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NEW QUESTION # 694
An application is processing clickstream data using Amazon Kinesis. The clickstream data feed into Kinesis experiences periodic spikes. The PutRecords API call occasionally fails and the logs show that the failed call returns the response shown below:
Which techniques will help mitigate this exception? (Choose two.)
Answer: A,E
Explanation:
Explanation
The response from the API call indicates that the ProvisionedThroughputExceededException exception has occurred. This exception means that the rate of incoming requests exceeds the throughput limit for one or more shards in a stream. To mitigate this exception, the developer can use one or more of the following techniques:
Implement retries with exponential backoff. This will introduce randomness in the retry intervals and avoid overwhelming the shards with retries.
Reduce the frequency and/or size of the requests. This will reduce the load on the shards and avoid throttling errors.
Increase the number of shards in the stream. This will increase the throughput capacity of the stream and accommodate higher request rates.
Use a PutRecord API instead of PutRecords. This will reduce the number of records per request and avoid exceeding the payload limit.
References:
[ProvisionedThroughputExceededException - Amazon Kinesis Data Streams Service API Reference]
[Best Practices for Handling Kinesis Data Streams Errors]
NEW QUESTION # 695
A developer is using AWS CloudFormation to deploy an AWS Lambda function. The developer needs to set the Lambda function's timeout value based on the environment parameter of the template. The template contains mappings of EnvironmentData for each environment's timeout value. The environment parameter and EnvironmentData mappings are as follows:
Environment parameter:
EnvironmentData mappings:
Which statement will meet these requirements?
Answer: C
NEW QUESTION # 696
A company requires that all applications running on Amazon EC2 use 1AM roles to gam access to AWS services. A developer is modifying an application that currently relies on 1AM user access keys stored in environment variables to access Amazon DynamoDB tables using boto, the AWS SDK for Python.
The developer associated a role with the same permissions as the 1AM user to the EC2 instance, then deleted the 1AM user. When the application was restarted, the AWS Access Denied Exception messages started appearing in the application logs. The developer was able to use their personal account on the server to run DynamoDB API commands using the AWS CLI.
What is the MOST likely cause of the exception?
Answer: A
NEW QUESTION # 697
A developer is building an application that consists of many AWS Lambda functions. The Lambda functions connect to a single Amazon RDS database.
The developer needs to implement a solution to store the database credentials securely. When the credentials are updated, the Lambda functions must be able to use the new credentials without requiring a code update or a configuration update.
Which solution will meet these requirements?
Answer: D
Explanation:
AWS Secrets Manager is specifically designed to securely store and manage sensitive information, such as database credentials. You can store the credentials as a secret and access them dynamically at runtime from within your Lambda functions. Secrets Manager also supports automatic rotation of secrets, so when the credentials are updated, the Lambda functions can access the updated credentials without needing a code or configuration update. This is the best solution for managing credentials securely and allowing Lambda functions to access them with minimal operational overhead.
NEW QUESTION # 698
A company needs to harden its container images before the images are in a running state. The company's application uses Amazon Elastic Container Registry (Amazon ECR) as an image registry. Amazon Elastic Kubernetes Service (Amazon EKS) for compute, and an AWS CodePipeline pipeline that orchestrates a continuous integration and continuous delivery (CI/CD) workflow. Dynamic application security testing occurs in the final stage of the pipeline after a new image is deployed to a development namespace in the EKS cluster. A developer needs to place an analysis stage before this deployment to analyze the container image earlier in the CI/CD pipeline. Which solution will meet these requirements with the MOST operational efficiency?
Answer: D
Explanation:
https://docs.aws.amazon.com/AmazonECR/latest/userguide/image-scanning-basic.html The below blog post refers to the solution using Amazon Inspector and ECS, but the architecture is almost same as required in this scenario. The built in image scanning in Amazon ECR provides a simpler solution.
https://aws.amazon.com/blogs/security/use-amazon-inspector-to-manage-your-build-and-deploy- pipelines-for-containerized-applications/
NEW QUESTION # 699
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