Cloud-Native ML+AI

  • Infinite scalability for model training in the cloud
  • Large-scale cloud-native data management
  • Faster workflows with cloud-native ML tools
  • Problem: Data engineers need access to Kubernetes

Local clusters are not powerful enough

  • Wide availability and comparably easy setup
  • No need to configure access to cloud platform
  • Burning laptops and loud fans due to high load
  • Very limited computing and storage capabilities
  • Admin effort for engineers to maintain their cluster
  • Cross-platform differences and config struggles

Solution: Shared Clusters for Experimentation

Giving developers access to shared clusters requires to solve many challenges. loft automates this process.

Self-Service Provisioning

  • On-demand namespace & vCluster creation
  • UI & CLI for managing users and account limits
  • Secure and automated user and workload isolation

70% Cost Savings via Sleep Mode

  • Puts inactive vClusters and namespaces to sleep
  • Wakes up sleeping spaces automatically
  • Best for clusters with horizontal auto-scaling

Works with any Kubernetes cluster

with Helm in less than 5 minutes

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