Hystax began its journey in 2016, founded by a team of experienced entrepreneurs, practitioners, and engineers. These passionate individuals set out to create a unique platform. They aimed to help businesses select an appropriate cloud and make it affordable and reliable. This marked the start of a multi-faceted story for Hystax.
And Hystax was born.
As time passed, the collaborative team realized something important. Their efforts needed reinforcement through a new, standout feature for their platform. This feature would make it more flexible, sophisticated, and highly desirable for R&D specialists. In the digital transformation era, it would become a key element of their success.
With over ten years of cloud expertise, Hystax OptScale has been developed as a promising FinOps and MLOps open source solution. This solution is designed to help businesses of all sizes optimize their cloud spending. It supports companies in starting or enhancing their FinOps adoption efforts. 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.
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