The outcome

Learn the interaction loop using a small task with a clear outcome.

DGX Cloud Lepton is a NVIDIA AI application and inference platform for Python Photons, containers, endpoints, jobs, and GPU resources. Turning Python model code into a Photon service, deploying a Photon or container as a GPU endpoint, and operating bounded AI jobs and inference workloads in a managed workspace. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define the service contract, users, model and code licenses, data class, resources, latency, concurrency, scaling, access, secrets, observability, cost, and rollback targets.

  2. 02

    Build the smallest Photon or pinned container locally, expose only typed handlers or the required port, and test inputs, outputs, errors, health, and dependency reproducibility.

  3. 03

    Push an immutable version, create a private test endpoint with scoped secrets, bounded replicas and resources, and capture logs, events, utilization, latency, failures, and spend under load.

  4. 04

    Canary a reviewed endpoint update rather than rerunning production in place, monitor it, preserve the previous version, and verify access revocation, teardown, storage deletion, and stopped billing.

Working standard

What good use looks like.

  • State the outcome before the background.
  • Provide the real source material.
  • Review the result before expanding the task.

Older material may call endpoints deployments and the product Lepton AI; current documentation uses NVIDIA DGX Cloud Lepton. A Photon simplifies packaging but does not remove responsibility for unsafe handlers, arbitrary code, dependency and model licenses, public exposure, secrets, logs, autoscaling, or GPU cost. Pin versions, use private access, isolate secrets, cap resources, and update with rollback.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.