Martin Larizzate – Optimizing Payload Logging in DataWeave
When working with MuleSoft and DataWeave, logging payloads is an essential part of debugging and monitoring data flows. However, a common issue arises when payloads are too long, causing loggers to cut them off or display them in a format that’s hard to read. This can make tracking down issues and analyzing logs far more tedious, especially with complex, nested data structures.
<logger level="DEBUG" doc:name="Log Original Payload" doc:id="671f0420-cdfe-4ebd-b78e-6c73214f8f18" message='#[%dw 2.0 output application/java --- "Received Payload: " ++ write(payload, "application/json", {indent: false})]' />One simple yet effective innovation is to leverage the indent:false option in DataWeave’s write() function. This small adjustment has a big impact on how payloads are logged, ensuring they are displayed in a single line without unnecessary line breaks. Here’s how it works:
%dw 2.0
output application/java
---
"Received Payload: " ++ write(payload, "application/json", {indent: false})Why Use indent:false?
In typical scenarios, logging a payload directly results in a pretty-printed JSON structure with multiple lines and indentations. While this is great for readability in some cases, it becomes a problem when payloads are large. Many loggers are configured to truncate lengthy entries, cutting off critical information, making it harder to trace issues effectively.
By using indent:false, you compact the entire payload into a single line, minimizing the chance of it being cut off by the logger. This ensures that the full payload is captured, even when dealing with large or deeply nested data. It enhances readability and provides a much cleaner, more manageable logging experience.
Improving the Developer Experience
This approach not only preserves payload integrity but also simplifies the review process by reducing noise in logs. Developers can quickly scan through log entries, improving debugging speed and efficiency. This small DataWeave enhancement ensures you get the best out of your logs, no matter how large your payloads are.
Wrote By:
_- Martin Larizzate -_ Mulesoft Certified Developer, Salesforce Ranger and Salesforce Solution Architect
