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A company runs a data processing workflow that takes about 60 minutes to complete. The workflow can withstand disruptions and it can be started and stopped multiple times. Which is the most cost-effective solution to build a solution for the workflow?

a) Use an On-Demand EC2 instance for processing
b) Implement AWS Step Functions
c) Utilize AWS Lambda for processing
d) Employ AWS Batch for batch processing

User Moonkid
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1 Answer

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Final answer:

The most cost-effective solution would be to utilize AWS Lambda for processing. AWS Lambda is a serverless compute service that scales automatically and charges based on usage, making it a cost-effective choice for the described workflow.

Step-by-step explanation:

The most cost-effective solution to build a solution for the workflow described would be to utilize AWS Lambda for processing. AWS Lambda is a serverless compute service that allows you to run your code without provisioning or managing servers. It scales automatically based on the workload, ensuring that resources are used efficiently, and you only pay for the compute time consumed.

With AWS Lambda, you can create a function that processes the data and invoke it whenever needed. This means you only pay for the time it takes to process the data, rather than paying for a long-running instance or having to manage interruptions and restarts. Since the workflow can be started and stopped multiple times, AWS Lambda's pay-per-use pricing model makes it a cost-effective choice.

Additionally, AWS Lambda integrates well with other AWS services, allowing you to build a complete end-to-end solution for your data processing workflow.

User Sivasankar
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