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NEW QUESTION # 232
A developer migrated a legacy application to an AWS Lambda function. The function uses a third-party service to pull data with a series of API calls at the end of each month. The function than processes the data to generate the monthly reports. The function has Been working with no issues so far.
The third-party service recently issued a restriction to allow a feed number to API calls each minute and each day. If the API calls exceed the limit tor each minute or each day, then the service will produce errors. The API also provides the minute limit and daily limit in the response header. This restriction might extend the overall process to multiple days because the process is consuming more API calls than the available limit.
What is the MOST operationally efficient way to refactor the server less application to accommodate this change?
Answer: B
Explanation:
The solution that will meet the requirements is to use an AWS Step Functions state machine to monitor API failures. Use the Wait state to delay calling the Lambda function. This way, the developer can refactor the serverless application to accommodate the change in a way that is automated and scalable. The developer can use Step Functions to orchestrate the Lambda function and handle any errors or retries. The developer can also use the Wait state to pause the execution for a specified duration or until a specified timestamp, which can help avoid exceeding the API limits. The other options either involve using additional services that are not necessary or appropriate for this scenario, or do not address the issue of API failures.
NEW QUESTION # 233
A developer is automating a new application deployment with AWS SAM. The new application has one AWS Lambda function and one Amazon S3 bucket. The Lambda function must access the S3 bucket to only read objects.
How should the developer configure AWS SAM to grant the necessary read permission to the S3 bucket?
Answer: C
Explanation:
Step-by-Step Breakdown:
Requirement Summary:
Use AWS SAM to deploy:
1 Lambda Function
1 S3 Bucket
Lambda needs read-only access to the S3 bucket
Solution must be expressed via AWS SAM template
Option A: Reference a second Lambda authorizer function
Incorrect: Lambda authorizers are used in API Gateway for authentication, not for granting S3 permissions.
Option B: Add a custom S3 bucket policy to the Lambda function
Incorrect: Bucket policies control who can access the bucket, not what the Lambda function can do.
The permission must be granted to the Lambda's IAM execution role.
Option C: Create an Amazon SQS topic for only S3 object reads
Incorrect: SQS cannot read objects from S3 and is not relevant to this scenario.
Option D: Add the S3ReadPolicy template to the Lambda function's execution role Correct: AWS SAM provides managed policy templates like AmazonS3ReadOnlyAccess and shortcuts like S3ReadPolicy.
You can apply these to the Lambda's execution role using the Policies: section in your SAM template.
Example SAM YAML:
yaml
CopyEdit
Resources:
MyFunction:
Type: AWS::Serverless::Function
Properties:
CodeUri: my-code/
Handler: app.handler
Runtime: python3.11
Policies:
- S3ReadPolicy:
BucketName: !Ref MyBucket
MyBucket:
Type: AWS::S3::Bucket
Properties:
BucketName: my-personal-bucket-name
SAM Policy Templates: https://docs.aws.amazon.com/serverless-application-model/latest/developerguide
/serverless-policy-templates.html
Example using S3ReadPolicy: https://docs.aws.amazon.com/serverless-application-model/latest
/developerguide/serverless-policy-templates.html#s3-readpolicy
NEW QUESTION # 234
An online food company provides an Amazon API Gateway HTTP API to receive orders for partners. The API is integrated with an AWS Lambda function. The Lambda function stores the orders in an Amazon DynamoDB table.
The company expects to onboard additional partners. Some of the partners require additional Lambda functions to receive orders. The company has created an Amazon S3 bucket. The company needs to store all orders and updates in the S3 bucket for future analysis.
How can the developer ensure that all orders and updates are stored to Amazon S3 with the LEAST development effort?
Answer: A
Explanation:
By enabling DynamoDB Streams on the DynamoDB table, you can capture changes (orders and updates) to the table. Whenever a new order or an update is made to the table, a stream record is generated. You can then create a new Lambda function, associate the stream's ARN with this Lambda function, and configure it to write the stream records (orders and updates) to the S3 bucket. This approach leverages built-in features of DynamoDB and Lambda, minimizing the development effort required to achieve the desired outcome.
NEW QUESTION # 235
A developer is publishing critical log data to a log group in Amazon CloudWatch Logs. The log group was created 2 months ago. The developer must encrypt the log data by using an AWS Key Management Service (AWS KMS) key so that future data can be encrypted to comply with the company's security policy.
Which solution will meet this requirement with the LEAST effort?
Answer: D
Explanation:
https://docs.aws.amazon.com/cli/latest/reference/logs/associate-kms-key.html
NEW QUESTION # 236
A company wants to run daily email promotions for its premium customers. The company has
5,000 premium customers who should receive the email messages.
A developer has created a serverless solution that uses an AWS Lambda function and Amazon SES for email notifications. The function ran successfully during unit testing. However, in production, the function is experiencing throttling issues.
What should the developer do to resolve this issue?
Answer: A
Explanation:
The throttling issue in production is likely caused by concurrent executions exceeding the account's limits or SES sending limits being breached. By configuring reserved concurrency for the Lambda function, the developer can limit and control the number of concurrent executions, helping to stay within Amazon SES rate limits and avoid throttling.
NEW QUESTION # 237
......
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