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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design Resilient Architectures | 26% | - Design highly available and/or fault-tolerant architectures
|
| Topic 2: Design Cost-Optimized Architectures | 20% | - Design cost-optimized database solutions
|
| Topic 3: Design Secure Architectures | 30% | - Determine appropriate data security controls
|
| Topic 4: Design High-Performing Architectures | 24% | - Determine high-performing database solutions
|
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NEW QUESTION # 884
A company has an application that provides marketing services to stores. The services are based on previous purchases by store customers. The stores upload transaction data to the company through SFTP, and the data is processed and analyzed to generate new marketing offers. Some of the files can exceed 200 GB in size.
Recently, the company discovered that some of the stores have uploaded files that contain personally identifiable information (PII) that should not have been included. The company wants administrators to be alerted if PII is shared again. The company also wants to automate remediation.
What should a solutions architect do to meet these requirements with the LEAST development effort?
Answer: D
Explanation:
To meet the requirements of detecting and alerting the administrators when PII is shared and automating remediation with the least development effort, the best approach would be to use Amazon S3 bucket as a secure transfer point and scan the objects in the bucket with Amazon Macie. Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect sensitive data stored in Amazon S3. It can be used to classify sensitive data, monitor access to sensitive data, and automate remediation actions.
In this scenario, after uploading the files to the Amazon S3 bucket, the objects can be scanned for PII by Amazon Macie, and if it detects any PII, it can trigger an Amazon Simple Notification Service (SNS) notification to alert the administrators to remove the objects containing PII. This approach requires the least development effort, as Amazon Macie already has pre-built data classification rules that can detect PII in various formats.
Hence, option B is the correct answer.
References:
* Amazon Macie User Guide: https://docs.aws.amazon.com/macie/latest/userguide/what-is-macie.html
* AWS Well-Architected Framework - Security Pillar:
https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html
NEW QUESTION # 885
A company runs a self-managed Microsoft SQL Server on Amazon EC2 instances and Amazon Elastic Block Store (Amazon EBS). Daily snapshots are taken of the EBS volumes. Recently, all the company's EBS snapshots were accidentally deleted while running a snapshot cleaning script that deletes all expired EBS snapshots. A solutions architect needs to update the architecture to prevent data loss without retaining EBS snapshots indefinitely. Which solution will meet these requirements with the LEAST development effort?
Answer: C
Explanation:
https://aws.amazon.com/blogs/aws/new-recycle-bin-for-ebs-snapshots/
NEW QUESTION # 886
An investment bank has a distributed batch processing application which is hosted in an Auto Scaling group of Spot EC2 instances with an SQS queue. You configured your components to use client- side buffering so that the calls made from the client will be buffered first and then sent as a batch request to SQS.
What is a period of time during which the SQS queue prevents other consuming components from receiving and processing a message?
Answer: A
Explanation:
The visibility timeout is a period of time during which Amazon SQS prevents other consuming components from receiving and processing a message.
When a consumer receives and processes a message from a queue, the message remains in the queue. Amazon SQS doesn't automatically delete the message. Because Amazon SQS is a distributed system, there's no guarantee that the consumer actually receives the message (for example, due to a connectivity issue, or due to an issue in the consumer application). Thus, the consumer must delete the message from the queue after receiving and processing it.
Immediately after the message is received, it remains in the queue. To prevent other consumers from processing the message again, Amazon SQS sets a visibility timeout, a period of time during which Amazon SQS prevents other consumers from receiving and processing the message. The default visibility timeout for a message is 30 seconds. The maximum is 12 hours. References:
https://aws.amazon.com/sqs/faqs/
https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-visibility-timeou t.html Check out this Amazon SQS Cheat Sheet:
https://tutorialsdojo.com/amazon-sqs/
NEW QUESTION # 887
A company stores confidential data in an Amazon Aurora PostgreSQL database in the ap-southeast-3 Region The database is encrypted with an AWS Key Management Service (AWS KMS) customer managed key The company was recently acquired and must securely share a backup of the database with the acquiring company's AWS account in ap-southeast-3.
What should a solutions architect do to meet these requirements?
Answer: A
NEW QUESTION # 888
A popular augmented reality (AR) mobile game is heavily using a RESTful API which is hosted in AWS. The API uses Amazon API Gateway and a DynamoDB table with a preconfigured read and write capacity. Based on your systems monitoring, the DynamoDB table begins to throttle requests during high peak loads which causes the slow performance of the game.
Which of the following can you do to improve the performance of your app?
Answer: A
Explanation:
DynamoDB auto scaling uses the AWS Application Auto Scaling service to dynamically adjust provisioned throughput capacity on your behalf, in response to actual traffic patterns. This enables a table or a global secondary index to increase its provisioned read and write capacity to handle sudden increases in traffic, without throttling. When the workload decreases, Application Auto Scaling decreases the throughput so that you don't pay for unused provisioned capacity.
Using DynamoDB Auto Scaling is the best answer. DynamoDB Auto Scaling uses the AWS Application Auto Scaling service to dynamically adjust provisioned throughput capacity on your behalf.
Integrating an Application Load Balancer with your DynamoDB table is incorrect because an Application Load Balancer is not suitable to be used with DynamoDB and in addition, this will not increase the throughput of your DynamoDB table.
Adding the DynamoDB table to an Auto Scaling Group is incorrect because you usually put EC2 instances on an Auto Scaling Group, and not a DynamoDB table.
Creating an SQS queue in front of the DynamoDB table is incorrect because this is not a design principle for high throughput DynamoDB table. Using SQS is for handling queuing and polling the request. This will not increase the throughput of DynamoDB which is required in this situation.
Reference:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/AutoScaling.html Check out this Amazon DynamoDB Cheat Sheet: https://tutorialsdojo.com/amazon-dynamodb/ Amazon DynamoDB Overview:
https://www.youtube.com/watch?v=3ZOyUNIeorU
NEW QUESTION # 889
......
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