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Amazon AWS Certified Developer - Associate Sample Questions (Q177-Q182):
NEW QUESTION # 177
When using the AWS Encryption SDK how does the developer keep track of the data encryption keys used to encrypt data?
- A. The data encryption key is stored m the user data for the EC2 instance.
- B. The developer must manually keep Hack of the data encryption keys used for each data object.
- C. The SDK stores the data encryption keys automaticity in Amazon S3.
- D. The SDK encrypts the data encryption key and stores it (encrypted) as part of the resumed ophertext.
Answer: D
Explanation:
This solution will meet the requirements by using AWS Encryption SDK, which is a client-side encryption library that enables developers to encrypt and decrypt data using data encryption keys that are protected by AWS Key Management Service (AWS KMS). The SDK encrypts the data encryption key with a customer master key (CMK) that is managed by AWS KMS, and stores it (encrypted) as part of the returned ciphertext.
The developer does not need to keep track of the data encryption keys used to encrypt data, as they are stored with the encrypted data and can be retrieved and decrypted by using AWS KMS when needed. Option A is not optimal because it will require manual tracking of the data encryption keys used for each data object, which is error-prone and inefficient. Option C is not optimal because it will store the data encryption keys automatically in Amazon S3, which is unnecessary and insecure as Amazon S3 is not designed for storing encryption keys. Option D is not optimal because it will store the data encryption key in the user data for the EC2 instance, which is also unnecessary and insecure as user data is not encrypted by default.
NEW QUESTION # 178
A company is using an AWS Lambda function to process records from an Amazon Kinesis data stream. The company recently observed slow processing of the records. A developer notices that the iterator age metric for the function is increasing and that the Lambda run duration is constantly above normal.
Which actions should the developer take to increase the processing speed? (Choose two.)
- A. Increase the timeout of the Lambda function.
- B. Decrease the number of shards of the Kinesis data stream.
- C. Increase the memory that is allocated to the Lambda function.
- D. Increase the number of shards of the Kinesis data stream.
- E. Decrease the timeout of the Lambda function.
Answer: C,D
Explanation:
Explanation
Increasing the number of shards of the Kinesis data stream will increase the throughput and parallelism of the data processing. Increasing the memory that is allocated to the Lambda function will also increase the CPU and network performance of the function, which will reduce the run duration and improve the processing speed. Option B is not correct because decreasing the timeout of the Lambda function will not affect the processing speed, but may cause some records to fail if they exceed the timeout limit. Option D is not correct because decreasing the number of shards of the Kinesis data stream will decrease the throughput and parallelism of the data processing, which will slow down the processing speed. Option E is not correct because increasing the timeout of the Lambda function will not affect the processing speed, but may increase the cost of running the function.
References: [Amazon Kinesis Data Streams Scaling], [AWS Lambda Performance Tuning]
NEW QUESTION # 179
A developer is building a serverless application that runs on AWS. The developer wants to create an accelerated development workflow that deploys incremental changes to AWS for testing. The developer wants to deploy the incremental changes but does not want to fully deploy the entire application to AWS for every code commit.
What should the developer do to meet these requirements?
- A. Use the AWS Cloud Development Kit (AWS CDK) to build the application. Use the cdk bootstrap command to deploy the incremental changes.
- B. Use the AWS Serverless Application Model (AWS SAM) to build the application. Use the sam sync command to deploy the incremental changes.
- C. Use the AWS Serverless Application Model (AWS SAM) to build the application. Use the sam init command to deploy the incremental changes.
- D. Use the AWS Cloud Development Kit (AWS CDK) to build the application. Use the cdk synth command to deploy the incremental changes.
Answer: B
NEW QUESTION # 180
An ecommerce website uses an AWS Lambda function and an Amazon RDS for MySQL database for an order fulfillment service. The service needs to return order confirmation immediately.
During a marketing campaign that caused an increase in the number of orders, the website's operations team noticed errors for "too many connections" from Amazon RDS. However, the RDS DB cluster metrics are healthy. CPU and memory capacity are still available.
What should a developer do to resolve the errors?
- A. Use Amazon Simple Queue Service (Amazon SQS) FIFO queues to queue the orders. Ingest the orders into the database. Set the Lambda function's concurrency to a value that equals the number of available database connections.
- B. Initialize the database connection outside the handler function. Use RDS Proxy instead of connecting directly to the DB cluster.
- C. Use Amazon Simple Queue Service (Amazon SQS) FIFO queues to queue the orders. Ingest the orders into the database. Set the Lambda function's concurrency to a value that is less than the number of available database connections.
- D. Initialize the database connection outside the handler function. Increase the max_user_connections value on the parameter group of the DB cluster. Restart the DB cluster.
Answer: B
Explanation:
https://aws.amazon.com/blogs/compute/using-amazon-rds-proxy-with-aws-lambda/
NEW QUESTION # 181
A company uses more than 100 AWS Lambda functions to handle application services. One Lambda function is critical and must always run successfully. The company notices that occasionally, the critical Lambda function does not initiate. The company investigates the issue and discovers instances of the Lambda TooManyRequestsException: Rate Exceeded error in Amazon CloudWatch logs. Upon further review of the logs, the company notices that some of the non-critical functions run properly while the critical function fails. A developer must resolve the errors and ensure that the critical Lambda function runs successfully. Which solution will meet these requirements with the LEAST operational overhead?
- A. Configure provisioned concurrency for the critical Lambda function. Set provisioned concurrent executions to the appropriate level.
- B. Configure reserved concurrency for the critical Lambda function. Set reserved concurrent executions to the appropriate level.
- C. Configure CloudWatch alarms for TooManyRequestsException errors. Add the critical Lambda function as an alarm state change action to invoke the critical function again after a failure.
- D. Configure CloudWatch alarms for TooManyRequestsException errors. Add Amazon EventBridge as an action for the alarm state change. Use EventBridge to invoke the critical function again after a failure.
Answer: B
Explanation:
Reserved concurrency guarantees a specific number of concurrent executions for a critical Lambda function. This ensures that the critical function always has sufficient resources to execute, even if other functions are consuming concurrency.
Why Option A:
Ensures Function Availability: Reserved concurrency isolates the critical Lambda function from other functions.
Low Overhead: Configuring reserved concurrency is straightforward and requires minimal setup.
Why Not Other Options:
Option B: Provisioned concurrency is ideal for reducing cold starts, not for managing execution limits.
Option C & D: Alarms and re-invocation mechanisms add complexity without resolving the root cause.
Reference:
Managing Concurrency for AWS Lambda
NEW QUESTION # 182
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