2016 was a starting point for the multi-faceted story of Hystax – a company founded by a seasoned team of enthusiastic entrepreneurs, practitioners, and engineers who passionately got started to design a unique platform to help businesses choose an appropriate cloud and make it affordable and reliable.
And Hystax was born.
The time passed gradually, and the collaborative team realized that all their endeavors needed to be reinforced by a new killer feature of their platform that would make it flexible, more sophisticated, and sought after by R&D specialists in the digital transformation era.
More than ten years of cloud expertise have found a deep reflection in the promising FinOps and MLOps open source solution – Hystax OptScale, which helps businesses of all sizes optimize their cloud spend by starting or enhancing FinOps adoption at a company. Moreover, the OptScale solution aims to improve the efficiency of the ML process, allowing you to run ML/AI or any type of workload with optimal performance and infrastructure cost by profiling ML jobs, carrying out automated experiments, and analyzing cloud usage.
Access to the OptScale open source solution is granted to users by the Apache 2.0 license on our GitHub page. This enables Hystax to deliver the OptScale platform to a broader range of ML & Data engineers, cloud capacity managers, and FinOps enthusiasts.
At present, starting your migration journey to a cloud without understanding how much your cloud resources would cost, how to set budget constraints, how to forecast/monitor an IT infrastructure cost, and what scenario of cloud spending you will have would be unreasonable and even wasteful. We have considered that aspect and reinforced commonly used cloud migration, cross-cloud disaster recovery, and backup by FinOps/MLOps adoption and cost management so that cloud cost was no longer a concern for your R&D team.
Hystax believes that every company, via acceleration of FinOps adoption, will gain complete cloud cost transparency and optimization and achieve operational excellence. Considering the OptScale product as an MLOps platform, our mission is to help companies optimize the performance and cost of ML model training jobs and increase the number of experiments an ML engineer can run.
If you want to achieve your goals, help others achieve theirs