From 7149c14228d346561f8b1118d7cec889890b5884 Mon Sep 17 00:00:00 2001 From: Sarah Charlotte Johnson Date: Wed, 10 Apr 2024 14:19:37 -0700 Subject: [PATCH] Add blog post link to README.md (#27) --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index e64877c..758d739 100644 --- a/README.md +++ b/README.md @@ -2,6 +2,8 @@ **This repository is a lightweight scalable example pipeline that runs large Python jobs on a schedule in the cloud. We hope this example is easy to copy and modify for your own needs.** +Learn more in our [blog post](https://docs.coiled.io/blog/easy-scalable-production-etl.html?utm_source=github&utm_medium=etl). + ## Background It’s common to run regular large-scale Python jobs on the cloud as part of production data pipelines. Modern workflow orchestration systems like Prefect, Dagster, Airflow, Argo, etc. all work well for running jobs on a regular cadence, but we often see groups struggle with complexity around cloud infrastructure and lack of scalability.