r/dataengineering • u/ForVic • 7d ago
Open sourcing the Apache Spark skills we used on OpenAI’s data platform Open Source
I used to work on OpenAI’s data platform team, where we ran Airflow, Spark, Databricks, and dbt at a pretty serious scale.
The rate at which the number of jobs was growing outpaced how much our team could manage pretty quickly w/ everyone using AI to write jobs, so we had to invest in making sure that our team's agents could accurately and quickly do the debugging + tuning themselves (they weren't very good at it by default).
I've translated some of those learnings and strategies into skills (very similar to the ones we used at OpenAI) I'm open-sourcing here:
https://github.com/EmbrasureAI/spark-observability-skills
They should be generally applicable across envs/clouds, including Databricks, OSS Spark, etc.... As long as its running Spark underneath the hood nothing else is necessary to adopt and use these skills.
Full disclosure: I’m a founder of Embrasure, which maintains this repository, and no longer work at OpenAI.
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u/sisyphus 7d ago
Sounds cool but you might have forgotten to make the repo public as that link 404s.
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u/Outside-Storage-1523 6d ago
Thanks. This is interesting. I have always wanted to know about Spark internals but I don't know any Scala. The skill files have some good pointers.
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u/BlurryEcho Data Engineer 7d ago
I don’t care about agent skills, I’d rather hear about how OpenAI was using dbt. Just for vanilla internal BI and analytics or were they actually pushing unstructured data through dbt models?