With 50 million requests per month and hundreds of requests per second at peak hours, a lot of effort is being done to improve server performance and scalability, providing a continued real time experience for agents.
- Scalability: Central caching using Redis
- Server performance and stability improvements → Auto scale at a busy monday afternoon, down scale in slow weekends.
- In-depth monitoring using Sentry and StackDriver Trace Logging in GCP → Insights in what’s happening at server and application level to understand and improve performance
- Recommendation Studio redactions now load live and faster, with less impact on production server.
- Reduce server load by 'debouncing' autocomplete requests. Autocomplete skips irrelevant characters to reduce unnecessary requests to the recommendation engine.