Metabit Trading is an AI-powered quantitative investment firm that builds their research platform on K8s. However, their computing platform often faces sudden tasks requiring scaling from 0 to 500 pods for the concurrent access of data from distributed storage systems. As these systems are rating-limited and slow, they significantly hamper training performance and limit compute scalability.

To tackle this, they used Fluid, a CNCF project, and JuiceFS to build an elastic distributed cache solution. In this session, experts from Metabit and Fluid will discuss how to achieve automatic scaling in production environments by creating an elastic cache cluster and using Prometheus to set up a strategy based on behavioral characteristics of cache usage, ultimately reaching 1000Gbps. They will also cover using Fluid with CronHPA for timed autoscaling to balance cost and performance while evaluating the performance and cost benefits of scaling, and present a demo showcasing the solution.