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| Section | Weight | Objectives |
|---|
| Topic 1: Design solutions for organizational complexity | 26% | |
| Topic 2: Continuous improvement for existing solutions | 25% | |
| Topic 3: Design for new solutions | 29% | |
| Topic 4: Accelerate workload migration and modernization | 20% | |
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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q69-Q74):
NEW QUESTION # 69
A financial services company receives a regular data feed from its credit card servicing partner Approximately
5.000 records are sent every 15 minutes in plaintext, delivered over HTTPS directly into an Amazon S3 bucket with server-side encryption. This feed contains sensitive credit card primary account number (PAN) data The company needs to automatically mask the PAN before sending the data to another S3 bucket for additional internal processing. The company also needs to remove and merge specific fields, and then transform the record into JSON format Additionally, extra feeds are likely to be added in the future, so any design needs to be easily expandable.
Which solutions will meet these requirements?
- A. Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Trigger another Lambda function when new messages arrive in the SQS queue to process the records, writing the results to a temporary location in Amazon S3. Trigger a final Lambda function once the SQS queue is empty to transform the records into JSON format and send the results to another S3 bucket for internal processing.
- B. Create an AWS Glue crawler and custom classifier based on the data feed formats and build a table definition to match. Trigger an AWS Lambda function on file delivery to start an AWS Glue ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, have the ETL job send the results to another S3 bucket for internal processing.
- C. Create an AWS Glue crawler and custom classifier based upon the data feed formats and build a table definition to match. Perform an Amazon Athena query on file delivery to start an Amazon EMR ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, send the results to another S3 bucket for internal processing and scale down the EMR cluster.
- D. Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Configure an AWS Fargate container application to automatically scale to a single instance when the SQS queue contains messages. Have the application process each record, and transform the record into JSON format. When the queue is empty, send the results to another S3 bucket for internal processing and scale down the AWS Fargate instance.
Answer: B
Explanation:
You can use a Glue crawler to populate the AWS Glue Data Catalog with tables. The Lambda function can be triggered using S3 event notifications when object create events occur. The Lambda function will then trigger the Glue ETL job to transform the records masking the sensitive data and modifying the output format to JSON. This solution meets all requirements.
NEW QUESTION # 70
A company is deploying a new API to AWS. The API uses Amazon API Gateway with a Regional API endpoint and an AWS Lambda function for hosting. The API retrieves data from an external vendor API, stores data in an Amazon DynamoDB global table, and retrieves data from the DynamoDB global table. The API key for the vendor's API is stored in AWS Secrets Manager and is encrypted with a customer managed key in AWS Key Management Service (AWS KMS). The company has deployed its own API into a single AWS Region.
A solutions architect needs to change the API components of the company's API to ensure that the components can run across multiple Regions in an active-active configuration.
Which combination of changes will meet this requirement with the LEAST operational overhead? (Choose three.)
- A. Create a new AWS managed KMS key in each in-scope Region. Convert an existing key to a multi-Region key. Use the multi-Region key in other Regions.
- B. Create a new Secrets Manager secret in each in-scope Region. Copy the secret value from the existing Region to the new secret in each in-scope Region.
- C. Deploy the API to multiple Regions. Configure Amazon Route 53 with custom domain names that route traffic to each Regional API endpoint. Implement a Route 53 multivalue answer routing policy.
- D. Replicate the existing Secrets Manager secret to other Regions. For each in-scope Region's replicated secret, select the appropriate KMS key.
- E. Create a new KMS multi-Region customer managed key. Create a new KMS customer managed replica key in each in-scope Region.
- F. Modify the deployment process for the Lambda function to repeat the deployment across in-scope Regions. Turn on the multi-Region option for the existing API. Select the Lambda function that is deployed in each Region as the backend for the multi-Region API.
Answer: C,D,E
Explanation:
The combination of changes that will meet the requirement with the least operational overhead are:
A). Deploy the API to multiple Regions. Configure Amazon Route 53 with custom domain names that route traffic to each Regional API endpoint. Implement a Route 53 multivalue answer routing policy.
B). Create a new KMS multi-Region customer managed key. Create a new KMS customer managed replica key in each in-scope Region.
C). Replicate the existing Secrets Manager secret to other Regions. For each in-scope Region's replicated secret, select the appropriate KMS key.
These changes will enable the company to have an active-active configuration for its API across multiple Regions, while minimizing the complexity and cost of managing the secrets and keys.
A). This change will allow the company to use Route 53 to distribute traffic across multiple Regional API endpoints, based on the availability and latency of each endpoint. This will improve the performance and availability of the API for global customers12
B). This change will allow the company to use KMS multi-Region keys, which are KMS keys in different Regions that can be used interchangeably. This will simplify the encryption and decryption of secrets across Regions, as the same key material and key ID can be used in any Region34
C). This change will allow the company to use Secrets Manager replication, which replicates the encrypted secret data and metadata across the specified Regions. This will ensure that the secrets are consistent and accessible in any Region, and that any update made to the primary secret will be propagated to the replica secrets automatically56 References:
1: Creating a regional API endpoint - Amazon API Gateway 2: Multivalue answer routing policy - Amazon Route 53 3: Multi-Region keys in AWS KMS - AWS Key Management Service 4: Creating multi-Region keys
- AWS Key Management Service 5: Replicate an AWS Secrets Manager secret to other AWS Regions 6: How to replicate secrets in AWS Secrets Manager to multiple Regions | AWS Security Blog
NEW QUESTION # 71
A company runs many workloads on AWS and uses AWS Organizations to manage its accounts.
The workloads are hosted on Amazon EC2, AWS Fargate, and AWS LambdA. Some of the workloads have unpredictable demand. Accounts record high usage in some months and low usage in other months.
The company wants to optimize its compute costs over the next 3 years. A solutions architect obtains a 6-month average for each of the accounts across the organization to calculate usage.
Which solution will provide the MOST cost savings for all the organization's compute usage?
- A. Purchase a Compute Savings Plan for the organization from the management account by using the recommendation at the management account level.
- B. Purchase Reserved Instances for the organization to match the size and number of the most common EC2 instances from the member accounts.
- C. Purchase an EC2 Instance Savings Plan for each member account from the management account based on EC2 usage data from the last 6 months.
- D. Purchase Reserved Instances for each member account that had high EC2 usage according to the data from the last 6 months.
Answer: A
NEW QUESTION # 72
A financial company needs to create a separate AWS account for a new digital wallet application.
The company uses AWS Organizations to manage its accounts. A solutions architect uses the IAM user Support1 from the management account to create a new member account with finance1@example.com as the email address.
What should the solutions architect do to create IAM users in the new member account?
- A. Go to the AWS Management Console sign-in page. Sign in by using the account ID of the new member account and the Support1 IAM credentials. Set up the IAM users as required.
- B. Sign in to the AWS Management Console with AWS account root user credentials by using the
64-character password from the initial AWS Organizations email sent to finance1@example.com.
Set up the IAM users as required. - C. From the management account, switch roles to assume the OrganizationAccountAccessRole role with the account ID of the new member account. Set up the IAM users as required.
- D. Go to the AWS Management Console sign-in page. Choose sign in using root account credentials.?Sign in in by using the email address finance 1@example.com and the management account's root password. Set up the IAM users as required.
Answer: C
Explanation:
https://repost.aws/knowledge-center/organizations-member-account-access
NEW QUESTION # 73
A company has purchased appliances from different vendors. The appliances all have loT sensors. The sensors send status information in the vendors' proprietary formats to a legacy application that parses the information into JSON. The parsing is simple, but each vendor has a unique format. Once daily, the application parses all the JSON records and stores the records in a relational database for analysis.
The company needs to design a new data analysis solution that can deliver faster and optimize costs.
Which solution will meet these requirements?
- A. Use AWS Snowball Edge to collect data from the loT sensors directly to perform local analysis.
Periodically collect the data into Amazon Redshift to perform global analysis. - B. Connect the loT sensors to AWS loT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon S3. Use AWS Glue to catalog the files. Use Amazon Athena and Amazon OuickSight for analysis.
- C. Migrate the application server to AWS Fargate, which will receive the information from loT sensors and parse the information into a relational format. Save the parsed information to Amazon Redshift for analysis.
- D. Create an AWS Transfer for SFTP server. Update the loT sensor code to send the information as a .csv file through SFTP to the server. Use AWS Glue to catalog the files. Use Amazon Athena for analysis.
Answer: B
Explanation:
Connect the IoT sensors to AWS IoT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon S3. Use AWS Glue to catalog the files. Use Amazon Athena and Amazon QuickSight for analysis. This solution meets the requirement of faster analysis and cost optimization by using AWS IoT Core to collect data from the IoT sensors in real-time and then using AWS Glue and Amazon Athena for efficient data analysis.
This solution involves connecting the loT sensors to the AWS loT Core, setting a rule to invoke an AWS Lambda function to parse the information, and saving a .csv file to Amazon S3. AWS Glue can be used to catalog the files and Amazon Athena and Amazon QuickSight can be used for analysis. This solution will enable faster and more cost-effective data analysis. This solution is in line with the official Amazon Textbook and Resources for the AWS Certified Solutions Architect - Professional certification. In particular, the book states that: "AWS IoT Core can be used to ingest and process the data, AWS Lambda can be used to process and transform the data, and Amazon S3 can be used to store the data. AWS Glue can be used to catalog and access the data, Amazon Athena can be used to query the data, and Amazon QuickSight can be used to visualize the data."
NEW QUESTION # 74
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