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Create Instance

Create Instance Demo

What are Instances (Nodes)​

Instances are ready-to-use, collaborative workspaces for AI/ML development.
Each Instances combines:

  • A container
  • JupyterLab (if included in selected image)
  • Common ML libraries

This allows your team to run Instances, Scripts, Datasets, and Model experiments without manual environment setup.

Quickstart​

  1. Log in to E2E networks.
  2. Create a Project (projects live in your private workspace).
  3. Inside the project, go to the section Instances (Nodes) → Create Instance.
  4. Pick an image (TIR Pre-built, Base OS, or Custom Images), choose CPU or GPU plan, name the instance, set required Configuration and Storage, choose Instance Pricing(Plans) and optionally enable SSH by selecting an SSH key.
  5. Click Create and open the Instance via JupyterLab (or SSH if enabled).

Instance Images​

Instances run on container images that serve as blueprints, bundling the necessary libraries, tools, and dependencies for each instances.

  • Pre-built — Ready to use images with ML libraries pre-installed
  • Base OS — Minimal OS, install everything manually
  • Custom Images — Use your own custom-built image (via E2E Container Registry)

💡 Start with a prebuilt image unless you require a custom environment.

Key Options You Should Know​

  • Enable SSH — add an SSH public key to access the Instance shell
note

To enable SSH, you must attach at least one Security Group with port 22 enabled.

  • Workspace path — the Instance’s workspace mounts at /home/jovyan.
    Use this path for persistent files. Files outside this path may be lost on restart because Instances are container-native.

  • Disk size — default 30 GB free storage; expandable up to 5 TB
    (raise a support ticket if you need >5 TB).

  • Local NVMe — available only on H100 plans at /mnt/local.
    High-speed but temporary — move critical data to /home/jovyan or the EOS bucket before shutdown

  • Plan & billing — choose hourly or committed.
    Committed plans often give discounts and may unlock local NVMe for certain GPU (currently H100)

Instance Lifecycle & Status​

  • Waiting — deploying on hardware.
  • Running — active; access via JupyterLab or SSH.
  • Stopped — not assigned to a machine; workspace remains and may incur storage charges.
  • Pending — inventory unavailable; node stays pending for 48–72 hours.
  • Expired — request not fulfilled after 72 hours.

Spot Instance​

A Spot Instance is a virtual instance that uses spare cloud compute capacity at significantly reduced costs compared to On-Demand pricing. Spot pricing fluctuates based on supply and demand for available capacity in each Availability Zone, making it a cost-effective option for flexible workloads.

Select spot plans

Important Warnings (must-read)​

⚠️ Persistence — use /home/jovyan for saving files. Anything outside this path may be lost on container restarts
⚠️ Local NVMe is ephemeral — move checkpoints/data off /mnt/local before shutdown
⚠️ SSH changes require a stop — If you forgot to add a key during instance creation, simply enable SSH Access and upload the key. To enable SSH, you must attach at least one Security Group.
⚠️ Deleting a node deletes its disk/workspace — back up anything you want to keep
⚠️ Pending → Expired — if inventory isn’t free, the request waits 48–72 hours (Pending) and expires after 72 hours

Quick Best Practices​

  • Start with a prebuilt Jupyter image for faster onboarding.
  • Keep project datasets mounted and versioned (move large data to EOS buckets).
  • Use committed plans for regular heavy workloads to optimised cost and access performance options.
  • Keep an SSH key backed up — it’s the recommended way to access the instance via shell.