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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Sample Questions (Q317-Q322):

NEW QUESTION # 317
A 3-tier e-commerce web application is current deployed on-premises and will be migrated to AWS for greater scalability and elasticity The web server currently shares read-only data using a network distributed file system The app server tier uses a clustering mechanism for discovery and shared session state that depends on IP multicast The database tier uses shared-storage clustering to provide database fall over capability, and uses several read slaves for scaling Data on all servers and the distributed file system directory is backed up weekly to off-site tapes
Which AWS storage and database architecture meets the requirements of the application?

A. Web servers store read-only data In S3 and copy from S3 to root volume at boot time App servers share state using a combination of DynamoDB and IP unicast Database use RDS with multi-AZ deployment Backup web and app servers backed up weekly via AM is. database backed up via DB snapshots
B. Web servers store -read-only data in S3, and copy from S3 to root volume at boot time App servers share state using a combination of DynamoDB and IP unicast Database, use RDS with multi-AZ deployment and one or more read replicas Backup web servers app servers, and database backed up weekly to Glacier using snapshots.
C. Web servers, store read-only data in S3, and copy from S3 to root volume at boot time App servers snare state using a combination or DynamoDB and IP unicast Database use RDS with multi-AZ deployment and one or more Read Replicas Backup web and app servers backed up weekly via Mils database backed up via DB snapshots.
D. Web servers, store read-only data in an EC2 NFS server, mount to each web server at boot time App servers share state using a combination of DynamoDB and IP multicast Database use RDS with multl-AZ deployment and one or more Read Replicas Backup web and app servers backed up weekly via Mils database backed up via DB snapshots

Answer: C

NEW QUESTION # 318
A company build an application that gives users the ability to check in to places they visit, rank the places, and add reviews about their experiences. The application is successful and is experiencing a rapid increase in the number of users every month.
The company uses a single Amazon RDS for MySQL DB instance for its database. The company fears that the database might not be able to handle the load for the upcoming month because the DB instance has activated alarms that are related to resource exhaustion.
A solutions architect must design a solution that prevents service interruptions at the database layer. The solutions architect also must minimize any changes to code.
Which solution meets these requirements?

A. Turn on the Multi-AZ feature for the DB instance. Redirect read-only traffic to the standby replica endpoint.
B. Create RDS read replicas. Redirect read-only traffic to the read replica endpoints
C. Create an Amazon EMR cluster. Migrate the data to a Hadoop Distributed File System (HDFS) with a replication factor of 3.
D. Create an Amazon ElastiCache cluster. Redirect all read-only traffic to the cluster. Set up the cluster to be deployed in three Availability Zones

Answer: B

NEW QUESTION # 319
A mining company is using Amazon S3 as its data lake. The company wants to analyze the data collected by the sensors in its mines. A data pipeline is being built to capture data from the sensors, ingest the data into an S3 bucket, and convert the data to Apache Parquet format. The data pipeline must be processed in near-real time. The data will be used for on-demand queries with Amazon Athena.
Which solution will meet these requirements?

A. Use Amazon Data Firehose to invoke an AWS Lambda function that converts the data to Parquet format and stores the data in Amazon S3.
B. Use AWS DataSync to invoke an AWS Lambda function that converts the data to Parquet format and stores the data in Amazon S3.
C. Use Amazon Kinesis Data Streams to invoke an AWS Lambda function that converts the data to Parquet format and stores the data in Amazon S3.
D. Use Amazon Simple Queue Service (Amazon SQS) to stream data directly to an AWS Glue job that converts the data to Parquet format and stores the data in Amazon S3.

Answer: A

Explanation:
Amazon Kinesis Data Firehose (now known as Amazon Data Firehose) supports near-real-time streaming, with built-in support to:
Invoke AWS Lambda functions for transformation.
Store data directly into Amazon S3 in desired formats like Apache Parquet.
"You can use Data Firehose to transform the data before delivering it, by invoking a Lambda function. You can convert to formats such as JSON or Apache Parquet before storing it into S3."
- Amazon Data Firehose Developer Guide
Why not the others?
B: Kinesis Data Streams requires more operational overhead than Firehose.
C: DataSync is for file movement-not stream processing.
D: SQS isn't designed for streaming and transformation pipelines.
Reference:
Amazon Data Firehose Transformations

NEW QUESTION # 320
A gaming company has multiple Amazon EC2 instances in a single Availability Zone for its multiplayer game that communicates with users on Layer 4. The chief technology officer (CTO) wants to make the architecture highly available and cost-effective What should a solutions architect do to meet these requirements? (Select TWO.)

A. Decrease the number of EC2 Instances
B. Configure an Application Load Balancer In front of the EC2 instances
C. Configure an Auto Scaling group to add or remove Instances in multiple Availability Zones automatically
D. Configure a Network Load Balancer in front of the EC2 instances.
E. Increase the number of EC2 instances

Answer: C,D

NEW QUESTION # 321
A solutions architect needs to host a high performance computing (HPC) workload in the AWS Cloud. The workload will run on hundreds of Amazon EC2 instances and will require parallel access to a shared file system to enable distributed processing of large datasets. Datasets will be accessed across multiple instances simultaneously. The workload requires access latency within 1 ms. After processing has completed, engineers will need access to the dataset for manual postprocessing.
Which solution will meet these requirements?

A. Use Amazon Elastic File System (Amazon EFS) as a shared file system. Access the dataset from Amazon EFS.
B. Mount an Amazon S3 bucket to serve as the shared file system. Perform postprocessing directly from the S3 bucket.
C. Use Amazon FSx for Lustre as a shared file system. Link the file system to an Amazon S3 bucket for postprocessing.
D. Configure AWS Resource Access Manager to share an Amazon S3 bucket so that it can be mounted to all instances for processing and postprocessing.

Answer: C

Explanation:
Explanation/Reference: https://jayendrapatil.com/aws-fsx-for-lustre/

NEW QUESTION # 322
......

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