Microservice architecture for ETL

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I am redesigning a small monolith ETL software written in Python. I find a microservice architecture suitable as it will give us the flexibility to use different technologies if needed (Python is not the nicest language for enterprise software in my opinion). So if we had three microservices (call them Extract, Transform, Load), we could use Java for Transform microservice in the future.

The problem is, it is not feasible here to pass the result of a service call in an API response (say HTTP). The output from Extract is going to be gigabytes of data.

One idea is to call Extract and have it store the results in a database (which is really what that module is doing in the monolith, so easy to implement). In this case, the service will return only a yes/no response (was the process successful or not).

I was wondering if there were a better way to approach this. What would be a better architecture? Is what I'm proposing reasonable?

restful-architecture microservices etl architecture web-services
4 Answers

I would suggest you to have a look into the Apache flink, It is very similar to what big sized enterprise apps like informatica, talend and data stage mappings but it process in a smaller scale but repetitively. It actually helps you to compute and transform the stuff on the fly/as they arrive and then store/load into a file/db.

The current infra we have with flink process close 28.5GB per every 4 hours and it just works. In the initial days, we had to run our daily batch and the flink stream to ensure both of them are producing consistent results and eventually most of the streams were left active and the daily batches were retired gradually. Hope it helps someone.

user_114603140

There's none preventing you to have an SFTP server containing CSV or database storing the results. You can do whatever make senses. Using messaging to pass gigabytes of data, or streaming through HTTP may or may not make senses for your case.

user_2632960
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