Free SAA-C03 Exam Braindumps
AWS Certified Solutions Architect - Associate SAA-C03 Questions 256–260 (page: 53)

Updated On: 16-Mar-2026

A solutions architect is implementing a document review application using an Amazon S3 bucket for storage. The solution must prevent accidental deletion of the documents and ensure that all versions of the documents are available. Users must be able to download, modify, and upload documents.
Which combination of actions should be taken to meet these requirements? (Choose two.)

  1. Enable a read-only bucket ACL.
  2. Enable versioning on the bucket.
  3. Attach an IAM policy to the bucket.
  4. Enable MFA Delete on the bucket.
  5. Encrypt the bucket using AWS KMS.

Answer(s): B,D

Explanation:

Enabling versioning ensures all object versions are preserved and recoverable, meeting the “all versions available” requirement. Enabling MFA Delete adds protection against accidental deletion, fulfilling the “prevent accidental deletion” condition when combined with versioning.
A) Read-only bucket ACL would prevent users from uploading or modifying, contradicting the requirement for download/modify/upload.
C) An IAM policy to the bucket alone does not by itself prevent deletions or ensure versioning state; policy must be paired with versioning and access controls.
E) Server-side encryption (KMS) protects data at rest but does not address deletion protection or versioning guarantees.



A company is building a solution that will report Amazon EC2 Auto Scaling events across all the applications in an AWS account. The company needs to use a serverless solution to store the EC2 Auto Scaling status data in Amazon S3. The company then will use the data in Amazon S3 to provide near-real-time updates in a dashboard. The solution must not affect the speed of EC2 instance launches.
How should the company move the data to Amazon S3 to meet these requirements?

  1. Use an Amazon CloudWatch metric stream to send the EC2 Auto Scaling status data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
  2. Launch an Amazon EMR cluster to collect the EC2 Auto Scaling status data and send the data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
  3. Create an Amazon EventBridge rule to invoke an AWS Lambda function on a schedule. Configure the Lambda function to send the EC2 Auto Scaling status data directly to Amazon S3.
  4. Use a bootstrap script during the launch of an EC2 instance to install Amazon Kinesis Agent. Configure Kinesis Agent to collect the EC2 Auto Scaling status data and send the data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.

Answer(s): A

Explanation:

A) Correct. CloudWatch metric streams can reliably stream EC2 Auto Scaling status metrics in near real-time to Kinesis Data Firehose, which then writes to S3 without impacting instance launch speeds, providing serverless, scalable ingestion for dashboards.
B) EMR adds unnecessary provisioning and latency; not serverless and could impact data freshness and cost for simple metric streaming.
C) EventBridge with scheduled Lambda introduces latency and polling gaps; not ideal for near-real-time Auto Scaling events and adds Lambda execution overhead.
D) Bootstrap with Kinesis Agent runs on each instance; violates serverless requirement and could impose overhead during instance launches and scaling.



A company has an application that places hundreds of .csv files into an Amazon S3 bucket every hour. The files are 1 GB in size. Each time a file is uploaded, the company needs to convert the file to Apache Parquet format and place the output file into an S3 bucket.
Which solution will meet these requirements with the LEAST operational overhead?

  1. Create an AWS Lambda function to download the .csv files, convert the files to Parquet format, and place the output files in an S3 bucket. Invoke the Lambda function for each S3 PUT event.
  2. Create an Apache Spark job to read the .csv files, convert the files to Parquet format, and place the output files in an S3 bucket. Create an AWS Lambda function for each S3 PUT event to invoke the Spark job.
  3. Create an AWS Glue table and an AWS Glue crawler for the S3 bucket where the application places the .csv files. Schedule an AWS Lambda function to periodically use Amazon Athena to query the AWS Glue table, convert the query results into Parquet format, and place the output files into an S3 bucket.
  4. Create an AWS Glue extract, transform, and load (ETL) job to convert the .csv files to Parquet format and place the output files into an S3 bucket. Create an AWS Lambda function for each S3 PUT event to invoke the ETL job.

Answer(s): D

Explanation:

The ETL job in AWS Glue handles large CSV-to-Parquet conversions with serverless, scalable orchestration and minimal operational overhead, triggered by S3 events.
A) Lambda per event would be inefficient for 1 GB files; Lambda has short execution limits and higher overhead for large data processing.
B) Spark job with per-event invocation adds extra orchestration and infrastructure management; not as low-overhead as Glue ETL.
C) Athena/Glue crawler approach adds unnecessary steps, uses query results rather than direct file transformation, increasing latency and cost.
D) Glue ETL job directly processes CSVs to Parquet in a managed, serverless ETL pipeline, and is invoked by S3 events for scalable, low-maintenance operation.



A company is implementing new data retention policies for all databases that run on Amazon RDS DB instances. The company must retain daily backups for a minimum period of 2 years. The backups must be consistent and restorable.
Which solution should a solutions architect recommend to meet these requirements?

  1. Create a backup vault in AWS Backup to retain RDS backups. Create a new backup plan with a daily schedule and an expiration period of 2 years after creation. Assign the RDS DB instances to the backup plan.
  2. Configure a backup window for the RDS DB instances for daily snapshots. Assign a snapshot retention policy of 2 years to each RDS DB instance. Use Amazon Data Lifecycle Manager (Amazon DLM) to schedule snapshot deletions.
  3. Configure database transaction logs to be automatically backed up to Amazon CloudWatch Logs with an expiration period of 2 years.
  4. Configure an AWS Database Migration Service (AWS DMS) replication task. Deploy a replication instance, and configure a change data capture (CDC) task to stream database changes to Amazon S3 as the target. Configure S3 Lifecycle policies to delete the snapshots after 2 years.

Answer(s): A

Explanation:

A) Creates a centralized, durable backup vault and automatic, compliant retention for RDS backups via AWS Backup, ensuring daily backups are retained for 2 years and remain restorable.
B) RDS daily snapshots with a 2-year retention via DLM is not applicable to RDS backups; DLM primarily manages EBS snapshots, not managed RDS automated backups.
C) Transaction log backups to CloudWatch Logs do not provide full-database point-in-time restore for RDS; this option does not guarantee complete, restorable daily backups for all RDS engines.
D) DMS CDC to S3 with lifecycle policies retains changes, not full daily backups; restoration from CDC-derived data is not equivalent to RDS automated backups.



A company’s compliance team needs to move its file shares to AWS. The shares run on a Windows Server SMB file share. A self-managed on-premises Active Directory controls access to the files and folders.
The company wants to use Amazon FSx for Windows File Server as part of the solution. The company must ensure that the on-premises Active Directory groups restrict access to the FSx for Windows File Server SMB compliance shares, folders, and files after the move to AWS. The company has created an FSx for Windows File Server file system.
Which solution will meet these requirements?

  1. Create an Active Directory Connector to connect to the Active Directory. Map the Active Directory groups to IAM groups to restrict access.
  2. Assign a tag with a Restrict tag key and a Compliance tag value. Map the Active Directory groups to IAM groups to restrict access.
  3. Create an IAM service-linked role that is linked directly to FSx for Windows File Server to restrict access.
  4. Join the file system to the Active Directory to restrict access.

Answer(s): D

Explanation:

The correct answer is D. Joining the FSx for Windows File Server file system to the on‑premises Active Directory enables AD-based permissions (groups, SACLs, NTFS permissions) to govern SMB access, preserving existing compliance controls.
Why the others are incorrect:
A) Active Directory Connector is for AWS Managed Microsoft AD integration with S3, not for directly applying on-prem AD ACLs to FSx; mapping AD groups to IAM groups does not affect SMB permissions.
B) Tag-based access control does not enforce SMB/NTFS permissions or AD group membership for FSx shares.
C) An IAM service‑linked role controls AWS service permissions, not SMB file share access or on‑prem AD group authorization.



Viewing page 53 of 205
Viewing questions 261 - 265 out of 1019 questions


Post your Comments and Discuss Amazon SAA-C03 exam prep with other Community members:

AI Tutor AI Tutor 👋 I’m here to help!