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

Recognized by Forrester as a leading cloud cost management solution


Trusted by


Boost your FinOps adoption

Seamlessly adopt FinOps at your organization or simply get an assessment of your current FinOps readiness

Certified FinOps solution

Hystax drives FinOps methodology and manages one of the most significant FinOps communities. OptScale helps companies implement FinOps principles by engaging engineering teams in cloud usage optimization and cost-saving processes. OptScale is designed to establish a long-term FinOps process by providing complete cloud cost transparency, improving resource utilization, identifying wastage, and providing countless cost optimization recommendations.

ML/AI profiling and optimization

Improve ML/AI model profiling process by getting optimal performance and cost-saving recommendations

MLOps capabilities to reach the best ML algorithm, model architecture, and parameters

With OptScale users get the tool with ML/AI-focused capabilities, which helps manage machine learning operations (MLOps) and make the processes across the ML lifecycle more efficient. OptScale provides ML/AI model training profiling, performance bottleneck detection, and optimization recommendations. The solution enables ML/AI engineers to run automated experiments based on datasets, and hyperparameter conditions within the defined infrastructure budget.

OptScale ML-AI Optimization

ML/AI model training tracking and profiling

With OptScale ML/AI and data engineering teams get an instrument for tracking and profiling ML/AI model training and other relevant tasks. OptScale collects inside and outside performance and model-specific metrics, which help give performance and cost optimization recommendations for ML/AI experiments or production tasks. OptScale improves ML/AI profiling process by getting optimal performance and helps reach the best outcome of ML/AI experiments. 

OptScale supports Apache Spark to make Spark ML/AI task profiling process more efficient and transparent.

Dozens of tangible optimization recommendations to improve ML/AI profiling process

OptScale provides full transparency across ML/AI tasks and ML/AI team performance, captures ML/AI metrics and KPI tracking, which help identify complex issues appearing in ML/AI training jobs. To improve the performance OptScale users get tangible recommendations such as utilizing Reserved/Spot instances and Saving Plans, rightsizing and instance family migration, detecting of CPU/IO, IOPS inconsistencies that can be caused by data transformations, effective usage of cross-regional traffic, avoiding Spark executors idle state, running comparison based on the segment duration. 

FinOps readiness and maturity assessment

OptScale enables companies to get an assessment of their current FinOps readiness and adoption state and provides a plethora of insightful recommendations on how to improve and accelerate FinOps implementation. OptScale analyzes connected cloud accounts, Kubernetes clusters, and engineering teams’ survey responses to generate a report with a detailed analysis of the IT infrastructure state, highlighted issues, recommendations, and next steps.

Optimize your cloud costs

Get complete cloud cost transparency, endless optimization scenarios, and engage engineers in cost-saving processes  

Free cloud and K8s cost optimization

OptScale assists companies in building efficient IT workload usage by providing free cost optimization for Kubernetes, AWS, MS Azure, Google Cloud Platform, and Alibaba workloads. The solution offers an abundance of optimization scenarios, anomaly detection, full IT cost transparency, in-depth cost analysis, budget allocation, and resource lifecycle management. OptScale monitors IT security issues and application behavior, identifies bottlenecks and wastage, recommends performance enhancements such as VM rightsizing, CI/CD job resource reflavoring and reducing cross-region traffic.

Cost anomaly detection

OptScale continuously observes cloud cost and resource utilization to identify anomalies and spikes. Real-time monitoring detects cost anomalies and allows companies to take action quickly in order to prevent unexpected expenses. Instantaneous alerts to resource owners enable the opportunity to avoid budget overruns, and to engage the engineering team in cost-saving processes, in which every team member is responsible only for the cloud resources they use.

Network traffic and cost geo map

Network traffic cost map shows accumulated expenses for paid network traffic between cloud regions and external services.

You can also leverage OptScale to track cloud costs of all your resources among different regions, identify potential risks, optimize cloud costs and gain complete visualization of your spending on the resource usage in AWS, MS Azure, GCP or Alibaba Cloud, or any Kubernetes cluster.

multi-account cost map for Kubernetes and traditional workloads


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.

Optimize cloud and Kubernetes costs and enhance IT infrastructure transparency

Cloud cost management

Get deep insights into IT infrastructure costs via a single dashboard and improve R&D process efficiency

IT environment management

Track IT resource usage, book and discover a simple way to acquire and release resources, and organize simultaneous shared access with OptScale. Our solution enables you to eliminate spreadsheets, chats and complicated tools to help easily identify R&D and test environment availability, and software versions deployed. Any distributed team can easily book clusters, VMs, or any other IT resources, and avoid all of the complexities of test environment utilization. OptScale delivers complete cost transparency across all IT environments and helps keep the R&D process costs down.


Multi-cloud cost management platform

Deep insights into actual VM utilization, consolidated data from dozens of cloud accounts, and various cloud or Kubernetes providers are easily accessible via a single OptScale dashboard. OptScale provides full cost transparency across AWS, MS Azure, GCP, Alibaba Cloud, and Kubernetes clusters. Granular visibility and one-click access to public clouds’ key resource metrics make it effortless to keep cloud costs under control.

Supported platforms

google cloud platform
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News & Reports

FinOps & Test Environment Management

A full description of OptScale as a FinOps and Test Environment Management platform to organize shared IT environment usage, optimize & forecast Kubernetes and cloud costs

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

Engage your engineers in FinOps and cloud cost savings

Discover how OptScale helps companies quickly increase FinOps adoption by engaging engineers in FinOps enablement and cloud cost savings