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135. Frage
A company wants to securely exchange data between its software as a service (SaaS) application Salesforce account and Amazon S3. The company must encrypt the data at rest by using AWS Key Management Service (AWS KMS) customer managed keys (CMKs). The company must also encrypt the data in transit. The company has enabled API access for the Salesforce account.
Which solution will meet these requirements with the LEAST development effort?
Antwort: D
Begründung:
Amazon AppFlow is a fully managed integration service that enables users to transfer data securely between SaaS applications and AWS services. It supports Salesforce as a source and Amazon S3 as a destination. It also supports encryption of data at rest using AWS KMS CMKs and encryption of data in transit using SSL
/TLS1. By using Amazon AppFlow, the solution can meet the requirements with the least development effort.
A: Create AWS Lambda functions to transfer the data securely from Salesforce to Amazon S3. This solution will not meet the requirement of the least development effort, as it involves writing custom code to interact with Salesforce and Amazon S3 APIs, handle authentication, encryption, error handling, and monitoring2.
B: Create an AWS Step Functions workflow Define the task to transfer the data securely from Salesforce to Amazon S3. This solution will not meet the requirement of the least development effort, as it involves creating a state machine definition to orchestrate the data transfer task, and invoking Lambda functions or other services to perform the actual data transfer3.
D: Create a custom connector for Salesforce to transfer the data securely from Salesforce to Ama-zon S3. This solution will not meet the requirement of the least development effort, as it involves using the Amazon AppFlow Custom Connector SDK to build and deploy a custom connector for Salesforce, which requires additional configuration and management.
Reference URL: https://aws.amazon.com/appflow/
136. Frage
A company uses Amazon Route 53 as its DNS provider. The company hosts a website both on premises and in the AWS Cloud. The company's on-premises data center is near the us-west-1 Region. The company hosts the website on AWS in the eu-central-1 Region.
The company wants to optimize load times for the website as much as possible.
Which solution will meet these requirements?
Antwort: D
Begründung:
Comprehensive and Detailed Explanation (paraphrased from AWS Solutions Architect guidance):
* Amazon Route 53 latency-based routing is specifically designed to route users to the endpoint that provides the lowest latency, based on actual latency measurements between AWS Regions and users' networks. This directly supports the goal of optimizing load times (performance).
* For non-AWS endpoints (like an on-premises data center), Route 53 lets you create a latency routing record and associate it with the AWS Region that is closest to that endpoint. In this case, the on- premises data center is near us-west-1, so you associate that latency record with the us-west-1 Region.
* Users for whom the eu-central-1 Region has lower latency will be routed to the AWS website in eu-central-1.
* Users for whom the us-west-1-associated endpoint has lower latency will be routed to the on- premises website.
* This matches AWS best practices for high-performance, low-latency architectures when you have multiple endpoints in different geographic locations, including a mix of AWS and on-premises resources.
Why the other options are not correct:
* Option A (Failover routing):
* Failover routing is designed for high availability and disaster recovery (active-passive), not for optimizing latency.
* All traffic goes to the primary endpoint (eu-central-1) unless it is unhealthy. That does not choose the lowest-latency endpoint for each user, so it does not meet the "optimize load times as much as possible" requirement.
* Option B (IP-based routing):
* IP-based / geo-based policies are about directing users based on location information (IP/geo), not measured latency.
* You would have to manually decide which IP ranges get which endpoint, which does not guarantee that each user goes to the lowest-latency endpoint. It's less precise and less dynamic than latency-based routing.
* Option D (Weighted routing):
* Weighted routing splits traffic according to fixed weights (e.g., 50/50), regardless of user location or latency.
* This is useful for testing, blue/green deployment, or gradual traffic shifting, but not for performance optimization per user.
Therefore, the only option that directly aligns with AWS guidance for performance optimization and latency- based traffic steering across Regions and on-premises endpoints is:
# C. Create a DNS record with a latency-based routing policy... associate the on-premises endpoint with us- west-1.
137. Frage
An ecommerce company is redesigning a product catalog system to handle millions of products and provide fast access to product information. The system needs to store structured product data such as product name, price, description, and category. The system also needs to store unstructured data such as high-resolution product videos and user manuals. The architecture must be highly available and must be able to handle sudden spikes in traffic during large-scale sales events.
Antwort: A
Begründung:
Amazon DynamoDB provides single-digit millisecond performance at any scale and is fully managed to handle millions of catalog records. It is ideal for structured catalog data such as product metadata and scales seamlessly during high-traffic events like sales. Amazon S3 is optimized for storing unstructured large objects such as videos and manuals, with virtually unlimited scalability and high durability. Option A (RDS) would not handle massive scale or traffic spikes as efficiently. Option C overloads DynamoDB by forcing it to store large binary data, which is not its purpose. Option D (DocumentDB) is suitable for JSON-like documents but not optimal for storing large media files and would add operational complexity. Therefore, option B represents the best separation of structured and unstructured data storage.
References:* DynamoDB Developer Guide - Millisecond performance at scale* Amazon S3 User Guide - Storage for unstructured data* AWS Well-Architected Framework - Performance Efficiency Pillar
138. Frage
A company is migrating applications to AWS. The applications are deployed in different accounts. The company manages the accounts centrally by using AWS Organizations. The company's security team needs a single sign-on (SSO) solution across all the company's accounts. The company must continue managing the users and groups in its on-premises self-managed Microsoft Active Directory.
Which solution will meet these requirements?
Antwort: D
Begründung:
To provide single sign-on (SSO) across all the company's accounts while continuing to manage users and groups in its on-premises self-managed Microsoft Active Directory, the solution is to enable AWS Single Sign-On (SSO) from the AWS SSO console and create a one-way forest trust or a one-way domain trust to connect the company's self-managed Microsoft Active Directory with AWS SSO by using AWS Directory Service for Microsoft Active Directory. This solution is described in the AWS documentation
139. Frage
A company wants to re-architect a large-scale web application to a serverless microservices architecture. The application uses Amazon EC2 instances and is written in Python.
The company selected one component of the web application to test as a microservice. The component supports hundreds of requests per second. The company wants to create and test the microservice on an AWS solution that supports Python. The solution must also scale automatically and require minimal infrastructure and minimal operational support.
Which solution will meet these requirements?
Antwort: A
Begründung:
D is the best match because AWS Lambda is a serverless compute service that runs code without provisioning or managing servers, which directly aligns with the requirement for minimal infrastructure and minimal operational support. Lambda supports Python runtimes, so the team can deploy the selected component as a microservice using the same language. For workloads with hundreds of requests per second, Lambda is designed to handle request-driven execution and automatically scales by running more concurrent instances of the function in response to incoming traffic, without the customer needing to pre-size or manage capacity.
140. Frage
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