MLOps Dashboard

Improve visibility and increase GPU/CPU utilization by up to 80% with advanced resource management

Improve compute visibility across all ML runs

  • Give IT/DevOps full snapshot of GPU/CPU and Memory allocation and utilization data in one place
  • Monitor and compare real time allocation vs. utilization vs. capacity or resources
  • Track all active jobs and clusters with info about user, project, container, allocation & utilization
  • Create visibility into computational debt with utilization and allocation graphs

Increase GPU/CPU and memory utilization by up to 80%

  • Improve ROI of ML projects with advanced resource management
  • Build a more effective resource management structure with compute templates
  • Create custom compute templates for specific ML jobs
  • Compare allocation per job with utilization to identify computational debt

Identify workload bottlenecks and improve ROI of ML projects

  • Improve productivity with optimized compute allocation 
  • Prioritize jobs to maximize productivity and GPU/CPU utilization
  • Analyze runs by job, user, and container for improved monitoring
  • Avoid wasting resources with the misallocation of resources

Forecast future GPU/CPU consumption needs

  • Analyze historical consumption metrics for improved forecasting and reporting
  • Connect and export consumption metrics with any external data analytics platforms
  • Set up chargeback for IT to control project and user budgets 
  • Improve reporting of utilization, allocation and capacity for ML projects
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