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| Section | Weight | Objectives |
|---|
| Design Secure Architectures | 30% | - Design for security and threat detection
- 1. Monitoring and logging services
- 2. Incident response and security automation
- Design secure workloads and applications
- 1. Compliance and governance controls
- 2. Network security (VPC, security groups, NACLs)
- 3. Data protection and encryption (at rest/in transit)
- Design secure access to AWS resources
- 1. Security best practices and least privilege
- 2. Multi-account access and control
- 3. Shared responsibility model
- 4. Identity and access management (IAM, IAM Identity Center)
|
| Design Resilient Architectures | 26% | - Design highly available and fault-tolerant architectures
- 1. Replication and disaster recovery strategies
- 2. Load balancing and auto scaling
- 3. Regions, Availability Zones, and edge locations
- Design decoupled and loosely coupled systems
- 1. Event-driven architectures
- 2. Messaging and queue services
- 3. Serverless and managed service integration
- Design for reliability and recovery
- 1. Backup and restore mechanisms
- 2. Failover and failback processes
|
| Design High-Performing Architectures | 24% | - Design high-performance storage solutions
- 1. Caching and content delivery
- 2. Storage performance and durability
- 3. Storage types (object, block, file)
- Design high-performance networking solutions
- 1. Global acceleration and routing
- 2. Network architecture and connectivity
- 3. Latency reduction and throughput optimization
- Design high-performance compute solutions
- 1. Scaling and performance optimization
- 2. Instance types and sizing
- 3. Compute options (EC2, Lambda, ECS, EKS)
|
| Design Cost-Optimized Architectures | 20% | - Identify cost-effective storage solutions
- 1. Data retention and archiving
- 2. Storage classes and lifecycle policies
- Control and monitor costs
- 1. Resource tagging and allocation
- 2. Cost management tools and alerts
- Design cost-effective compute and network solutions
- 1. Right-sizing and reserved instances
- 2. Serverless and pay-as-you-go models
- 3. Data transfer cost optimization
|
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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q72-Q77):
NEW QUESTION # 72
A solutions architect wants to use the following JSON text as an identity-based policy to grant specific permissions:

Which IAM principals can the solutions architect attach this policy to? (Select TWO.)
- A. Amazon Elastic Container Service (Amazon ECS) resource
- B. Amazon EC2 resource
- C. Group
- D. Role
- E. Organization
Answer: C,D
Explanation:
This JSON text is an identity-based policy that grants specific permissions. The IAM principals that the solutions architect can attach this policy to are Role and Group. This is because the policy is written in JSON and is an identity-based policy, which can be attached to IAM principals such as users, groups, and roles. Identity-based policies are permissions policies that you attach to IAM identities (users, groups, or roles) and explicitly state what that identity is allowed (or denied) to do1. Identity-based policies are different from resource-based policies, which define the permissions around the specific resource1. Resource-based policies are attached to a resource, such as an Amazon S3 bucket or anAmazon EC2 instance1. Resource- based policies can also specify a principal, which is the entity that is allowed or denied access to the resource1. Organization is not an IAM principal, but a feature of AWS Organizations that allows you to manage multiple AWSaccountscentrally2. Amazon ECS resource and Amazon EC2 resource are not IAM principals, but AWS resources that can have resource-based policies attached to them34.
References:
Identity-based policies and resource-based policies
AWS Organizations
Amazon ECS task role
Amazon EC2 instance profile
NEW QUESTION # 73
[Design Secure Architectures]
A company is migrating a large amount of data from on-premises storage to AWS. Windows, Mac, and Linux based Amazon EC2 instances in the same AWS Region will access the data by using SMB and NFS storage protocols. The company will access a portion of the data routinely. The company will access the remaining data infrequently.
The company needs to design a solution to host the data.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Create an Amazon FSx for ONTAP instance. Create an FSx for ONTAP file system with a root volume that uses the auto tiering policy. Migrate the data to the FSx for ONTAP volume.
- B. Create an Amazon FSx for OpenZFS file system. Migrate the data to the new volume.
- C. Create an Amazon S3 bucket that uses S3 Intelligent-Tiering. Migrate the data to the S3 bucket by using an AWS Storage Gateway Amazon S3 File Gateway.
- D. Create an Amazon Elastic File System (Amazon EFS) volume that uses EFS Intelligent-Tiering. Use AWS DataSync to migrate the data to the EFS volume.
Answer: A
Explanation:
Amazon FSx for ONTAP supports both NFS and SMB protocols and includes automated tiering between SSD and capacity pool storage, optimizing cost and performance. It is ideal for mixed operating systems and varied access patterns with minimal administrative overhead.
NEW QUESTION # 74
A company is designing a microservice-based architecture tor a new application on AWS. Each microservice will run on its own set of Amazon EC2 instances. Each microservice will need to interact with multiple AWS services such as Amazon S3 and Amazon Simple Queue Service (Amazon SQS).
The company wants to manage permissions for each EC2 instance based on the principle of least privilege.
Which solution will meet this requirement?
- A. Create individual IAM roles based on the specific needs of each microservice. Associate the IAM roles with the appropriate EC2 instances.
- B. Assign an IAM user to each micro-service. Use access keys stored within the application code to authenticate AWS service requests.
- C. Use AWS Organizations to create a separate account for each microservice. Manage permissions at the account level.
- D. Create a single IAM role that has permission to access all AWS services. Associate the IAM role with all EC2 instances that run the microservices
Answer: A
Explanation:
When designing a microservice architecture where each microservice interacts with different AWS services, it's essential to follow the principle of least privilege. This means granting each microservice only the permissions it needs to perform its tasks, reducing the risk of unauthorized access or accidental actions.
The recommended approach is to create individualIAM roleswith policies that grant each microservice the specific permissions it requires. Then, these roles should be associated with the EC2 instances that run the corresponding microservice. By doing so, each EC2 instance will assume its specific IAM role, and permissions will be automatically managed by AWS.
IAM roles provide temporary credentials via the instance metadata service, eliminating the need to hard-code credentials in your application code, which enhances security.
AWS References:
IAM Roles for Amazon EC2explains how EC2 instances can use IAM roles to securely access AWS services without managing long-term credentials.
Best Practices for IAMincludes recommendations for implementing the least privilege principle and using IAM roles effectively.
Why the other options are incorrect:
A:Assign an IAM user to each microservice: This requires managing long-term credentials (access keys), which should be avoided. Storing keys in application code is insecure and creates a maintenance burden.
B:Create a single IAM role: This violates the principle of least privilege, as a single role with broad permissions across all services is less secure.
C:Use AWS Organizations: This approach adds unnecessary complexity. Managing permissions at the account level for each microservice is excessive for this use case and doesn't adhere to the principle of least privilege.
NEW QUESTION # 75
A large media company hosts a web application on AWS. The company wants to start caching confidential media files so that users around the world will have reliable access to the files. The content is stored in Amazon S3 buckets. The company must deliver the content quickly, regardless of where the requests originate geographically.
Which solution will meet these requirements?
- A. Use AWS DataSync to connect the S3 buckets to the web application.
- B. Deploy Amazon CloudFront to connect the S3 buckets to CloudFront edge servers.
- C. Use Amazon Simple Queue Service (Amazon SQS) to connect the S3 buckets to the web application.
- D. Deploy AWS Global Accelerator to connect the S3 buckets to the web application.
Answer: B
Explanation:
CloudFront uses a local cache to provide the response, AWS Global accelerator proxies requests and connects to the application all the time for the response.
https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/private-content-restricting-access-to-s3.html#private-content-granting-permissions-to-oai
NEW QUESTION # 76
A company is using microservices to build an ecommerce application on AWS. The company wants to preserve customer transaction information after customers submit orders. The company wants to store transaction data in an Amazon Aurora database. The company expects sales volumes to vary throughout each year.
- A. Use an Amazon API Gateway REST API to invoke an AWS Lambda function to send transaction data to the Aurora database. Send transaction data to an Amazon Simple Queue Service (Amazon SQS) queue that has a dead-letter queue. Use a second Lambda function to read from the SQS queue and to update the Aurora database.
- B. Use an Application Load Balancer (ALB) to route transaction data to Amazon Elastic Kubernetes Service (Amazon EKS). Use Amazon EKS to send the data to the Aurora database.
- C. Use an Amazon API Gateway HTTP API to send transaction data to an Application Load Balancer (ALB). Use the ALB to send the transaction data to Amazon Elastic Container Service (Amazon ECS) on Amazon EC2. Use ECS tasks to store the data in Aurora database.
- D. Use Amazon Data Firehose to send transaction data to Amazon S3. Use AWS Database Migration Service (AWS DMS) to migrate the data from Amazon S3 to the Aurora database.
Answer: A
Explanation:
Analysis:
The solution must handle variable sales volumes, preserve transaction information, and store data in an Amazon Aurora database with minimal operational overhead. Using API Gateway, AWS Lambda, and SQS is the best option because it provides scalability, reliability, and resilience.
Why Option A is Correct:
* API Gateway: Serves as an entry point for transaction data in a serverless, scalable manner.
* AWS Lambda: Processes the transactions and sends them to Amazon SQS for queuing.
* Amazon SQS: Buffers the transaction data, ensuring durability and resilience against spikes in transaction volume.
* Second Lambda Function: Processes messages from the SQS queue and updates the Aurora database, decoupling the workflow for better scalability.
* Dead-Letter Queue (DLQ): Ensures failed transactions are logged for later debugging or reprocessing.
Why Other Options Are Not Ideal:
* Option B:
* Using an ALB with ECS on EC2 introduces operational overhead, such as managing EC2 instances and scaling ECS tasks.Not cost-effective.
* Option C:
* EKS is highly operationally intensive and requires Kubernetes cluster management, which is unnecessary for this use case.Too complex.
* Option D:
* Amazon Data Firehose and DMS are not designed for real-time transactional workflows. They are better suited for data analytics pipelines.Not suitable.
AWS References:
* Amazon API Gateway:AWS Documentation - API Gateway
* AWS Lambda:AWS Documentation - Lambda
* Amazon SQS:AWS Documentation - SQS
* Amazon Aurora:AWS Documentation - Aurora
NEW QUESTION # 77
......
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