Whitepapers

OptScale is an open source MLOps and FinOps platform that optimizes workload performance and cost

OptScale is available on GitHub or as a SaaS solution at https://my.optscale.com

OptScale MLOps and FinOps capabilities

MLOps capabilities

ML model leaderboards, the performance bottleneck identification, and optimization, bulk run of ML/AI experiments using Spot and Reserved Instances, experiment tracking

Utilizing the functionality, ML teams multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing the costs associated with the necessary cloud and infrastructure resources.

Complete cloud resource usage, cost transparency & optimization

With comprehensive cost analytics and the ability to detect unassigned/orphaned resources, OptScale helps companies identify optimization scenarios for cloud workloads/K8s clusters. OptScale offers hundreds of optimization recommendations, from VM rightsizing to PaaS services and abandoned buckets.

PaaS or any external service instrumentation

OptScale delivers integral insights into API call cost, performance, and output; supports metrics tracking, and facilitates cost-efficient performance optimization. It also efficiently manages cross-regional traffic and enables easy integration of additional services like S3, Redshift, and BigQuery for scalable operations.

OptScale integration with MLFlow

The smooth integration facilitates the management of model and experiment results throughout their entire lifecycle. This is achieved by enhancing and combining MLFlow user experience with MLOps and FinOps capabilities.

With OptScale, you can optimize ML experiment performance and cost and instrument any PaaS or external SaaS service.

Figure out the complete picture of S3, Redshift, BigQuery, Databricks, or Snowflake API calls, usage, and cost for your ML model training or data experiments.

Do some cloud integration, PaaS/SaaS service instrumentation, or any optimization recommendation need to be included? → OptScale is fully open source and built so that any engineering team can easily add a new module as a public pull request or for private usage.

Supported platforms

About us

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. The tool aims to find performance bottlenecks, optimize cloud spend and give a complete picture of utilized cloud resources and their usage details. The platform can be used as a SaaS or deployed from source code; it is optimized for ML/AI teams but works with any workload.

Contacts

Email: [email protected]
Phone: +1 628 251 1280
Address: 1250 Borregas Avenue Sunnyvale, CA 94089

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