How we scale Raygun's architecture to handle more data

How we scale Raygun's architecture to handle more data

We identified the sourcemapping process as an area that we could improve performance and improve Raygun’s architecture. Naturally, we took it apart to see what we could find.

Due to the huge importance of sourcemaps in the workflow of our customers, sourcemaps are a crucial part of our Crash Reporting offering.

We constantly strive to stay ahead of our customer demands as the amount of data we process continues to grow. We identified the sourcemapping process as an area ripe for performance improvement, so we took it apart and looked at exciting ways to build it from the ground-up using cutting-edge tech. Our key objectives were: horizontal scalabilityblazingly fast processing rates and easy monitorability.

A quick background of sourcemaps

Skip ahead_ if you’re familiar with JavaScript sourcemaps already._ 😀

Sourcemaps are an essential part of the JavaScript debugging process. A sourcemap is essentially a JSON file containing the instructions used to piece together JavaScript code which has been compressed (or minified) down for optimal performance. A major proportion of the total Crash Reports which Raygun processes are from JavaScript, and nearly all JavaScript running in production these days is compressed (commonly by a tool like UglifyJS).

This presents an interesting problem; if your production code is compressed, how are you going to know exactly where an error occurred when reading an error stacktrace? This is where our sourcemaps worker comes into play. It processes hundreds of millions of these compressed JavaScript files every month in order for customers to be able to easily debug their JS errors.

data analysis

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