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July

Info

GPU PaaS releases are initially rolled out via Rafay's Air Gapped Controller form factor. These will be periodically bundled and rolled out into Rafay's Production SaaS.

v3.1-July

xx July, 2025

Email Notifications

Cloud Provider administrators can now configure email providers for user notifications. SMTP and SendGrid are the currently supported providers. When enabled, end users will automatically receive notifications for scenarios such as the following:

  • Temporary password for new users
  • Password reset workflows
  • Self service sign up of new orgs, etc

Email Notifications

Schedules

Schedules allows for automated start/stop/custom actions on resources based on cron expressions and time zone. Schedules can be defined at various levels:

  1. Project Tags
  2. Compute/Service Profile Spec
  3. Instance / Service Spec

Example 1

A good example for a use case for this is "Time-Sharing Limited GPU Resources Across Teams". For example, consider an enterprise that has a limited pool of high-end GPUs (e.g., A100s or H100s) that must be shared among multiple internal teams (e.g., research, inference, and training teams). To prevent resource contention and ensure fair access, teams are assigned non-overlapping usage windows.

How Schedules Help:

  • Research team: 8:00 AM – 12:00 PM IST
  • Training team: 12:30 PM – 4:30 PM IST
  • Inference team: 5:00 PM – 9:00 PM IST

Benefits:

  1. Enables fair and scheduled GPU sharing
  2. Prevents one team from monopolizing resources
  3. Automates transitions and avoids manual intervention
  4. Scales easily across projects using profile-level or tag-based schedules

Example 2

Shift-Left Provisioning for Slow-Starting Workloads

Some environments—such as GPU-backed training clusters, large LLM inference stacks, or complex data pipelines—can take 10–30 minutes to provision and become operational. Users expect these environments to be ready when they log in, not wait for deployment delays. This is particularly impactful in education, enterprise R&D, or MLOps platforms, where slow-starting resources can derail daily workflows or testing cycles.

Use a “start” schedule to pre-warm or provision environments in advance of expected usage windows. For example,

  • Environment scheduled to start at 7:30 AM IST
  • Users typically log in by 8:00 AM IST
  • Auto-stop schedules to shut down idle environments post-work hours.

Benefits:

  1. Eliminates cold-start delays for time-sensitive teams
  2. Improves user experience for researchers, analysts, or students
  3. Ensures readiness without manual intervention
  4. Optimizes resource scheduling across dependent systems (e.g., inference + storage + UI)

Container Deployment Wizard

End users can use Rafay's wizard type workflow to deploy their container images to the Kubernetes cluster or virtual cluster based compute instances without having to write a single line of Kubernetes YAML. Based on the user's inputs, Rafay will automatically generate a deployment YAML specification and deploy it to an isolated namespace in the shared/tenant specific cluster.