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General information about the ML Platform product

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Selectel ML Platform is a pre-configured infrastructure for implementing ML development processes, such as training and deploying ML models. The infrastructure consists of software and hardware components that are already set up and ready for use.

When selecting ML Platform components, all available cloud server configurations are used. After connecting the platform, its composition can be expanded with your own software components. Tested usage includes:

  • ClearML;
  • Kubeflow — for more details on installing Kubeflow, see the Install Kubeflow guide.

There are no additional restrictions on managing the ML Platform cluster from Selectel.

Platform components

By default, the ML Platform consists of:

  • hardware components:
    • cloud platform — a base for Managed Kubernetes with NVIDIA® GPUs (Tesla T4, A2, A30, A100, A2000, A5000, GTX 1080⁠, RTX 2080 Ti⁠);
  • software components:
    • Managed Kubernetes clusters with preconfiguration;
    • a domain for accessing the Managed Kubernetes cluster;
    • SSO Keycloak — authorization in internal platform services;
    • Prom Stack — monitoring of platform components;
    • Forecastle — the platform homepage;
    • S3 — storage for datasets and experiment data;
    • Container Registry — container image storage.

In Managed Kubernetes clusters:

  • drivers are installed;
  • nodes are annotated;
  • necessary GPU resources for computing are added;
  • the network is configured, including Traefik Kubernetes Ingress.

When installing the ClearML platform in a cluster, direct management is performed via an SDK installed in the user's own IDE. ClearML uses cluster nodes to run ML experiments. The ClearML architecture allows for various component configurations:

  • a single Managed Kubernetes cluster for all ML tasks;
  • several Managed Kubernetes clusters — each for its own task (Inference and Training);
  • connecting a dedicated server as a computational node for ML experiments.

Connect platform

  1. In the control panel, from the top menu, click Products and select ML Platform.
  2. Click Create a test request.
  3. Select the data type.
  4. Specify the data volume in GB or MB.
  5. Optional: to help us recommend suitable connection methods to the ML Platform, enter your data source. For example: Selectel, on-premise, or other cloud providers.
  6. Optional: to help us consider your specific data security requirements during the test, select the checkbox Additional data security requirements for the test. Describe the requirements in the Application comments field.
  7. Specify the model size in GB or MB.
  8. Specify the number of people who will use the platform simultaneously.
  9. Select the desired GPU model or check the No requirements for GPU model checkbox. GPU specifications can be viewed in the Available GPUs subsection of the Create a cloud server with GPU guide.
  10. Enter the contact information for a technical specialist. It is required to clarify the technical details of the testing.
  11. Optional: enter application comments. For example, specify your desired tools, components, or requirements for data security in the test.
  12. Click Submit application. A ticket with the ML Platform test request will be automatically created.
  13. Wait for a response from a Selectel employee in the ticket. They will contact you to clarify the details for setting up the ML Platform.

Cost

The cost of the ML Platform is calculated after the application is processed and the configuration is selected. It consists only of the cost of the platform components: Managed Kubernetes cluster, S3, and Container Registry.