Whitepaper 'FinOps and cost management for Kubernetes'
OptScale is fully available as an open source solution under Apache 2.0 on GitHub
Ebook 'From FinOps to proven cloud cost management & optimization strategies'

FinOps and MLOps open source platform

Run ML/AI or any type of workload with optimal performance and infrastructure cost
FinOps and MLOps open source

Trusted by

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We run a FinOps & MLOps community with 7,000+ members

OptScale is an open source solution with a unique mix of FinOps and MLOps capabilities,
which helps companies boost innovation and reduce cloud costs

OptScale is an open source solution with a unique mix of FinOps and MLOps capabilities, which helps companies boost innovation and reduce cloud costs

FinOps adoption

Certified FinOps solution with the best cloud cost optimization engine, providing rightsizing recommendations, Reserved Instances/Savings Plans, and dozens of other optimization scenarios.

Optimize cloud costs and gain complete visualization of your spending on resource usage in AWS, MS AzureGCP or Alibaba Cloud, or any Kubernetes cluster.

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MLOps-with-OptScale

MLOps capabilities

OptScale MLOps capabilities allow you to increase the number of experiments, reduce model training time and track your ML team’s progress.

The solution enables ML/AI engineers to run automated experiments based on datasets and hyperparameter conditions within the defined infrastructure budget.

Runsets to identify the most efficient ML/AI model training results

Run experiments in parallel with various input parameters like datasets, hyperparameters, and model versions.

Optscale launches experiments on the optimal cloud hardware and shows results with optimization recommendations and optimal cloud costs, utilizing different instance types and an efficient RI/SP strategy.

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Profiling and recommendation engine

Profile ML/AI or any type of application and get performance and cost optimization recommendations, which your ML and data engineers can easily execute.

OptScale profiles machine learning models and gives a deep analysis of metrics to identify bottlenecks and provide dozens of recommendations.

Integrations

OptScale quickly plugs into any tool chain, thanks to the support of Jira, Jenkins, Slack, GitLab and GitHub. Assign IT environments to any task using Jira. Сreate a simple schedule, plan and book IT environment within your R&D teams to avoid conflicts via Slack. Receive real-time notifications about IT environment availability, expired TTLs or cloud budget exceeds in a familiar interface. Export or update an IT environment and deployment information from your Jenkins pipelines.

Supported platforms

aws
google cloud platform
Alibaba Cloud Logo
Kubernetes
kubeflow
TensorFlow
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News & Reports

FinOps and MLOps

A full description of OptScale as a FinOps and MLOps open source platform to perform multi-scenario cloud cost optimization and ensure ML/AI profiling and optimization

FinOps, cloud cost optimization and security

Discover our best practices: 

  • How to release Elastic IPs on Amazon EC2
  • Detect incorrectly stopped MS Azure VMs
  • And much more deep insights

From FinOps to proven cloud cost management & optimization strategies

This ebook covers the implementation of basic FinOps principles to shed light on alternative ways of conducting cloud cost optimization