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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q559-Q564):

NEW QUESTION # 559
A company collects air quality data from sensors. The company plans to use the MQTT protocol to send the data to AWS IoT Core. The company will process the data and then will store the data in an Amazon Aurora database.
During periods of low air quality, sensors will send data more frequently. The company must buffer the data during these periods to make sure that no data is lost before the data is processed and stored.
Which solution will meet these requirements?

Answer: D

Explanation:
Using an Amazon Kinesis data stream as a target for the IoT Core rule ensures durable and scalable buffering of data during traffic spikes.
An ECS Fargate application reads data from Kinesis, processes it, and stores it in Aurora, meeting the requirement for flexible, serverless data handling.
This solution guarantees no data loss while providing real-time or near-real-time data processing capabilities.


NEW QUESTION # 560
A company runs an application on AWS. The company curates data from several different sources. The company uses proprietary algorithms to perform data transformations and aggregations. After the company performs E TL processes, the company stores the results in Amazon Redshift tables. The company sells this data to other companies. The company downloads the data as files from the Amazon Redshift tables and transmits the files to several data customers by using FTP. The number of data customers has grown significantly. Management of the data customers has become difficult.
The company will use AWS Data Exchange to create a data product that the company can use to share data with customers. The company wants to confirm the identities of the customers before the company shares data.
The customers also need access to the most recent data when the company publishes the data.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: C

Explanation:
Explanation
The company should download the data from the Amazon Redshift tables to an Amazon S3 bucket periodically and use AWS Data Exchange for S3 to share data with customers. The company should configure subscription verification and require the data customers to subscribe to the data product. This solution will meet the requirements with the least operational overhead because AWS Data Exchange for S3 is a feature that enables data subscribers to access third-party data files directly from data providers' Amazon S3 buckets.
Subscribers can easily use these files for their data analysis with AWS services without needing to create or manage data copies. Data providers can easily set up AWS Data Exchange for S3 on top of their existing S3 buckets to share direct access to an entire S3 bucket or specific prefixes and S3 objects. AWS Data Exchange automatically manages subscriptions, entitlements, billing, and payment1.
The other options are not correct because:
Using AWS Data Exchange for APIs to share data with customers would not work because AWS Data Exchange for APIs is a feature that enables data subscribers to access third-party APIs directly from data providers' AWS accounts. Subscribers can easily use these APIs for their data analysis with AWS services without needing to manage API keys or tokens. Data providers can easily set up AWS Data Exchange for APIs on top of their existing API Gateway resources to share direct access to an entire API or specific routes and stages2. However, this feature is not suitable for sharing data from Amazon Redshift tables, which are not exposed as APIs.
Creating an Amazon API Gateway Data API service integration with Amazon Redshift would not work because the Data API is a feature that enables you to query your Amazon Redshift cluster using HTTP requests, without needing a persistent connection or a SQL client3. It is useful for building applications that interact with Amazon Redshift, but not for sharing data files with customers.
Creating an AWS Data Exchange datashare by connecting AWS Data Exchange to the Redshift cluster would not work because AWS Data Exchange does not support datashares for Amazon Redshift clusters. A datashare is a feature that enables you to share live and secure access to your Amazon Redshift data across your accounts or with third parties without copying or moving the underlying data4.
It is useful for sharing query results and views with other users, but not for sharing data files with customers.
Publishing the Amazon Redshift data to an Open Data on AWS Data Exchange would not work because Open Data on AWS Data Exchange is a feature that enables you to find and use free and public datasets from AWS customers and partners. It is useful for accessing open and free data, but not for confirming the identities of the customers or charging them for the data.
References:
https://aws.amazon.com/data-exchange/why-aws-data-exchange/s3/
https://aws.amazon.com/data-exchange/why-aws-data-exchange/api/
https://docs.aws.amazon.com/redshift/latest/mgmt/data-api.html
https://docs.aws.amazon.com/redshift/latest/dg/datashare-overview.html
https://aws.amazon.com/data-exchange/open-data/


NEW QUESTION # 561
A company deploys a new web application. As pari of the setup, the company configures AWS WAF to log to Amazon S3 through Amazon Kinesis Data Firehose. The company develops an Amazon Athena query that runs once daily to return AWS WAF log data from the previous 24 hours. The volume of daily logs is constant. However, over time, the same query is taking more time to run.
A solutions architect needs to design a solution to prevent the query time from continuing to increase. The solution must minimize operational overhead.
Which solution will meet these requirements?

Answer: C

Explanation:
Explanation
The best solution is to modify the Kinesis Data Firehose configuration and Athena table definition to partition the data by date and time. This will reduce the amount of data scanned by Athena and improve the query performance. Changing the Athena query to view the relevant partitions will also help to filter out unnecessary data. This solution requires minimal operational overhead as it does not involve creating additional resources or changing the log format. References: [AWS WAF Developer Guide], [Amazon Kinesis Data Firehose User Guide], [Amazon Athena User Guide]


NEW QUESTION # 562
A global media company is planning a multi-Region deployment of an application. Amazon DynamoDB global tables will back the deployment to keep the user experience consistent across the two continents where users are concentrated. Each deployment will have a public Application Load Balancer (ALB). The company manages public DNS internally. The company wants to make the application available through an apex domain.
Which solution will meet these requirements with the LEAST effort?

Answer: D

Explanation:
AWS Global Accelerator is a service that directs traffic to optimal endpoints (in this case, the Application Load Balancer) based on the health of the endpoints and network routing. It allows you to create an accelerator that directs traffic to multiple endpoint groups, one for each Region where the application is deployed. The accelerator uses the AWS global network to optimize the traffic routing to the healthy endpoint.
By using Global Accelerator, the company can use a single static IP address for the apex domain, and traffic will be directed to the optimal endpoint based on the user's location, without the need for additional load balancers or routing policies.
Reference:
AWS Global Accelerator documentation: https://aws.amazon.com/global-accelerator/ Routing User Traffic to the Optimal AWS Region using Global Accelerator documentation: https://aws.amazon.com/blogs/networking-and-content-delivery/routing-user-traffic-to-the-optimal-aws-region-using-global-accelerator/


NEW QUESTION # 563
A company is planning a large event where a promotional offer will be introduced The company's website is hosted on AWS and backed by an Amazon RDS for PostgreSQL DB instance The website explains the promotion and includes a sign-up page that collects user information and preferences Management expects large and unpredictable volumes of traffic periodically which will create many database writes A solutions architect needs to build a solution that does not change the underlying data model and ensures that submissions are not dropped before they are committed to the database Which solutions meets these requirements'?

Answer: C


NEW QUESTION # 564
......

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