The Real Problem With Scaling DataWeave
MuleSoft is built to handle enterprise integrations — but most developers test with small payloads. Everything looks fine in dev, until one day a real file with 1 million records hits your flow. Suddenly, your worker crashes with an OutOfMemoryError, and the job fails halfway through.
The truth is, DataWeave by default works in-memory. That’s acceptable for small datasets, but in production, we often deal with: