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Passing the Amazon SAA-C03 Exam requires a thorough understanding of AWS services and their architecture. It is a challenging exam that tests the candidate's ability to design and implement scalable and reliable solutions on the AWS platform. Candidates who pass the exam are awarded the AWS Certified Solutions Architect - Associate certification, which is recognized globally and can help professionals advance their careers in the cloud computing industry.

Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q120-Q125):

NEW QUESTION # 120
[Design High-Performing Architectures]
A company uses Amazon EC2 instances and Amazon Elastic Block Store (Amazon EBS) volumes to run an application. The company creates one snapshot of each EBS volume every day.
The company needs to prevent users from accidentally deleting the EBS volume snapshots. The solution must not change the administrative rights of a storage administrator user.
Which solution will meet these requirements with the LEAST administrative effort?

A. Create an IAM policy that denies snapshot deletion. Attach the policy to the storage administrator user.
B. Add tags to the snapshots. Create tag-level retention rules in the Recycle Bin for EBS snapshots. Configure rule lock settings for the retention rules.
C. Take EBS snapshots by using the EBS direct APIs. Copy the snapshots to an Amazon S3 bucket. Configure S3 Versioning and Object Lock on the bucket.
D. Create an IAM role that has permission to delete snapshots. Attach the role to a new EC2 instance. Use the AWS CLI from the new EC2 instance to delete snapshots.

Answer: B

Explanation:
Amazon EBS Snapshots Recycle Bin enables you to specify retention rules for EBS snapshots based on tags. When snapshots are deleted, they are retained in the Recycle Bin for a specified duration, preventing accidental deletion. Tag-level rules allow selective protection without changing IAM roles or user permissions.
Reference:

NEW QUESTION # 121
A medical company wants to perform transformations on a large amount of clinical trial data that comes from several customers. The company must extract the data from a relational database that contains the customer dat a. Then the company will transform the data by using a series of complex rules. The company will load the data to Amazon S3 when the transformations are complete.
All data must be encrypted where it is processed before the company stores the data in Amazon S3. All data must be encrypted by using customer-specific keys.
Which solution will meet these requirements with the LEAST amount of operational effort?

A. Create one Amazon EMR cluster for each customer Attach a security configuration to each cluster that uses server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the data.
B. Create one AWS Glue job for each customer Attach a security configuration to each job that uses server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the data.
C. Create one AWS Glue job for each customer Attach a security configuration to each job that uses client-side encryption with AWS KMS managed keys (CSE-KMS) to encrypt the data.
D. Create one Amazon EMR cluster for each customer Attach a security configuration to each cluster that uses client-side encryption with a custom client-side root key (CSE-Custom) to encrypt the data.

Answer: C

Explanation:
AWS Glue jobs are designed for extract, transform, and load (ETL) operations, which are perfect for transforming clinical trial data. AWS Glue integrates with AWS Key Management Service (KMS), allowing for customer-specific encryption keys, fulfilling the encryption requirement with minimal operational effort. Client-side encryption with AWS KMS ensures that the data is encrypted before it is sent to S3, aligning with the security needs specified in the scenario.
Key aspects:
AWS Glue: This managed ETL service simplifies data transformation, reduces operational overhead, and integrates seamlessly with KMS.
CSE-KMS: Client-side encryption with KMS ensures that the data is encrypted with customer-specific keys before it is processed or stored in S3, offering robust security.
Minimal Operational Overhead: Compared to managing an EMR cluster, AWS Glue automates much of the process, making it a lower-effort solution.
AWS Documentation: According to the AWS Well-Architected Framework, encryption with AWS KMS offers strong security controls that meet the needs of industries requiring high levels of confidentiality.

NEW QUESTION # 122
[Design High-Performing Architectures]
A company has a data ingestion workflow that consists the following:
An Amazon Simple Notification Service (Amazon SNS) topic for notifications about new data deliveries An AWS Lambda function to process the data and record metadata The company observes that the ingestion workflow fails occasionally because of network connectivity issues. When such a failure occurs, the Lambda function does not ingest the corresponding data unless the company manually reruns the job.
Which combination of actions should a solutions architect take to ensure that the Lambda function ingests all data in the future? (Select TWO.)

A. Modify the Lambda function to read from an Amazon Simple Queue Service (Amazon SQS) queue
B. Configure the Lambda function In multiple Availability Zones.
C. Increase provisioned throughput for the Lambda function.
D. Create an Amazon Simple Queue Service (Amazon SQS) queue, and subscribe It to me SNS topic.
E. Increase the CPU and memory that are allocated to the Lambda function.

Answer: A,D

Explanation:
To ensure that the Lambda function ingests all data in the future despite occasional network connectivity issues, the following actions should be taken:
Create an Amazon Simple Queue Service (SQS) queue and subscribe it to the SNS topic. This allows for decoupling of the notification and processing, so that even if the processing Lambda function fails, the message remains in the queue for further processing later.
Modify the Lambda function to read from the SQS queue instead of directly from SNS. This decoupling allows for retries and fault tolerance and ensures that all messages are processed by the Lambda function.
Reference:
AWS SNS documentation:https://aws.amazon.com/sns/
AWS SQS documentation:https://aws.amazon.com/sqs/
AWS Lambda documentation:https://aws.amazon.com/lambda/

NEW QUESTION # 123
Question:
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.
Options:

A. 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.
B. Create an AWS Glue DataBrew Job to migrate data from Aurora to Amazon S3. Configure S3 Lifecycle rules on the S3 bucket.
C. 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.
D. Create an AWS Glue crawler to export data to Amazon S3. Create an AWS Lambda function to compress the data.

Answer: A

Explanation:
The SELECT INTO OUTFILE S3 feature allows you to export Amazon Aurora MySQL data directly to Amazon S3 with minimal operational overhead. This method is efficient and cost-effective for archiving historical data.
* You can configure S3 Lifecycle rules to transition the exported data to lower-cost storage (e.g., S3 Glacier or S3 Standard-IA) and eventually delete it after 5 years.
* No need for additional ETL tools like Glue or DataBrew unless complex transformations are required.
References:
Exporting data from Aurora MySQL to S3

NEW QUESTION # 124
A solutions architect is creating an application. The application will run on Amazon EC2 instances in private subnets across multiple Availability Zones in a VPC. The EC2 instances will frequently access large files that contain confidential information. These files are stored in Amazon S3 buckets for processing. The solutions architect must optimize the network architecture to minimize data transfer costs.
What should the solutions architect do to meet these requirements?

A. Create a gateway endpoint for Amazon S3 in the VPC. In the route tables for the private subnets, add an entry for the gateway endpoint
B. Create an AWS PrivateLink interface endpoint for Amazon S3 in the VPC. In the route tables for the private subnets, add an entry for the interface endpoint.
C. Create a single NAT gateway in a public subnet. In the route tables for the private subnets, add a default route that points to the NAT gateway
D. Create one NAT gateway for each Availability Zone in public subnets. In each of the route labels for the private subnets, add a default route that points lo the NAT gateway in the same Availability Zone

Answer: A

Explanation:
Understanding the Requirement: The application running on EC2 instances in private subnets needs frequent access to large confidential files stored in S3, minimizing data transfer costs.
Analysis of Options:
Gateway Endpoint for S3: Provides a secure, scalable, and cost-effective way for instances in private subnets to access S3 without using the internet or NAT gateways, thus minimizing data transfer costs.
Single NAT Gateway: Incurs additional costs for data transfer through the NAT gateway, which is not cost-effective.
PrivateLink Interface Endpoint for S3: Primarily used for accessing AWS services over a private connection but is more complex and costly compared to a gateway endpoint for S3.
Multiple NAT Gateways: Increases costs significantly and adds complexity without offering the cost benefits of a gateway endpoint.
Best Solution:
Gateway Endpoint for S3: This solution provides the required access with the least data transfer costs and minimal complexity.
Reference:
VPC Endpoints for Amazon S3
Gateway Endpoints

NEW QUESTION # 125
......

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