller traffic requirements.

AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. By creating a Config rule, you can automatically check whether your Amazon EBS volumes are encrypted and flag those that are not, with minimal cost and configuration effort.

AWS Config Rule: AWS Config provides managed rules that you can use to automatically check the compliance of your resources against predefined or custom criteria. In this case, you wouldcreate a rule to evaluate EBS volumes and determine if they are encrypted. If a volume is not encrypted, the rule will flag it, allowing you to take corrective action.

Operational Overhead: This approach significantly reduces operational overhead because once the rule is in place, it continuously monitors your EBS volumes for compliance, and there’s no need for manual checks or custom scripting.

Why Not Other Options?:

Option A (Lambda with API calls and EventBridge): While this can work, it involves writing and maintaining custom code, which increases operational overhead compared to using a managed AWS Config rule.

Option B (API calls on Fargate): Running API calls on Fargate is more complex and costly compared to using AWS Config, which provides a simpler, managed solution.

Option C (IAM policy with Cost Explorer): This option does not directly enforce encryption compliance and involves manual intervention, making it less efficient and more prone to errors.

AWS References:

AWS Config Rules- Overview of AWS Config rules and how they can be used to evaluate resource configurations.

Amazon EBS Encryption- Information on how to manage and enforce encryption for EBS volumes.

The issue in this case is related to the processing tier, where EC2 instances are overwhelmed at peak times, causing delays.Option D, using anAmazon EC2 Auto Scaling target tracking policybased on theApproximateNumberOfMessagesin the SQS queue, is the best solution.

Auto Scaling with Target Tracking:

Target tracking policiesdynamically scale out or in based on a specific metric. For this use case, you can monitor theApproximateNumberOfMessagesin the SQS queue. When the number of messages (orders) in the queue increases, the Auto Scaling group will scale out more EC2 instances to handle the additional load, ensuring that the queue doesn’t build up and cause delays.

This solution is ideal for handling variable and unpredictable peak times, as Auto Scaling can automatically adjust based on real-time load rather than scheduled times.

Why Not the Other Options?:

Option A (Scheduled Scaling): Scheduled scaling works well for predictable peak times, but this company experiencesunpredictable peak usage, making scheduled scaling less effective.

Option B (ElastiCache for Redis): Adding a caching layer would help if DynamoDB were the bottleneck, but in this case, the issue is CPU overload on EC2 instances in the processing tier.

Option C (CloudFront): CloudFront would help cache static content from the web tier, but it wouldn’t resolve the issue of the processing tier’s overloaded EC2 instances.

AWS References:

Amazon EC2 Auto Scaling Target Tracking

Amazon SQS ApproximateNumberOfMessages

Amazon API Gateway supportsresource policies, which allow you to control access to your API by specifying the IP addresses or ranges that can access the API. By creating a resource policythat explicitly denies access to any IP address outside the allowed set, you can ensure that only trusted IP addresses (such as those from your internal network) can access the critical information in your API. This approach provides fine-grained access control without the need for additional infrastructure or complex configurations.

Option A (Private integration): API Gateway private integrations are for creating private APIs that are only accessible within a VPC, but this solution is about restricting access to certain IP addresses.

Option C (Private subnet and ACLs): Deploying the API in a private subnet and using network ACLs adds unnecessary complexity and isn't the best fit for HTTP APIs.

Option D (Security group): API Gateway doesn't have a security group because it isn't a resource inside a VPC. Instead, resource policies are the correct mechanism for controlling IP-based access.

AWS References:

Controlling Access to API Gateway with Resource Policies

AmazonSES (Simple Email Service)allows for the automatic ingestion of incoming emails. By setting up email receiving in SES and creating a rule set with a receipt rule, you can configure SES to invoke anAWS Lambda functionwhenever an email is received. The Lambda function can then process the email body and attachments, saving any attachments to an Amazon S3 bucket. This solution is highly scalable, cost-effective, and provides near real-time processing of emails with minimal operational overhead.

Option B (Content filtering): This only filters emails based on content and does not provide the functionality to save attachments to S3.

Option C (S3 Event Notifications): While SES can store emails in S3, SES with Lambda offers more flexibility for processing attachments in real-time.

Option D (EventBridge rule): EventBridge cannot directly listen for incoming emails, making this solution incorrect.

AWS References:

Receiving Email with Amazon SES

Invoking Lambda from SES

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.

This solution provides the most secure access for external support engineers with the least exposure to potential security risks.

AWS Systems Manager (SSM) and Session Manager: Systems Manager Session Manager allows secure and auditable access to EC2 instances without the need to open inbound SSH ports or manage SSH keys. This reduces the attack surface significantly. The SSM Agent must be installed and configured on all instances, and the instances must have an instance profile with the necessary IAM permissions to connect to Systems Manager.

IAM Identity Center: IAM Identity Center provides centralized management of access to the AWS Management Console for external support engineers. By using IAM Identity Center, youcan control console access securely and ensure that external engineers have the appropriate permissions based on their roles.

Why Not Other Options?:

Option B (Local IAM user credentials): This approach is less secure because it involves managing local IAM user credentials and does not leverage the centralized management and security benefits of IAM Identity Center.

Option C (Security group with SSH access): Allowing SSH access opens up the infrastructure to potential security risks, even when restricted by IP addresses. It also requires managing SSH keys, which can be cumbersome and less secure.

Option D (Bastion host): While a bastion host can secure SSH access, it still requires managing SSH keys and opening ports. This approach is less secure and more operationally intensive compared to using Session Manager.

AWS References:

AWS Systems Manager Session Manager- Documentation on using Session Manager for secure instance access.

AWS IAM Identity Center- Overview of IAM Identity Center and its capabilities for managing user access.

Amazon RDS Proxy: RDS Proxy is a fully managed, highly available database proxy that makes applications more resilient to database failures by pooling and sharing connections, and it can automatically handle database failovers.

Reduced Failover Time: By using RDS Proxy, the connection management between the application and the database is improved, reducing failover times significantly. RDS Proxy maintains connections in a connection pool and reduces the time required to re-establish connections during a failover.

Configuration:

Create an RDS Proxy instance.

Configure the proxy to connect to the RDS for PostgreSQL DB instance.

Modify the application configuration to use the RDS Proxy endpoint instead of the direct database endpoint.

Operational Benefits: This solution provides high availability and reduces application timeouts during failovers with minimal changes to the application code.

AWSDirect Connectis the best solution for establishing a consistent, low-latency connection from an on-premises data center to AWS without using the public internet. Direct Connect offers dedicated, high-throughput, and low-latency network connections, which are ideal for performance-sensitive applications like a trading platform that processes high volumes of market data and stock trades.

Direct Connect provides a private connection to your AWS VPC, ensuring that data doesn't traverse the public internet, which enhances both security and performance consistency.

AWS References:

AWS Direct Connectprovides a dedicated network connection to AWS services with consistent, low-latency performance.

Best Practices for High Performance on AWSfor performance-sensitive workloads like trading platforms.

Why the other options are incorrect:

A. AWS Client VPN: While this offers secure connectivity, it's over the public internet and is not designed for the low-latency, high-performance needs of a trading platform.

C. AWS PrivateLink: PrivateLink is used for connecting VPCs and services within AWS, but it is not designed for connecting on-premises data centers to AWS.

D. AWS Site-to-Site VPN: Although this provides secure connectivity, it uses the public internet, which can introduce latency and doesn't meet the low-latency requirements of the use case.

Option B: Pre-signed URLs provide temporary, authenticated access to S3, limiting uploads to the time frame specified. This solution is lightweight, efficient, and easy to implement.

Option Arequires the management of IAM temporary credentials, adding complexity.

Option Cinvolves unnecessary development effort.

Option Dintroduces more complexity with STS and roles than pre-signed URLs.

Amazon EFSwithMax I/O performance modeis designed for workloads that require high levels of parallelism, such as video processing across multiple EC2 instances. EFS provides shared file storage that can be mounted on both Windows and Linux EC2 instances, and the Max I/O mode ensures the best performance for handling large files and concurrent access across multiple instances.

Option A and B (FSx for Windows File Server): FSx for Windows File Server is optimized for Windows workloads and would not be ideal for Linux instances or high-throughput, parallel workloads.

Option D (EFS General Purpose mode): General Purpose mode offers lower latency but doesn't support the high throughput needed for large, concurrent workloads.

AWS References:

Amazon EFS Performance Modes

VPC Endpoint for S3: A gateway endpoint for Amazon S3 enables you to privately connect your VPC to S3 without requiring an internet gateway, NAT device, VPN connection, or AWS Direct Connect connection.

Configuration Steps:

In the VPC console, navigate to "Endpoints" and create a new endpoint.

Select the service name for S3 (com.amazonaws.region.s3).

Choose the VPC and the subnets where your EC2 instances are running.

Update the route tables for the selected subnets to include a route pointing to the endpoint.

Security Compliance: By configuring an S3 gateway endpoint, all traffic between the VPC and S3 stays within the AWS network, complying with the company's security regulations to avoid internet traversal.

Amazon S3 Intelligent-Tiering: This storage class is designed to optimize costs by automatically moving data between two access tiers (frequent and infrequent) when access patterns change. It provides cost savings without performance impact or operational overhead.

S3 Lifecycle Rules: By creating an S3 Lifecycle rule, the company can automatically transition objects to the Intelligent-Tiering storage class. This eliminates the need for manual intervention and ensures that objects are moved to the most cost-effective storage tier based on their access patterns.

Operational Efficiency: Intelligent-Tiering requires no additional management and delivers immediate availability for frequently accessed objects. This makes it the most operationally efficient solution for the given requirements.

This solution is the most suitable for running cron jobs on AWS with minimal refactoring, while also supporting the possibility of running jobs in response to future events.

Container Image for Cron Jobs: By containerizing the cron jobs, you can package the environment and dependencies required to run the jobs, ensuring consistency and ease of deployment across different environments.

Amazon EventBridge Scheduler: EventBridge Scheduler allows you to create a recurring schedule that can trigger tasks (like running your cron jobs) at specific times or intervals. It provides fine-grained control over scheduling and integrates seamlessly with AWS services.

AWS Fargate: Fargate is a serverless compute engine for containers that removes the need to manage EC2 instances. It allows you to run containers without worrying about the underlying infrastructure. Fargate is ideal for running jobs that can vary in duration, like cron jobs, as it scales automatically based on the task's requirements.

Why Not Other Options?:

Option A (Lambda): While AWS Lambda could handle short-running cron jobs, it has limitations in terms of execution duration (maximum of 15 minutes) and might not be suitable for jobs that run up to 20 minutes.

Option B (AWS Batch on ECS): AWS Batch is more suitable for batch processing and workloads that require complex job dependencies or orchestration, which might be more than what is needed for simple cron jobs.

Option D (Step Functions with Wait State): While Step Functions provide orchestration capabilities, this approach would introduce unnecessary complexity and overhead compared to the straightforward scheduling with EventBridge and running on Fargate.

AWS References:

Amazon EventBridge Scheduler- Details on how to schedule tasks using Amazon EventBridge Scheduler.

AWS Fargate- Information on how to run containers in a serverless manner using AWS Fargate.

This solution meets the requirement of encrypting each customer’s data separately with the least operational overhead by leveraging AWS Key Management Service (KMS).

Separate AWS KMS Keys: By creating separate KMS keys for each customer, you can ensure that each customer’s data is encrypted with a unique key. This approach satisfies the compliance requirement for separate encryption and provides fine-grained control over access to the keys.

Granular Access Control: AWS KMS allows you to define key policies and use IAM policies to grant specific permissions to the keys. This ensures that only authorized users or services can access the keys, thereby maintaining the principle of least privilege.

Logging and Monitoring: AWS KMS integrates with AWS CloudTrail, which logs all key usage and management activities. This provides an audit trail that is essential for meeting compliance requirements.

Why Not Other Options?:

Option A (Store keys in S3): Storing keys in S3 is not recommended because it does not provide the same level of security, access control, or integration with AWS services as KMS does.

Option B (Hardware security appliance): Deploying a hardware security appliance adds significant operational overhead and complexity, which is unnecessary given that KMS already provides a secure and centralized key management solution.

Option C (Single KMS key for all data): Using a single KMS key does not meet the requirement of encrypting each customer's data separately.

AWS References:

AWS Key Management Service (KMS)- Overview of KMS, its features, and best practices for key management.

Using AWS KMS for Multi-Tenant Applications- Guidance on how to design applications using KMS for multi-tenancy.

Amazon Macieis purpose-built for detecting PII in S3.

Option Auses EventBridge to filter SensitiveData findings and notify via SNS, meeting the requirements.

Options B and Dinvolve GuardDuty, which is not designed for PII detection.

Option Cuses SQS, which is less suitable for immediate notifications.

To address the high CPU utilization on the EC2 instance and the degraded performance of Amazon RDS for read requests, the solution involves two key actions: resizing the EC2 instance and leveraging Amazon RDS read replicas.

Resizing the EC2 Instance: The first step is to resize the EC2 instance to a type with more CPU capacity to handle the higher computational demands during peak usage times. This helps to alleviate the immediate pressure on the CPU.

Auto Scaling Group with a Size of 1: Although the application can only run on a single EC2 instance due to its monolithic nature, creating an Auto Scaling group with a minimum and maximum size of 1 ensures that the instance is automatically restarted or replaced in case of failure, maintaining high availability.

RDS Read Replica: Configuring an RDS read replica allows the application to offload read requests to a separate instance, thus reducing the load on the primary RDS instance. This improves the performance of read operations, which were previously bottlenecked due to the high CPU usage on the EC2 instance.

Why Not Other Options?:

Option B: Redirecting all traffic to the RDS read replica is not recommended because replicas are meant for read traffic only, not for write operations. This could lead to data consistency issues.

Option C: Increasing the RDS instance type capacity helps, but it doesn’t address the high CPU usage on the EC2 instance, nor does it provide a solution for scaling reads.

Option D: While resizing both the EC2 and RDS instances increases their capacities, it doesn’t address the specific need to offload read traffic from the primary RDS instance.

AWS References:

Amazon RDS Read Replicas- Explains how to create and use read replicas to offload read traffic from the primary database instance.

Resizing Your EC2 Instance- Guidance on resizing EC2 instances to meet workload demands.

Amazon Athena provides a cost-effective, serverless way to query data without affecting the performance of DynamoDB. By using the Athena DynamoDB connector, the company can perform the necessary SQL queries without consuming read capacity on the DynamoDB table, which is essential for minimizing impact on provisioned throughput.

Key benefits:

Minimal Impact on Provisioned Capacity: Athena queries do not directly impact DynamoDB’s read capacity, making it ideal for running analytics without affecting the customer-facing workloads.

Cost-Effective: Athena is a serverless solution, meaning you pay only for the queries you run, making it highly cost-effective compared to running a dedicated cluster like Amazon EMR or Redshift.

AWS Documentation: The use of Athena to query DynamoDB through its connector aligns with AWS's best practices for performance efficiency and cost optimization​​.

The company is looking for a solution that provides single sign-on (SSO) across multiple AWS accounts while continuing to manage users and groups in their on-premises Active Directory (AD). AWS IAM Identity Center (formerly AWS SSO) is the recommended solution for this type of requirement.

AWS IAM Identity Centerprovides a centralized identity management solution, enabling single sign-on across multiple AWS accounts and other cloud applications. It can integrate with on-premises Active Directory to leverage existing users and groups.

By configuring a two-way forest trust relationship between AWS Directory Service for Microsoft Active Directory and the company's on-premises Active Directory, users can be authenticated by their on-premises AD and still access AWS resources through IAM Identity Center. This solution allows centralized management of AWS accounts within AWS Organizations.

The two-way trust allows mutual access between the on-premises AD and the AWS Directory Service. This means that users and groups in the on-premises AD can be used for authentication in AWS IAM Identity Center while maintaining the existing identity management system.

AWS References:

AWS IAM Identity Center Documentation

AWS Directory Service for Microsoft Active Directory Trust Relationships

AWS Directory Service Integration with IAM Identity Center

Why the other options are incorrect:

A. Create an Enterprise Edition Active Directory in AWS Directory Service: This would require setting up a new directory and managing it in AWS, which adds unnecessary overhead. The requirement is to continue using the existing on-premises AD, making this option unsuitable.

C. Use AWS Directory Service and create a two-way trust relationship: While this approach establishes a trust between on-premises AD and AWS Directory Service, it does not address the single sign-on (SSO) requirements across multiple AWS accounts through IAM Identity Center.

D. Deploy an identity provider (IdP) on Amazon EC2: This is more complex than necessary and introduces more management overhead. AWS IAM Identity Center natively supports integration with on-premises Active Directory without requiring a custom IdP.

Option Ais the simplest solution, using DynamoDB Streams and Lambda for real-time ingestion into S3.

Options B, C, and Dadd unnecessary complexity with Data Firehose or Kinesis.

TheGateway Load Balancer (GWLB)is specifically designed to route traffic through a security appliance in a hub-and-spoke model, making it the ideal solution for inspecting traffic between multiple AWS accounts. GWLB enables you to simplify, scale, and deploy third-party virtual appliances transparently, and it can work across multiple VPCs or accounts using interface endpoints (Gateway Load Balancer Endpoints).

Key AWS features:

Traffic Inspection: The GWLB allows the centralized security appliance to inspect traffic between different VPCs, making it suitable for inspecting inter-account interactions.

Interface VPC Endpoints: By using interface endpoints in the application accounts, traffic can securely and efficiently be routed to the security appliance in the networking account.

AWS Documentation: The use of GWLB aligns with AWS’s best practices for centralized network security, simplifying architecture and reducing operational complexity​.

Understanding the Requirement: The job is stateful, cannot tolerate interruptions, and needs to run reliably for at least one hour each week.

Analysis of Options:

AWS Fargate with Amazon ECS and EventBridge: This option provides a serverless compute engine for containers that can run stateful tasks reliably. Using EventBridge Scheduler, the job can be triggered automatically at the specified time without manual intervention.

AWS Lambda with EventBridge: Lambda functions are not suitable for long-running stateful jobs since they have a maximum execution time of 15 minutes.

EC2 Spot Instances: Spot Instances can be interrupted, making them unsuitable for a stateful job that cannot tolerate interruptions.

AWS DataSync: This service is primarily for moving large amounts of data and is not designed to run stateful analysis jobs.

Best Option for Reliable, Scheduled Execution:

The Fargate task on ECS with EventBridge Scheduler meets all requirements, providing the necessary reliability and scheduling capabilities without interruption risks.

AWS Secrets Manager is designed specifically to securely store and manage sensitive information such as database credentials. It integrates seamlessly with AWS services like Lambda and RDS, and it provides automatic credential rotation with minimal operational overhead.

AWS Secrets Manager: By storing the database credentials in Secrets Manager, you ensure that the credentials are securely stored, encrypted, and managed. Secrets Manager provides a built-in mechanism to automatically rotate credentials at regular intervals (e.g., every 30 days), which helps in maintaining security best practices without requiring additional manual intervention.

Lambda Integration: The Lambda function can be easily configured to retrieve the credentials from Secrets Manager using the AWS SDK, ensuring that the credentials are accessed securely at runtime.

Why Not Other Options?:

Option A (Parameter Store with Rotation): While Parameter Store can store parameters securely, Secrets Manager is more tailored for secrets management and automatic rotation, offering more features and less operational overhead.

Option C (Encrypted Lambda environment variable): Storing credentials directly in Lambda environment variables, even when encrypted, requires custom code to manage rotation, which increases operational complexity.

Option D (KMS with automatic rotation): KMS is for managing encryption keys, not for storing and rotating secrets like database credentials. This option would require more custom implementation to manage credentials securely.

AWS References:

AWS Secrets Manager- Detailed documentation on how to store, manage, and rotate secrets using AWS Secrets Manager.

Using Secrets Manager with AWS Lambda- Guidance on integrating Secrets Manager with Lambda for secure credential management.

AWS Backup is the most appropriate solution for managing backups with minimal operational overhead while meeting the regulatory requirement to retain data for 90 days and enabling point-in-time restore for up to 14 days.

AWS Backup: AWS Backup provides a centralized backup management solution that supports automated backup scheduling, retention management, and compliance reporting across AWS services, including Amazon RDS. By creating a backup plan, you can define a retention period (in this case, 90 days) and automate the backup process.

Point-in-Time Restore (PITR): Amazon RDS supports point-in-time restore for up to 35 days with automated backups. By using AWS Backup in conjunction with RDS, you ensure that your backup strategy meets the requirement for restoring data to a specific point in time within the last 14 days.

Why Not Other Options?:

Option A (RDS Automated Backups): While RDS automated backups support PITR, they do not directly support retention beyond 35 days without manual intervention.

Option B (Manual Snapshots): Manually creating and managing snapshots is operationally intensive and less automated compared to AWS Backup.

Option C (Aurora Clones): Aurora Clone is a feature specific to Amazon Aurora and is not applicable to Amazon RDS for Oracle.

AWS References:

AWS Backup- Overview of AWS Backup and its capabilities.

Amazon RDS Automated Backups- Information on how RDS automated backups work and their limitations.

AWS Glue Crawler: AWS Glue is a fully managed ETL (Extract, Transform, Load) service that makes it easy to prepare and load data for analytics. A Glue crawler can automatically discover new data and schema in Amazon S3, making it easy to keep the data catalog up-to-date.

Crawling the Data:

Set up an AWS Glue crawler to scan the S3 bucket containing the clickstream data.

The crawler will automatically detect the schema and create/update the tables in the AWS Glue Data Catalog.

Amazon Athena:

Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.

Once the data catalog is updated by the Glue crawler, use Athena to query the clickstream data directly in S3.

Operational Efficiency: This solution leverages fully managed services, reducing operational overhead. Glue crawlers automate data cataloging, and Athena provides a serverless, pay-per-query model for quick data analysis without the need to set up or manage infrastructure.

Setting the RDS backup retention policy to 30 days forautomated backupsthrough AWS Backup allows the company to retain backups cost-effectively. Manual backups, however, are notautomatically managed by RDS's retention policy, so they need to be manually deleted if they are older than 30 days to avoid unnecessary storage costs.

Key AWS features:

Automated Backups: Can be configured with a retention policy of up to 35 days, ensuring that older automated backups are deleted automatically.

Manual Backups: These are not subject to the automated retention policy and must be manually managed to avoid extra costs.

AWS Documentation: AWS recommends using backup retention policies for automated backups while manually managing manual backups​.

To make the application highly available across regions:

Deploy the application in a different region using a newECS clusterandALBto ensure regional redundancy.

UseRoute 53 failover routingto automatically direct traffic to the healthy region in case of failure.

UseDynamoDB Global Tablesto ensure the database is replicated and available across multiple regions, supporting read and write operations in each region.

Option D (EKS cluster in the same region): This does not provide regional redundancy.

Option E (Global Secondary Indexes): GSIs improve query performance but do not provide multi-region availability.

Option F (PrivateLink): PrivateLink is for secure communication, not for cross-region high availability.

AWS References:

DynamoDB Global Tables

Amazon ECS with ALB

The most cost-effective and scalable solution for generating thumbnails when photos are uploaded to an S3 bucket is to useS3 event notificationsto trigger anAWS Lambda function. This approach avoids the need for a long-running EC2 instance or EMR cluster, making it highly cost-effective because Lambda only charges for the time it takes to process each event.

S3 Event Notifications: Automatically triggers the Lambda function when a new photo is uploaded to the S3 bucket.

AWS Lambda: A serverless compute service that scales automatically and only charges for execution time, which makes it the most economical choice when dealing with periodic events like photo uploads.

The Lambda function can generate the thumbnail and upload it to a second S3 bucket, fulfilling the requirement efficiently.

Option AandOption B(EMR or EC2 with scheduled scripts)**: These are less cost-effective as they involve continuously running infrastructure, which incurs unnecessary costs.

Option D (S3 Storage Lens): S3 Storage Lens is a tool for storage analytics and is not designed for event-based photo processing.

AWS References:

Amazon S3 Event Notifications

AWS Lambda Pricing

Amazon Elastic File System (EFS) is a managed file storage service that can be mounted across multiple EC2 instances. It provides a scalable and high-performing solution to share data among instances within a VPC.

High Performance: EFS provides scalable performance for workloads that require high throughput and IOPS. It is particularly well-suited for applications that need to share data across multiple instances.

Ease of Use: EFS can be easily mounted on multiple instances across different Availability Zones, providing a shared file system accessible to all the instances within the VPC.

Security: EFS can be configured to ensure that data remains within the VPC, and it supports encryption at rest and in transit.

Why Not Other Options?:

Option A (Amazon S3 bucket with APIs): While S3 is excellent for object storage, it is not a file system and does not provide the low-latency access required for shared data between instances.

Option B (S3 bucket as a mounted volume): S3 is not designed to be mounted as a file system, and this approach would introduce unnecessary complexity and latency.

Option C (EBS volume shared across instances): EBS volumes cannot be attached to multiple instances simultaneously. It is not designed to be shared across instances like EFS.

AWS References:

Amazon EFS- Overview of Amazon EFS and its features.

Best Practices for Amazon EFS- Recommendations for using EFS with multiple instances.

Amazon S3 Storage Lens:

S3 Storage Lens provides organization-wide visibility into object storage usage and activity trends.

It can generate metrics and insights about your S3 buckets, including versioning status.

Configuration:

Enable S3 Storage Lens at the organization level.

Configure the dashboard to include the versioning status metric.

Identify Non-Versioned Buckets:

Use the S3 Storage Lens dashboard to filter and identify buckets that do not have versioning enabled.

Storage Lens provides detailed insights and reports which can be used to enforce compliance and manage storage effectively.

Operational Efficiency: Using S3 Storage Lens provides a centralized, easy-to-use interface for monitoring bucket configurations across multiple Regions and accounts, reducing the need for custom scripts or manual checks.

This solution is the most cost-effective and meets the RPO and RTO requirements of 24 hours.

Automatic Snapshots: Amazon RDS automatically creates snapshots of your DB instance at regular intervals. By copying these snapshots to another AWS Region every 24 hours, you ensure that you have a backup available in a different geographic location, providing disaster recovery capability.

RPO and RTO: Since the company’s RPO and RTO are both 24 hours, copying snapshots daily to another Region is sufficient. In the event of a disaster, you can restore the DB instance from the most recent snapshot in the target Region.

Why Not Other Options?:

Option A (Cross-Region Read Replica): This could provide a faster recovery time but is more costly due to the ongoing replication and resource usage in another Region.

Option B (DMS Cross-Region Replication): While effective for continuous replication, it introduces complexity and cost that isn’t necessary given the 24-hour RPO/RTO.

Option C (Cross-Region Native Backup Copy): This involves more manual steps and doesn’t offer as straightforward a solution as automated snapshot copying.

AWS References:

Amazon RDS Automated Backups and Snapshots- Details on automated backups and snapshots in RDS.

Copying an Amazon RDS DB Snapshot- How to copy DB snapshots to another Region.

The company wants to reduce end-to-end load time for its global customer base.AWS Global Acceleratorprovides a network optimization service that reduces latency by routing traffic to the nearest AWS edge locations, improving the user experience for globally distributed customers.

AWS Global Accelerator:

Global Acceleratorimproves the performance of your applications by routing traffic through AWS’s global network infrastructure. This reduces the number of hops and latency compared to using the public internet.

By creating astandard acceleratorand configuring the existing NLBs as target endpoints, Global Accelerator ensures that traffic from users around the world is routed to the nearest AWS edge location and then through optimized paths to the NLBs in each region. This significantly improves end-to-end load time for global customers.

Why Not the Other Options?:

Option A (ALBs instead of NLBs): ALBs are designed for HTTP/HTTPS traffic and provide layer 7 features, but they wouldn’t solve the latency issue for a global customer base. The key problem here is latency, and Global Accelerator is specifically designed to address that.

Option B (Route 53 weighted routing): Route 53 can route traffic to different regions, but it doesn’t optimize network performance. It simply balances traffic between endpoints without improving latency.

Option C (Additional NLBs in more regions): This could potentially improve latency but would require setting up infrastructure in multiple regions. Global Accelerator is a simpler and more efficient solution that leverages AWS’s existing global network.

AWS References:

AWS Global Accelerator

By usingAWS Global Acceleratorwith the existing NLBs, the company can optimize global traffic routing and improve the customer experience by minimizing latency. Therefore,Option Dis the correct answer.

AmazonTextractcan extract text from the PDFs, andAmazon Comprehendis the most suitable service to analyze the extracted text for sentiment and insights. Comprehend offers a fully managed, low-operational overhead solution for analyzing text data. The results can then be stored in anAmazon S3bucket, ensuring scalability and easy access.

Option A: Athena is for querying structured data and is not suitable for sentiment analysis.

Option B: SageMaker adds complexity and is not necessary when Comprehend can handle sentiment analysis natively.

Option D: QuickSight is used for visualization and analytics, but it does not provide sentiment analysis.

AWS References:

Amazon Comprehend

Amazon Textract

For improving availability and performance of the hybrid application, the following solutions are optimal:

AWS Global Accelerator (Option A): Global Accelerator provides high availability and improves performance by using the AWS global network to route user traffic to the nearest healthy endpoint (across AWS Regions). By adding the Network Load Balancers as endpoints, Global Accelerator ensures that traffic is routed efficiently to the closest endpoint, improving both availability and performance.

Network Load Balancer (Option D): Thestateful TCP-based workloadhosted on Amazon EC2 instances and thestateless UDP-based workloadhosted on-premises are best served by Network Load Balancers (NLBs). NLBs are designed to handle TCP and UDP traffic with ultra-low latency and can route traffic to both EC2 and on-premises endpoints.

Option B (CloudFront and Route 53): CloudFront is better suited for HTTP/HTTPS workloads, not for TCP/UDP-based applications.

Option C (ALB): Application Load Balancers do not support the stateless UDP-based workload, making NLBs the better choice for both TCP and UDP.

AWS References:

AWS Global Accelerator

Network Load Balancer

For an application requiring TCP communication and high availability:

Network Load Balancer (NLB)is the best choice for load balancing TCP traffic because it is designed for handling high-throughput, low-latency connections.

Auto Scaling groupensures that the application can automatically scale based on demand, adding or removing EC2 instances as needed, which is crucial for handling user growth.

Option C (Application Load Balancer): ALB is primarily for HTTP/HTTPS traffic, not ideal for TCP.

Option D (Manual scaling): Manually adding instances does not provide the automation or scalability required.

Option E (Gateway Load Balancer): GLB is used for third-party virtual appliances, not for direct application load balancing.

AWS References:

Network Load Balancer

Auto Scaling Group

SSE-KMS: Server-side encryption with AWS Key Management Service (SSE-KMS) provides robust encryption of data at rest, integrated with AWS KMS for key management and auditing.

Automatic Key Rotation: By enabling automatic rotation for the KMS keys, the system ensures that keys are rotated annually without manual intervention, meeting compliance requirements.

Logging and Auditing: AWS KMS automatically logs all key usage and management actions in AWS CloudTrail, providing the necessary audit logs.

Implementation:

Create a KMS key with automatic rotation enabled.

Configure the S3 bucket to use SSE-KMS with the created KMS key.

Ensure CloudTrail is enabled for logging KMS key usage.

Operational Efficiency: This solution provides encryption, automatic key management, and auditing in a seamless, fully managed way, reducing operational overhead.

Aurora I/O-Optimized: This storage configuration is designed to provide consistent high performance for Aurora databases. It automatically scales IOPS as the workload increases, without needing to provision IOPS separately.

Cost-Effectiveness: With Aurora I/O-Optimized, you only pay for the storage and I/O you use, making it a cost-effective solution for applications with varying and unpredictable I/O demands.

Implementation:

During the creation of the Aurora PostgreSQL Serverless v2 cluster, select the I/O-Optimized storage configuration.

The storage system will automatically handle scaling and performance optimization based on the application load.

Operational Efficiency: This configuration reduces the need for manual tuning and ensures optimal performance without additional administrative overhead.

To improve the performance of the primary RDS PostgreSQL database during business hours and reduce the load, the best solution is to create aread replicain the same region (us-east-1). This will offload the read-heavy operations (like generating reports) to the replica, reducing the burden on the primary instance, which improves overall performance. Additionally, read replicas provide near real-time replication, making them ideal for real-time reporting use cases.

Option A (cross-Region read replica): This adds unnecessary latency for real-time reporting and increased costs due to cross-region data transfer.

Option B (Multi-AZ): Multi-AZ deployments are for high availability and disaster recovery but won’t offload the read traffic, as the standby database cannot serve read requests.

Option C (AWS DMS replication): This adds complexity and is not as cost-effective as using an RDS read replica for the same region.

AWS References:

Amazon RDS Read Replicas

Amazon RDS Performance Best Practices

CloudFront Signed URLs: These URLs allow you to provide limited access to content that is being served through an Amazon CloudFront distribution. Signed URLs can be generated to grant time-limited access to premium customers.

Content Restriction:

By using CloudFront signed URLs, you can control access to your media streams and file content stored in S3.

These URLs can be customized with an expiration time, ensuring that access is only available for a specific period, which is useful for scenarios like movie rentals or music downloads.

Security and Flexibility:

Signed URLs ensure that only authenticated users (premium customers) can access the restricted content.

This approach integrates seamlessly with CloudFront and S3, providing an efficient way to manage access controls without additional overhead.

Operational Efficiency: Using CloudFront signed URLs leverages AWS managed services to handle the complexity of access control, reducing the need for custom implementation and maintenance.

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.

Option Aallows importing your own encryption keys into AWS KMS, ensuring control over key material.

Option Duses S3 Glacier with SSE-C, where the customer controls the encryption keys, meeting compliance needs.

Option Buses AWS-managed key material, violating the requirement for key material control.

Option C and Eare not fully compliant with the control requirement.

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 programmatic access to its AWS usage costs for the current year and cost forecasts for the next 12 months, with minimal operational overhead.

Analysis of Options:

AWS Cost Explorer API: Provides programmatic access to detailed usage and cost data, including forecast costs. It supports pagination for handling large datasets, making it an efficient solution.

Downloadable AWS Cost Explorer report csv files: While useful, this method requires manual handling of files and does not provide real-time access.

AWS Budgets actions via FTP: This is less suitable as it involves setting up FTP transfers and does not provide the same level of detail and real-time access as the API.

AWS Budgets reports via SMTP: Similar to FTP, this method involves additional setup and lacks the real-time access and detail provided by the API.

Best Option for Minimal Operational Overhead:

AWS Cost Explorer API provides direct, programmatic access to cost data, including detailed usage and forecasting, with minimal setup and operational effort. It is the most efficient solution for integrating cost data into an operational cost dashboard.

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 development team needs to prevent the launch of large EC2 instances across multiple AWS accounts used for development, staging, and production environments.

Analysis of Options:

IAM Policies: Would need to be applied individually to each user in every account, leading to significant operational overhead.

AWS Resource Access Manager: Used for sharing resources, not for enforcing restrictions on resource creation.

IAM Role in Each Account: Requires creating and managing roles in each account, leading to higher operational overhead compared to using a centralized approach.

Service Control Policy (SCP) with AWS Organizations: Provides a centralized way to enforce policies across multiple AWS accounts, ensuring that large EC2 instances cannot be launched in any account.

Best Solution:

Service Control Policy (SCP) with AWS Organizations: This solution offers the least operational overhead by allowing centralized management and enforcement of policies across all accounts, effectively preventing the launch of large EC2 instances.