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SAA-C03 Practice Test


Page 7 out of 193 Pages

Topic 1: Exam Pool A

A development team needs to host a website that will be accessed by other teams. The website contents consist of HTML, CSS, client-side JavaScript, and images Which method is the MOST cost-effective for hosting the website?


A. Containerize the website and host it in AWS Fargate.


B. Create an Amazon S3 bucket and host the website there


C. Deploy a web server on an Amazon EC2 instance to host the website.


D. Configure an Application Loa d Balancer with an AWS Lambda target that uses the Express js framework.





B.
  Create an Amazon S3 bucket and host the website there

Explanation:In Static Websites, Web pages are returned by the server which are prebuilt. They use simple languages such as HTML, CSS, or JavaScript.
There is no processing of content on the server (according to the user) in Static Websites. Web pages are returned by the server with no change therefore, static Websites are fast.
There is no interaction with databases.
Also, they are less costly as the host does not need to support server-side processing with different languages.
============
In Dynamic Websites, Web pages are returned by the server which are processed during runtime means they are not prebuilt web pages but they are built during runtime according to the user’s demand.
These use server-side scripting languages such as PHP, Node.js, ASP.NET and many more supported by the server.
So, they are slower than static websites but updates and interaction with databases are possible.

A company is preparing a new data platform that will ingest real-time streaming data from multiple sources. The company needs to transform the data before writing the data to Amazon S3. The company needs the ability to use SQL to query the transformed data. Which solutions will meet these requirements? (Choose two.)


A. Use Amazon Kinesis Data Streams to stream the data. Use Amazon Kinesis Data Analytics to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.


B. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use AWS Glue to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.


C. Use AWS Database Migration Service (AWS DMS) to ingest the data. Use Amazon EMR to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.


D. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use Amazon Kinesis Data Analytics to transform the data and to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.


E. Use Amazon Kinesis Data Streams to stream the data. Use AWS Glue to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.





A.
  Use Amazon Kinesis Data Streams to stream the data. Use Amazon Kinesis Data Analytics to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.

B.
  Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use AWS Glue to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.

Explanation: To ingest, transform, and query real-time streaming data from multiple sources, Amazon Kinesis and Amazon MSK are suitable solutions. Amazon Kinesis Data Streams can stream the data from various sources and integrate with other AWS services. Amazon Kinesis Data Analytics can transform the data using SQL or Apache Flink. Amazon Kinesis Data Firehose can write the data to Amazon S3 or other destinations. Amazon Athena can query the transformed data from Amazon S3 using standard SQL. Amazon MSK can stream the data using Apache Kafka, which is a popular open-source platform for streaming data. AWS Glue can transform the data using Apache Spark or Python scripts and write the data to Amazon S3 or other destinations. Amazon Athena can also query the transformed data from Amazon S3 using standard SQL.

A company stores call transcript files on a monthly basis. Users access the files randomly within 1 year of the call, but users access the files infrequently after 1 year. The company wants to optimize its solution by giving users the ability to query and retrieve files that are less than 1-year-old as quickly as possible. A delay in retrieving older files is acceptable. Which solution will meet these requirements MOST cost-effectively?


A. Store individual files with tags in Amazon S3 Glacier Instant Retrieval. Query the tags to retrieve the files from S3 Glacier Instant Retrieval.


B. Store individual files in Amazon S3 Intelligent-Tiering. Use S3 Lifecycle policies to move the files to S3 Glacier Flexible Retrieval after 1 year. Query and retrieve the files that are in Amazon S3 by using Amazon Athena. Query and retrieve the files that are in S3 Glacier by using S3 Glacier Select.


C. Store individual files with tags in Amazon S3 Standard storage. Store search metadata for each archive in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Instant Retrieval after 1 year. Query and retrieve the files by searching for metadata from Amazon S3.


D. Store individual files in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Deep Archive after 1 year. Store search metadata in Amazon RDS. Query the files from Amazon RDS. Retrieve the files from S3 Glacier Deep Archive.





B.
  Store individual files in Amazon S3 Intelligent-Tiering. Use S3 Lifecycle policies to move the files to S3 Glacier Flexible Retrieval after 1 year. Query and retrieve the files that are in Amazon S3 by using Amazon Athena. Query and retrieve the files that are in S3 Glacier by using S3 Glacier Select.

Explanation: "For archive data that needs immediate access, such as medical images, news media assets, or genomics data, choose the S3 Glacier Instant Retrieval storage class, an archive storage class that delivers the lowest cost storage with milliseconds retrieval. For archive data that does not require immediate access but needs the flexibility to retrieve large sets of data at no cost, such as backup or disaster recovery use cases, choose S3 Glacier Flexible Retrieval (formerly S3 Glacier), with retrieval in minutes or free bulk retrievals in 5- 12 hours.

A company is moving its on-premises Oracle database to Amazon Aurora PostgreSQL. The database has several applications that write to the same tables. The applications need to be migrated one by one with a month in between each migration. Management has expressed concerns that the database has a high number of reads and writes. The data must be kept in sync across both databases throughout the migration. What should a solutions architect recommend?


A. Use AWS DataSync for the initial migration. Use AWS Database Migration Service (AWS DMS) to create a change data capture (CDC) replication task and a table mapping to select all tables.


B. Use AWS DataSync for the initial migration. Use AWS Database Migration Service (AWS DMS) to create a full load plus change data capture (CDC) replication task and a table mapping to select all tables.


C. Use the AWS Schema Conversion Tool with AWS Database Migration Service (AWS DMS) using a memory optimized replication instance. Create a full load plus change data capture (CDC) replication task and a table mapping to select all tables.


D. Use the AWS Schema Conversion Tool with AWS Database Migration Service (AWS DMS) using a compute optimized replication instance. Create a full load plus change data capture (CDC) replication task and a table mapping to select the largest tables.





C.
  Use the AWS Schema Conversion Tool with AWS Database Migration Service (AWS DMS) using a memory optimized replication instance. Create a full load plus change data capture (CDC) replication task and a table mapping to select all tables.

A company is launching a new application and will display application metrics on an Amazon CloudWatch dashboard. The company’s product manager needs to access this dashboard periodically. The product manager does not have an AWS account. A solution architect must provide access to the product manager by following the principle of least privilege.
Which solution will meet these requirements?


A. Share the dashboard from the CloudWatch console. Enter the product manager’s email address, and complete the sharing steps. Provide a shareable link for the dashboard to the product manager.


B. Create an IAM user specifically for the product manager. Attach the CloudWatch Read Only Access managed policy to the user. Share the new login credential with the product manager. Share the browser URL of the correct dashboard with the product manager.


C. Create an IAM user for the company’s employees, Attach the View Only Access AWS managed policy to the IAM user. Share the new login credentials with the product manager. Ask the product manager to navigate to the CloudWatch console and locate the dashboard by name in the Dashboards section.


D. Deploy a bastion server in a public subnet. When the product manager requires access to the dashboard, start the server and share the RDP credentials. On the bastion server, ensure that the browser is configured to open the dashboard URL with cached AWS credentials that have appropriate permissions to view the dashboard.





B.
  Create an IAM user specifically for the product manager. Attach the CloudWatch Read Only Access managed policy to the user. Share the new login credential with the product manager. Share the browser URL of the correct dashboard with the product manager.

Explanation: To provide the product manager access to the Amazon CloudWatch dashboard while following the principle of least privilege, a solution architect should create an IAM user specifically for the product manager and attach the CloudWatch Read Only Access managed policy to the user. This policy allows the user to view the dashboard without being able to make any changes to it. The solution architect should then share the new login credential with the product manager and provide them with the browser URL of the correct dashboard.


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