About this event
The issue of how to implement FinOps methodology, manage ML/AI processes efficiently, and continuously optimize workload performance and cost is becoming increasingly important due to the lack of visibility and the growing trend of cloud waste in terms of the latest statistics.
Join us to discover what is the difference between FinOps and Cloud Cost Management, which saving recommendations have the biggest impact, how to avoid bill shocks and the ways how MLOps helps to increase the efficiency of ML experiments.
Edwin-Alexander Kuss, Director of Global Sales at Hystax, will show you how OptScale, an open source FinOps and MLOps platform, can be used for:
- Providing complete cloud resource usage and cost transparency
- Delivering cost & performance optimization recommendations
- Anomaly detection and extensive functionality to avoid budget overruns
- Getting lots of MLOps capabilities like ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments using Spot and Reserved Instances, experiment tracking
OptScale allows running ML/AI or any type of workload with optimal performance and infrastructure cost.
During our 45-min Hystax OptScale group demo, you’ll learn how with OptScale users can:
- Track cloud instance usage
- Instrument any PaaS or external SaaS service
- Control performance, and cost for every application or ML/AI experiment at a single pane of glass
We will also schedule some time for a Q&A session to ensure we answer all of your questions.
Looking forward to e-meeting you there!
Hystax
Hystax develops OptScale, an MLOps & FinOps open source platform, that optimizes performance and IT infrastructure cost by analyzing cloud usage, profiling and instrumentation of applications, ML/AI tasks, and cloud PaaS services, and delivering tangible optimization recommendations.
