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Amazon SAA-C03 Exam Overview:

Certification Vendor:	Amazon AWS
Exam Name:	AWS Certified Solutions Architect - Associate
Exam Number:	SAA-C03
Certificate Validity Period:	3 years
Exam Price:	$150 USD
Passing Score:	720 (scaled score 100–1000)
Available Languages:	Simplified Chinese, German, French, Korean, Spanish (Latin America), Traditional Chinese, Spanish (Spain), Portuguese (Brazil), English, Italian, Japanese
Exam Format:	Multiple-choice, Multiple-response
Real Exam Qty:	65 (50 scored + 15 unscored)
Related Certifications:	AWS Certified Security - Specialty AWS Certified Solutions Architect - Professional AWS Certified DevOps Engineer - Professional AWS Certified Cloud Practitioner
Exam Duration:	130 minutes
Recommended Training:	AWS Certified Solutions Architect - Associate Exam Guide AWS Official Training
Exam Registration:	Pearson VUE Registration AWS Certification Registration
Sample Questions:	Amazon SAA-C03 Sample Questions
Exam Way:	Online proctored or at Pearson VUE authorized test centers
Pre Condition:	No mandatory prerequisites; recommended 1+ year hands-on experience designing cloud solutions on AWS; AWS Cloud Practitioner recommended but not required
Official Syllabus URL:	https://docs.aws.amazon.com/aws-certification/latest/solutions-architect-associate-03/solutions-architect-associate-03.pdf

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SAA-C03 Buch & SAA-C03 Exam Fragen

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Amazon AWS Certified Solutions Architect - Associate SAA-C03 Prüfungsfragen mit Lösungen (Q643-Q648):

643. Frage
A company temporarily stages transactional datasets in an Amazon S3 bucket before the company moves the datasets to their final destinations. Some datasets include personally identifiable information PII.
The company must remove PII data during staging before the company moves the datasets to their destinations. A solutions architect needs to configure Amazon Macie to continuously monitor the datasets.
Which solution will meet these requirements with the LEAST operational overhead?

A. Schedule a daily Amazon Macie discovery job. Create an AWS Lambda function to run once every day to remove the PII data that the daily Macie job finds.
B. Create an AWS Lambda function that runs once each day to list all datasets that are saved to the S3 bucket every day. Call Amazon Macie on the list of datasets. Create a second Lambda function to remove the PII data that Macie finds. Configure an Amazon EventBridge rule to invoke the PII removal Lambda function every day.
C. Create an AWS Lambda function to launch an Amazon Macie discovery job when a new dataset is stored in the target S3 bucket if a Macie discovery job is not already running. Create a second Lambda function to remove the PII data that the Macie discovery job finds.
D. Set up Amazon Macie automated sensitive data discovery. Create an AWS Lambda function to remove the PII data that Macie finds. Configure an Amazon EventBridge rule to invoke the Lambda function when Macie discovers PII data.

Antwort: D

Begründung:
AWS documents that Amazon Macie supportsautomated sensitive data discovery, which continuously discovers and reports sensitive data in S3. AWS also documents that Macie findings can be processed automatically by usingAmazon EventBridge, including sending those events to a Lambda function for remediation or downstream processing. That combination provides continuous monitoring with low operational overhead and avoids the custom scheduling and job-launch logic in the other options. Because the question explicitly asks for continuous monitoring and low overhead, Macie automated sensitive data discovery plus EventBridge-triggered Lambda remediation is the best fit.

644. Frage
A healthcare company is designing a system to store and manage logs in the AWS Cloud. The system ingests and stores logs that are in JSON format. The logs contain sensitive patient information. The company must identify any sensitive data. The company must be able to search the log data by using SQL queries. Which solution will meet these requirements?

A. Store the logs in an Amazon S3 bucket. Configure Amazon Macie to discover sensitive data. Use Amazon Athena to query the logs.
B. Store the logs in Amazon DynamoDB. Use AWS Key Management Service (AWS KMS) to discover sensitive data. Use Amazon Redshift Spectrum to query the logs.
C. Store the logs in an Amazon Elastic Block Store (Amazon EBS) volume. Create an application that uses Amazon SageMaker AI to detect sensitive data. Use Amazon RDS to query the logs.
D. Store the logs in an Amazon S3 bucket. Use Amazon Inspector to discover sensitive data. Use Amazon Athena to query the logs.

Antwort: A

Begründung:
Storing the JSON logs in Amazon S3 provides durable, scalable storage. Amazon Macie is specifically designed to discover and classify sensitive data in S3, including PII and healthcare- related data. You can then use Amazon Athena to run SQL queries directly on the JSON log files in S3, satisfying the requirement to search the log data with SQL while retaining strong security and compliance capabilities.

645. Frage
A company that is in the ap-northeast-1 Region has a fleet of thousands of AWS Outposts servers. The company has deployed the servers at remote locations around the world. All the servers regularly download new software versions that consist of 100 files. There is significant latency before all servers run the new software versions. The company must reduce the deployment latency for new software versions. Which solution will meet this requirement with the LEAST operational overhead?

A. Create an Amazon S3 bucket in ap-northeast-1. Set up an Amazon CloudFront distribution in ap- northeast-1 that includes a CachingDisabled cache policy. Configure the S3 bucket as the origin.
Download the software by using signed URLs.
B. Create an Amazon S3 bucket in ap-northeast-1. Configure Amazon S3 Transfer Acceleration.
Download the software by using the S3 Transfer Acceleration endpoint.
C. Create an Amazon S3 bucket in ap-northeast-1. Create a second S3 bucket in the us-east-1 Region. Configure replication between the buckets. Set up an Amazon CloudFront distribution that uses ap-northeast-1 as the primary origin and us-east-1 as the secondary origin. Download the software by using signed URLs.
D. Create an Amazon S3 bucket in ap-northeast-1. Set up an Amazon CloudFront distribution.Configure the S3 bucket as the origin. Download the software by using signed URLs.

Antwort: D

646. Frage
A company is designing the architecture for a new mobile app that uses the AWS Cloud. The company uses organizational units (OUs) in AWS Organizations to manage its accounts. The company wants to tag Amazon EC2 instances with data sensitivity by using values of sensitive and nonsensitive 1AM identities must not be able to delete a tag or create instances without a tag Which combination of steps will meet these requirements? (Select TWO.)

A. Create a tag policy to deny running instances when a tag key is not specified. Create another tag policy that prevents identities from deleting tags Attach the tag policies to the appropriate OU.
B. In Organizations, create a new service control policy (SCP) that specifies the data sensitivity tag key and the required tag values Enforce the tag values for the EC2 instances. Attach the SCP to the appropriate OU.
C. Create an AWS Config rule to check if EC2 instances use the data sensitivity tag and the specified values. Configure an AWS Lambda function to delete the resource if a noncompliant resource is found.
D. In Organizations, create a new tag policy that specifies the data sensitivity tag key and the required values. Enforce the tag values for the EC2 instances Attach the tag policy to the appropriate OU.
E. Create a service control policy (SCP) to deny creating instances when a tag key is not specified. Create another SCP that prevents identities from deleting tags Attach the SCPs to the appropriate OU.

Antwort: D,E

Begründung:
To meet the requirements for tagging and preventing instance creation or deletion without proper tags, the company can use a combination of AWS Organizations tag policies and service control policies (SCPs).
Tag Policies: These enforce specific tag values across resources. Creating a tag policy with required values (e.
g., sensitive, non-sensitive) and attaching it to the appropriate organizational unit (OU) ensures consistency in tagging.
SCPs: SCPs can be used to enforce compliance by preventing instance creation without a tag and preventing tag deletion. These policies control actions at the account level across the organization.
Key AWS features:
Tag Policies help standardize tags across accounts, and SCPs enforce governance by restricting actions that violate the policies.
AWS Documentation: AWS best practices recommend using tag policies and SCPs to enforce compliance across multiple accounts within AWS Organizations.

647. Frage
A company runs container applications by using Amazon Elastic Kubernetes Service (Amazon EKS) and the Kubernetes Horizontal Pod Autoscaler. The workload is not consistent throughout the day. A solutions architect notices that the number of nodes does not automatically scale out when the existing nodes have reached maximum capacity in the cluster, which causes performance issues Which solution will resolve this issue with the LEAST administrative overhead?

A. Use an AWS Lambda function to resize the EKS cluster automatically.
B. Scale out the nodes by tracking the memory usage
C. Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.
D. Use an Amazon EC2 Auto Scaling group to distribute the workload.

Antwort: C

Begründung:
The Kubernetes Cluster Autoscaler is a component that automatically adjusts the number of nodes in your cluster when pods fail or are rescheduled onto other nodes. It uses Auto Scaling groups to scale up or down the nodes according to the demand and capacity ofyour cluster1.
By using the Kubernetes Cluster Autoscaler in your Amazon EKS cluster, you can achieve the following benefits:
You can improve the performance and availability of your container applications by ensuring that there are enough nodes to run your pods and that there are no idle nodes wasting resources.
You can reduce the administrative overhead of managing your cluster size manually or using custom scripts.
The Cluster Autoscaler handles the scaling decisions and actions for you based on the metrics and events from your cluster.
You can leverage the integration of Amazon EKS and AWS Auto Scaling to optimize the cost and efficiency of your cluster. You can use features such as launchtemplates, mixed instances policies, and spot instances to customize your node configuration and save up to 90% on compute costs2

648. Frage
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