I still remember building an entire bookkeeping system in FoxPro for my university coursework back in 2007. Planning every table structure upfront, carefully designing indexes because adding them later meant locking everything up for a reindex, managing backups manually, worrying about file corruption. Every schema change was a small crisis.

It all began with a fairly normal data pipeline. Events were coming in through Kafka, landing in AWS S3 as Parquet files after going through some lightweight microbatch processing. It looked clean at first glance. Efficient. Predictable. But one day I opened one of the hourly folders and saw the

Working with dates in Argo Workflows can range from simple to unexpectedly challenging depending on your needs. Whether you're scheduling tasks, extracting specific parts of a date, or looping through hours for complex workflows there’s plenty you can achieve—but figuring it out might take some trial