Topic 1: Exam Pool A
An application allows users at a company's headquarters to access product data. The product data is stored in an Amazon RDS MySQL DB instance. The operations team has isolated an application performance slowdown and wants to separate read traffic from write traffic. A solutions architect needs to optimize the application's performance quickly.
What should the solutions architect recommend?
A. Change the existing database to a Multi-AZ deployment. Serve the read requests from the primary Availability Zone.
B. Change the existing database to a Multi-AZ deployment. Serve the read requests from the secondary Availability Zone.
C. Create read replicas for the database. Configure the read replicas with half of the compute and storage resources as the source database.
D. Create read replicas for the database. Configure the read replicas with the same compute and storage resources as the source database.
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?
A. Use an Amazon S3 bucket as a secure transfer point. Use Amazon Inspector to scan me objects in the bucket. If objects contain Pll. trigger an S3 Lifecycle policy to remove the objects that contain Pll.
B. Use an Amazon S3 bucket as a secure transfer point. Use Amazon Macie to scan the objects in the bucket. If objects contain Pll. Use Amazon Simple Notification Service (Amazon SNS) to trigger a notification to the administrators to remove the objects mat contain Pll.
C. Implement custom scanning algorithms in an AWS Lambda function. Trigger the function when objects are loaded into the bucket. It objects contain Rll. use Amazon Simple Notification Service (Amazon SNS) to trigger a notification to the administrators to remove the objects that contain Pll.
D. Implement custom scanning algorithms in an AWS Lambda function. Trigger the function when objects are loaded into the bucket. If objects contain Pll. use Amazon Simple Email Service (Amazon STS) to trigger a notification to the administrators and trigger on S3 Lifecycle policy to remove the objects mot contain PII.
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.
A company hosts its multi-tier applications on AWS. For compliance, governance, auditing, and security, the company must track configuration changes on its AWS resources and record a history of API calls made to these resources.
What should a solutions architect do to meet these requirements?
A. Use AWS CloudTrail to track configuration changes and AWS Config to record API calls
B. Use AWS Config to track configuration changes and AWS CloudTrail to record API calls
C. Use AWS Config to track configuration changes and Amazon CloudWatch to record API calls
D. Use AWS CloudTrail to track configuration changes and Amazon CloudWatch to record API calls
Explanation: AWS Config is a fully managed service that allows the company to assess, audit, and evaluate the configurations of its AWS resources. It provides a detailed inventory of the resources in use and tracks changes to resource configurations. AWS Config can detect configuration changes and alert the company when changes occur. It also provides a historical view of changes, which is essential for compliance and governance purposes. AWS CloudTrail is a fully managed service that provides a detailed history of API calls made to the company's AWS resources. It records all API activity in the AWS account, including who made the API call, when the call was made, and what resources were affected by the call. This information is critical for security and auditing purposes, as it allows the company to investigate any suspicious activity that might occur on its AWS resources.
A company is subscribed to the AWS Business Support plan. Compliance rules require the company to check on AWS infrastructure health before deployments can proceed. The company needs a programmatic and automated way to check on infrastructure health at the beginning of new deployments. Which solution will meet these requirements?
A. Use the AWS Trusted Advisor API at the start of each deployment. Pause all new deployments if the API returns any issues.
B. Use the AWS Health API at the start of each deployment. Pause all new deployments if the API returns any issues.
C. Query the AWS Support API at the start of each deployment. Pause all new deployments if the API returns any open issues.
D. Send an API call to each workload ahead of deployment. Pause the deployments if the API call fails.
Explanation: The AWS Health API provides programmatic access to the AWS Health information that is presented in the AWS Personal Health Dashboard. You can use the API operations to get information about AWS Health events that affect your AWS services and resources. You can also use the API to enable or disable health-based insights for your organization. You can use the AWS Health API at the start of each deployment to check on AWS infrastructure health and pause all new deployments if the API returns any issues.
A solutions architect is designing a highly available Amazon ElastiCache for Redis based solution. The solutions architect needs to ensure that failures do not result in performance degradation or loss of data locally and within an AWS Region. The solution needs to provide high availability at the node level and at the Region level. Which solution will meet these requirements?
A. Use Multi-AZ Redis replication groups with shards that contain multiple nodes.
B. Use Redis shards that contain multiple nodes with Redis append only files (AOF) tured on.
C. Use a Multi-AZ Redis cluster with more than one read replica in the replication group.
D. Use Redis shards that contain multiple nodes with Auto Scaling turned on.
Explanation: This answer is correct because it provides high availability at the node level and at the Region level for the ElastiCache for Redis solution. A Multi-AZ Redis replication group consists of a primary cluster and up to five read replica clusters, each in a different Availability Zone. If the primary cluster fails, one of the read replicas is automatically promoted to be the new primary cluster. A Redis replication group with shards enables partitioning of the data across multiple nodes, which increases the scalability and performance of the solution. Each shard can have one or more replicas to provide redundancy and read scaling.
A company runs an online marketplace web application on AWS. The application serves hundreds of thousands of users during peak hours. The company needs a scalable, near- real-time solution to share the details of millions of financial transactions with several other internal applications Transactions also need to be processed to remove sensitive data before being stored in a document database for low-latency retrieval.
What should a solutions architect recommend to meet these requirements?
A. Store the transactions data into Amazon DynamoDB Set up a rule in DynamoDB to remove sensitive data from every transaction upon write Use DynamoDB Streams to share the transactions data with other applications
B. Stream the transactions data into Amazon Kinesis Data Firehose to store data in Amazon DynamoDB and Amazon S3 Use AWS Lambda integration with Kinesis Data Firehose to remove sensitive data. Other applications can consume the data stored in Amazon S3
C. Stream the transactions data into Amazon Kinesis Data Streams Use AWS Lambda integration to remove sensitive data from every transaction and then store the transactions data in Amazon DynamoDB Other applications can consume the transactions data off the Kinesis data stream.
D. Store the batched transactions data in Amazon S3 as files. Use AWS Lambda to process every file and remove sensitive data before updating the files in Amazon S3 The Lambda function then stores the data in Amazon DynamoDB Other applications can consume transaction files stored in Amazon S3.
Explanation: The destination of your Kinesis Data Firehose delivery stream. Kinesis Data Firehose can send data records to various destinations, including Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon OpenSearch Service, and any HTTP endpoint that is owned by you or any of your third-party service providers. The following are the supported destinations:
* Amazon OpenSearch Service
* Amazon S3
* Datadog
* Dynatrace
* Honeycomb
* HTTP Endpoint
* Logic Monitor
* MongoDB Cloud
* New Relic
* Splunk
* Sumo Logic
Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events.
A company uses Amazon Elastic Kubernetes Service (Amazon EKS) to run a container application. The EKS cluster stores sensitive information in the Kubernetes secrets object. The company wants to ensure that the information is encrypted. Which solution will meet these requirements with the LEAST operational overhead?
A. Use the container application to encrypt the information by using AWS Key Management Service (AWS KMS).
B. Enable secrets encryption in the EKS cluster by using AWS Key Management Service (AWS KMS)_
C. Implement an AWS Lambda tuncüon to encrypt the information by using AWS Key Management Service (AWS KMS).
D. Use AWS Systems Manager Parameter Store to encrypt the information by using AWS Key Management Service (AWS KMS).
Explanation: it allows the company to encrypt the Kubernetes secrets object in the EKS cluster with the least operational overhead. By enabling secrets encryption in the EKS cluster, the company can use AWS Key Management Service (AWS KMS) to generate and manage encryption keys for encrypting and decrypting secrets at rest. This is a simple and secure way to protect sensitive information in EKS clusters.
A company's application integrates with multiple software-as-a-service (SaaS) sources for data collection. The company runs Amazon EC2 instances to receive the data and to upload the data to an Amazon S3 bucket for analysis. The same EC2 instance that receives and uploads the data also sends a notification to the user when an upload is complete. The company has noticed slow application performance and wants to improve the performance as much as possible.
Which solution will meet these requirements with the LEAST operational overhead?
A. Create an Auto Scaling group so that EC2 instances can scale out. Configure an S3 event notification to send events to an Amazon Simple Notification Service (Amazon SNS) topic when the upload to the S3 bucket is complete.
B. Create an Amazon AppFlow flow to transfer data between each SaaS source and the S3 bucket. Configure an S3 event notification to send events to an Amazon Simple Notification Service (Amazon SNS) topic when the upload to the S3 bucket is complete.
C. Create an Amazon EventBridge (Amazon CloudWatch Events) rule for each SaaS source to send output data. Configure the S3 bucket as the rule's target. Create a second EventBridge (CloudWatch Events) rule to send events when the upload to the S3 bucket is complete. Configure an Amazon Simple Notification Service (Amazon SNS) topic as the second rule's target.
D. Create a Docker container to use instead of an EC2 instance. Host the containerized application on Amazon Elastic Container Service (Amazon ECS). Configure Amazon CloudWatch Container Insights to send events to an Amazon Simple Notification Service (Amazon SNS) topic when the upload to the S3 bucket is complete.
Explanation: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, SAP, Zendesk, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks.
A company has resources across multiple AWS Regions and accounts. A newly hired solutions architect discovers a previous employee did not provide details about the resources invent^. The solutions architect needs to build and map the relationship details of the various workloads across all accounts. Which solution will meet these requirements in the MOST operationally efficient way?
A. Use AWS Systems Manager Inventory to generate a map view from the detailed view report.
B. Use AWS Step Functions to collect workload details Build architecture diagrams of the workloads manually.
C. Use Workload Discovery on AWS to generate architecture diagrams of the workloads.
D. Use AWS X-Ray to view the workload details Build architecture diagrams with relationships
Explanation: Workload Discovery on AWS (formerly called AWS Perspective) is a tool that visualizes AWS Cloud workloads. It maintains an inventory of the AWS resources across your accounts and Regions, mapping relationships between them, and displaying them in a web UI. It also allows you to query AWS Cost and Usage Reports, search for resources, save and export architecture diagrams, and more1. By using Workload Discovery on AWS, the solution can build and map the relationship details of the various workloads across all accounts with the least operational effort. Use AWS Systems Manager Inventory to generate a map view from the detailed view report. This solution will not meet the requirement of building and mapping the relationship details of the various workloads across all accounts, as AWS Systems Manager Inventory is a feature that collects metadata from your managed instances and stores it in a central Amazon S3 bucket. It does not provide a map view or architecture diagrams of the workloads2. Use AWS Step Functions to collect workload details Build architecture diagrams of the work-loads manually. This solution will not meet the requirement of the least operational effort, as it involves creating and managing state machines to orchestrate the workload details collection, and building architecture diagrams manually. Use AWS X-Ray to view the workload details Build architecture diagrams with relationships. This solution will not meet the requirement of the least operational effort, as it involves instrumenting your applications with X-Ray SDKs to collect workload details, and building architecture diagrams manually.
A social media company allows users to upload images to its website. The website runs on Amazon EC2 instances. During upload requests, the website resizes the images to a standard size and stores the resized images in Amazon S3. Users are experiencing slow upload requests to the website.
The company needs to reduce coupling within the application and improve website performance. A solutions architect must design the most operationally efficient process for image uploads.
Which combination of actions should the solutions architect take to meet these requirements? (Choose two.)
A. Configure the application to upload images to S3 Glacier.
B. Configure the web server to upload the original images to Amazon S3.
C. Configure the application to upload images directly from each user's browser to Amazon S3 through the use of a presigned URL.
D. Configure S3 Event Notifications to invoke an AWS Lambda function when an image is uploaded. Use the function to resize the image
E. Create an Amazon EventBridge (Amazon CloudWatch Events) rule that invokes an AWS Lambda function on a schedule to resize uploaded images.
Explanation: Amazon S3 is a highly scalable and durable object storage service that can store and retrieve any amount of data from anywhere on the web1. Users can configure the application to upload images directly from each user’s browser to Amazon S3 through the use of a presigned URL. A presigned URL is a URL that gives access to an object in an S3 bucket for a limited time and with a specific action, such as uploading an object2. Users can generate a presigned URL programmatically using the AWS SDKs or AWS CLI. By using a presigned URL, users can reduce coupling within the application and improve website performance, as they do not need to send the images to the web server first.
AWS Lambda is a serverless compute service that runs code in response to events and automatically manages the underlying compute resources3. Users can configure S3 Event Notifications to invoke an AWS Lambda function when an image is uploaded. S3 Event Notifications is a feature that allows users to receive notifications when certain events happen in an S3 bucket, such as object creation or deletion. Users can configure S3 Event Notifications to invoke a Lambda function that resizes the image and stores it back in the same or a different S3 bucket. This way, users can offload the image resizing task from the web server to Lambda.
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