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'

Advanced multi-cloud resource filtering for instant clean-up tasks

Filter, manage and optimize cloud usage with your engineers
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Cloud resource
optimization

Advanced multi-cloud
resource filtering

Smart resource
management

Filter and manage cloud resources in an automated way

Hystax OptScale provides your team with a unique opportunity to filter and manage all cloud resources such as volumes, VMs or snapshots across multiple cloud platforms and accounts.

Cloud resource optimization

Hystax OptScale assists teams to manage filtered resources in an automated way. You can find unutilized resources and clean them up effortlessly. Hystax OptScale supports AWS, Microsoft Azure, Alibaba, and all Kubernetes clusters.

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Advanced multi-cloud resource filtering

Hystax OptSсale enables you to filter all cloud resources in complex multi-cloud infrastructures, perform them in different geographical regions and accounts.

Multi-cloud resource filtering to simplify daily tasks and start FinOps adoption

Smart resource management

Advanced filtering helps to monitor, visualize and analyze cloud resources across multiple cloud platforms for proper management and full cloud transparency. Start your FinOps adoption process with OptScale.

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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