A logistics company built an asset-tracking microservice by using the AWS Serverless Application Model (AWS SAM). One of the microservice’s AWS Lambda functions needs to import a large geospatial dataset from Amazon S3 before the function can process the requests. The import of the dataset requires significant time and is causing the function to take too long to finish running. The results are increased latency and cost. A developer needs to optimize the function to process requests faster with the least possible cost. Which solution will meet these requirements?

Topic #: - All AWS Certified Developer Associate Questions

A. Store the geospatial dataset on Amazon Elastic File System (Amazon EFS) instead of on Amazon S3. Attach the EFS file system to the function. Retrieve the dataset by accessing the file system for every invocation.
B. Store the geospatial dataset on Amazon Elastic File System (Amazon EFS) instead of on Amazon S3. Attach the EFS file system to the function. Cache the data in the /tmp directory for use with every invocation.
C. Declare the Amazon S3 SDK and object request outside of the function handler. Configure provisioned concurrency for the function.
D. Declare the Amazon S3 SDK and object request outside of the function handler. Increase memory capacity of the function to 1,769 MB.

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