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Manage an H2O Engine

This guide covers all aspects of managing your H2O Engine through the H2O AI Cloud interface.

Overview​

Once you've created an H2O Engine, you can perform various management operations:

  • Access the Engine: Launch and interact with your H2O instance
  • Control Engine State: Terminate and manage engine lifecycle
  • Monitor Operations: View logs and track engine performance
  • View Configuration: Access detailed engine specifications and settings
  • Manage Resources: Update engine configurations as needed
  • Clean Up: Delete engines when no longer needed

Access Your H2O Engine​

Step 1: Navigate to AI Engines​

  1. From the H2O AI Cloud dashboard, click AI Engines in the left navigation.
  2. Locate your H2O Engine in the engines list.

Step 2: Launch the Engine​

  1. Click Visit to launch the H2O Engine interface.

Visit H2O Engine

This opens the H2O-3 home page in a new web browser window where you can:

  • Upload and prepare your datasets
  • Build machine learning models using H2O algorithms
  • Perform data analysis and visualization
  • Export models for deployment
  • Use H2O's AutoML capabilities
Getting Started with H2O

For detailed guidance on building models using H2O, see the H2O-3 documentation.

Control Engine State​

Terminate an H2O Engine​

Terminating an H2O engine stops all operations and deallocates resources to help optimize costs when the engine is not actively being used.

Step 1: Initiate Termination​

  1. From the AI Engines list, locate your running H2O Engine.
  2. Select Terminate to initiate the termination operation.

Terminate H2O Engine

Step 2: Confirm Termination Operation​

  1. Review the termination confirmation dialog.
  2. Click Terminate to confirm the engine termination operation.

Confirm H2O Engine Termination

Important Considerations
  • Running jobs: All active machine learning experiments and data processing jobs will be terminated
  • Data loss: Your data and model artifacts are deleted when the engine terminates (H2O engines are stateless)
  • Manual recreation: You'll need to recreate your experiments and models when starting a new engine
  • Cost optimization: Terminating reduces computational costs but does not preserve your work
Termination vs Deletion

Termination removes the engine state and deallocates all resources. Only the database record remains.

Deletion permanently removes the engine and all associated data, including the database record. This action cannot be undone.

Monitor Engine Operations​

View Engine Logs​

AI Engine logs provide valuable insights into engine operations, errors, and performance metrics.

Step 1: Access Logs​

  1. From the AI Engines list, locate your H2O Engine.
  2. Click the Actions dropdown menu.
  3. Select Logs to view the engine logs.

Read Logs

Log Management Features​

The logs interface provides options to Download complete log files for offline analysis.

View Engine Configuration​

Access Engine Details​

View detailed information about your H2O Engine configuration and status.

Step 1: Open Details View​

  1. From the AI Engines list, locate your H2O Engine.
  2. Click the Actions dropdown menu.
  3. Select View Details to access the engine information.

View Details Button

Engine Details Overview​

The Engine Details tab displays comprehensive information about your engine:

View Details of H2O Engine

FieldDescription
Instance NameThe display name of your engine instance
Engine IDThe unique identifier for the engine
Engine UIDThe unique universal identifier (with copy-to-clipboard button)
ProfileThe engine profile configuration (e.g., "default")
AI EngineThe type of AI engine (H2O) displayed in a tag
OwnerEmail address of the engine creator/owner
VersionThe H2O version running on the engine
Number of NodesNumber of H2O nodes for distributed processing
CPUs per NodeNumber of CPU units allocated per node
GPUs per NodeNumber of GPU units allocated per node
Memory per Node (GiB)Amount of memory allocated per node in gigabytes
Max Idle Time (Hrs)Maximum idle time before automatic termination
Max Uptime (Hrs)Maximum uptime before automatic termination
Created AtDate and time when the engine was created (ISO format)

Additional Configuration Sections​

The Engine Details tab view also includes three expandable sections:

Last Used Profile Info​

  • Detailed profile configuration information including:
    • Profile display name and internal name
    • Enablement status and priority
    • OIDC role assignments
    • Resource constraints (CPU, GPU, Memory, Node Count limits)
    • Timeout configurations (Idle and Running duration limits)
    • Additional settings like Java classpath, Java options, and H2O options
    • GPU Resource Name
    • Yaml Pod Template Specification and GPU tolerations

Engine Version Info​

  • Version-specific details including:
    • Version name and aliases
    • Deprecation status
    • Docker image information with copy functionality
    • Image pull policy and secrets
    • Creation metadata (creator and date)

Delete an H2O Engine​

Deleting an engine permanently removes it and all associated data. This action cannot be undone.

Permanent Deletion

Warning: Deleting an H2O Engine will permanently remove:

  • All engine configurations and settings
  • All datasets and model artifacts
  • All experiment history and results
  • All logs and audit information

Ensure you have backed up any important data before proceeding.

Step 1: Initiate Deletion​

  1. From the AI Engines list, locate your H2O Engine.
  2. Click the Actions dropdown menu.
  3. Select Delete to initiate the deletion process.

Delete H2O Engine

Step 2: Confirm Deletion​

  1. Verify you have backed up any important data.
  2. Click Delete to confirm the engine deletion.

Confirm H2O Engine Deletion

Post-Deletion
  • The engine will be removed from your AI Engines list
  • All associated resources will be deallocated
  • Storage costs will be eliminated immediately
  • The engine ID will be available for reuse
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