Free Amazon SAA-C03 Exam Questions

Question 1

A company is building a new application that uses multiple serverless architecture components. The application architecture includes an Amazon API Gateway REST API and AWS Lambda functions to manage incoming requests. The company needs a service to send messages that the REST API receives to multiple target Lambda functions for processing. The service must filter messages so each target Lambda function receives only the messages the function needs. Which solution will meet these requirements with the LEAST operational overhead?

A : Send the requests from the REST API to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe multiple Amazon Simple Queue Service (Amazon SQS) queues to the SNS topic. Configure the target Lambda functions to poll the SQS queues.

B : Send the requests from the REST API to a set of Amazon EC2 instances that are configured to process messages. Configure the instances to filter messages and to invoke the target Lambda functions.

C : Send the requests from the REST API to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Configure Amazon MSK to publish the messages to the target Lambda functions.

D : Send the requests from the REST API to multiple Amazon Simple Queue Service (Amazon SQS) queues. Configure the target Lambda functions to poll the SQS queues.

Answer: C

Question 2

A company runs HPC workloads requiring high IOPS.Which combination of steps will meet these requirements? (Select TWO)

A : Use Amazon EFS as a high-performance file system.

B : Use Amazon FSx for Lustre as a high-performance file system.

C : Create an Auto Scaling group of EC2 instances. Use Reserved Instances. Configure a spread placement group. Use AWS Batch for analytics.

D : Use Mountpoint for Amazon S3 as a high-performance file system.

E : Create an Auto Scaling group of EC2 instances. Use mixed instance types and a cluster placement group. Use Amazon EMR for analytics.

Answer: B,E

Question 3

A company wants to run a hybrid workload for data processing. The data needs to be accessed by on-premisesapplications for local data processing using an NFS protocol, and must also be accessible from the AWSCloud for further analytics and batch processing.Which solution will meet these requirements?

A : Use an AWS Storage Gateway file gateway to provide file storage to AWS, then perform analytics on this data in the AWS Cloud.

B : Use an AWS Storage Gateway tape gateway to copy the backup of the local data to AWS, then perform analytics on this data in the AWS Cloud.

C : Use an AWS Storage Gateway volume gateway in a stored volume configuration to regularly take snapshots of the local data, then copy the data to AWS.

D : Use an AWS Storage Gateway volume gateway in a cached volume configuration to back up all the local storage in the AWS Cloud, then perform analytics on this data in the cloud

Answer: A

Question 4

A solutions architect is designing a customer-facing application for a company. The application's database will have a clearly defined access pattern throughout the year and will have a variable number of reads and writes that depend on the time of year. The company must retain audit records for the database for 7 days. The recovery point objective (RPO) must be less than 5 hours. Which solution meets these requirements?

A : Use Amazon DynamoDB with auto scaling. Use on-demand backups and Amazon DynamoDB Streams.

B : Use Amazon Redshift. Configure concurrency scaling. Activate audit logging. Perform database snapshots every 4 hours.

C : Use Amazon RDS with Provisioned IOPS. Activate the database auditing parameter. Perform database snapshots every 5 hours.

D : Use Amazon Aurora MySQL with auto scaling. Activate the database auditing parameter.

Answer: D

Question 5

A company runs an online order management system on AWS. The company stores order and inventory data for the previous 5 years in an Amazon Aurora MySQL database. The company deletes inventory data after 5 years. The company wants to optimize costs to archive data.

A : Create an AWS Glue crawler to export data to Amazon S3. Create an AWS Lambda function to compress the data.

B : Use the SELECT INTO OUTFILE S3 query on the Aurora database to export the data to Amazon S3. Configure S3 Lifecycle rules on the S3 bucket.

C : Create an AWS Glue DataBrew Job to migrate data from Aurora to Amazon S3. Configure S3 Lifecycle rules on the S3 bucket.

D : Use the AWS Schema Conversion Tool (AWS SCT) to replicate data from Aurora to Amazon S3. Use the S3 Standard-Infrequent Access (S3 Standard-IA) storage class.

Answer: B