Hey PH 👋 Built this because I kept seeing the same pattern on every data team I worked with: someone senior ‘just knows’ a job’s OOM-ing because memory’s sized for last quarter’s data volume, or that shuffle partitions are way overcounted — and that knowledge lives in one person’s head, not anywhere checkable. opti-pipe makes that pattern-matching explicit: 7 threshold rules, each fully auditable You can see exactly why a recommendation fired. Nothing ML/black-box, and nothing auto-applies — you approve or you don’t. Try the live demo (no signup): opti-pipe.onrender.com. Would genuinely love feedback, especially ‘this rule is wrong’ — that’s the fastest way I improve it.” Let me know once it’s live and I can help draft replies to early comments if you want.

opti-pipe

Stop guessing Spark/dbt config values

Stop guessing Spark/dbt config values