OptScale helps companies implement FinOps principles by engaging engineering teams in cloud optimization and cost-saving processes. With OptScale team members share the ownership and responsibility for the cloud resources that they use.
ML/AI and Data engineering teams get a tool for tracking and profiling ML/AI model training. OptScale collects inside/outside performance and model-specific metrics, which help give performance and cost optimization tips for ML/AI experiments or production tasks.
Comprehensive cost analytics enable companies to identify the best optimization scenarios for their cloud workloads and К8s clusters. OptScale offers hundreds of insightful optimization recommendations, from VM rightsizing to PaaS services and abandoned buckets.
OptScale enables obtaining the complete visualization of the company’s spending on the resource usage in AWS, MS Azure or Alibaba Cloud regions and moreover shows accumulated expenses for paid network traffic between cloud regions and external services.
OptScale continuously observes cloud cost and resource utilization to identify anomalies and spikes. The solution offers resource lifecycle management with TTL rules and over-budget constraints, and instantaneous alerts to resource owners to avoid budget overruns.
Track IT resource usage, book, release test environments, and simplify simultaneously shared access with OptScale. The solution helps easily identify R&D and IT environment availability, and software versions deployed.
Supported platforms
Hystax, the leading MLOps and FinOps solution provider has been developing its flagship product, OptScale, which allows running ML/AI or any type of workload with optimal performance and infrastructure cost by profiling ML jobs, running automated experiments, and analyzing cloud usage. Access to the OptScale open source solution is granted to users by the Apache 2.0 license. This enables Hystax to deliver the OptScale platform to a wider range of ML & Data engineers, cloud capacity managers, and FinOps enthusiasts.
The mission of Hystax is to help businesses optimize the performance and cost of ML model training jobs and increase the number of experiments an ML engineer can run.
The solutions of Hystax are currently the choice for such iconic brands as PwC, Ives Rocher, Nokia, DHL, and Airbus for its FinOps/MLOps adoption, offering them a platform that provides countless optimization recommendations and complete cloud cost visibility/control over Kubernetes, AWS, Microsoft Azure, Google Cloud Platform and Alibaba Cloud costs. The company was founded in 2016 and has customers in 48 countries.
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