Whitepaper 'FinOps and cost management for Kubernetes'
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Ebook 'From FinOps to proven cloud cost management & optimization strategies'
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OptScale — FinOps
FinOps overview
Cost optimization:
AWS
MS Azure
Google Cloud
Alibaba Cloud
Kubernetes
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OptScale — MLOps
ML/AI Profiling
ML/AI Optimization
Big Data Profiling
OPTSCALE PRICING
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Acura — Cloud migration
Overview
Database replatforming
Migration to:
AWS
MS Azure
Google Cloud
Alibaba Cloud
VMWare
OpenStack
KVM
Public Cloud
Migration from:
On-premise
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Acura — DR & cloud backup
Overview
Migration to:
AWS
MS Azure
Google Cloud
Alibaba Cloud
VMWare
OpenStack
KVM
Whitepaper

How-tos and best practices for FinOps, cloud cost optimization and security

The whitepaper is also available on the Amazon Marketplace →

No doubt that today there are a considerable number of companies whose activity is closely related to cloud technology, and this number is constantly growing.

However, it doesn’t come without its challenges. Keeping a hold on cloud consumption, security issues and having a true method in place to optimize cloud costs is harder than it looks.

In this whitepaper, we’ve compiled a set of How-tos, best practices for FinOps, cloud cost optimization and cloud security. 

Find our recommendations for AWS, Microsoft Azure and Alibaba Cloud:

  • How to release Elastic IPs on Amazon EC2
  • Reduce your AWS bill by eliminating orphaned and unused disk snapshots
  • 3 easy steps to find all inactive users in your AWS account for access management and security improvements
  • Detect incorrectly stopped MS Azure VMs
  • How to find and cleanup orphaned and unused snapshots in MS Azure and Alibaba Cloud
  • Step-by-step guide for tagging Alibaba cloud resources

And much more deep insights on FinOps adoption in your company.

To improve IT infrastructure usage learn more about OptScale, a FinOps and cloud cost management solution → free live demo.

 
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News & Reports

MLOps open source platform

A full description of OptScale as an MLOps open source platform.

Enhance the ML process in your company with OptScale capabilities, including

  • ML/AI Leaderboards
  • Experiment tracking
  • Hyperparameter tuning
  • Dataset and model versioning
  • Cloud cost optimization

How to use OptScale to optimize RI/SP usage for ML/AI teams

Find out how to: 

  • enhance RI/SP utilization by ML/AI teams with OptScale
  • see RI/SP coverage
  • get recommendations for optimal RI/SP usage

Why MLOps matters

Bridging the gap between Machine Learning and Operations, we’ll cover in this article:

  • The driving factors for MLOps
  • The overlapping issues between MLOps and DevOps
  • The unique challenges in MLOps compared to DevOps
  • The integral parts of an MLOps structure
cost optimization ML resource management

Free cloud cost optimization & enhanced ML/AI resource management for a lifetime

Nick Smirnov, CEO and Co-Founder

Nick Smirnov,
FinOps enthusiast & CEO at Hystax

About the author

Nick Smirnov is a FinOps and digital transformation enthusiast with more than 10 years of expertise working with public clouds and in enterprise software development. Nick is passionate about cloud adoption and is helping companies navigate cloud cost management more effectively.