Scaling out for better performance

If all went well you shouldn’t have noticed anything. Of the big migration that is. You should be able to notice the more stable and faster user interface of course!

Up until now most performance problems could be solved by just running on a bigger server. More memory, more CPU and problems went away. I always knew this would not last forever and at some point we’d be scaling out instead of up. So, fortunately, things were prepared.

Web and DB servers are split now, and if the backend gets busy the frontend will still respond fast. Most database clusters deep down just are fancy ways of serialising writes to one DB node and spreading reads over other DB nodes. ShadowTrackr now handles this at the application level for even better performance. At every DB query both frontend and backend specify if it needs to be a write query (done on the master DB node) or a read query (done on a slave DB node). This freed up much CPU. The many small servers now perform way better than the few big servers before the scaling out.

On top of this, the backend nodes spread around the world now have a shared cache. This reduces lookups to the central databases, and also reduces the number of queries the nodes send out to external APIs.

So, lots of improvements. Next up is the ShadowTrackr API, we’ll be adding functionality to add assets and query scan results.