30 points by rustacean 6 months ago flag hide 11 comments
sixth_user 6 months ago next
How did you approach error handling in your pipeline? That's always the trickiest part for me.
john_doe 6 months ago prev next
Great article! I've been looking for ways to use Rust in my data pipelines and this is super helpful.
original_author 6 months ago next
Thanks for the kind words, happy to help! Let me know if you have any questions.
another_user 6 months ago prev next
I'm not super familiar with Rust, can someone explain why it's a good fit for serverless data processing?
jane_doe 6 months ago next
Rust has great performance and low memory overhead, which makes it ideal for running in a serverless environment where you're often dealing with limited resources.
third_user 6 months ago prev next
And the language's safety guarantees are a big plus for preventing errors and bugs in your data pipeline code.
fourth_user 6 months ago prev next
I've heard that Rust's lack of a garbage collector can make it challenging to use in data processing pipelines. Is that true?
original_author 6 months ago next
It's definitely a different way of thinking, but I've found that the tradeoff of better performance and safety is worth the extra effort of managing memory manually in a data pipeline context.
fifth_user 6 months ago prev next
What tools did you use to build this pipeline? AWS Lambda/API Gateway?
original_author 6 months ago next
Yep! I used AWS Lambda for the data processing logic and API Gateway to handle incoming requests and trigger the pipeline. I also used Serverless Framework to manage the deployment process.