Deka GPU Documentations
  • Starter Guide
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  • Deka GPU
    • Deka GPU: Kubernetes
      • Introduction
      • GPU Type
      • Dashboard
        • Check Status Kubernetes
        • Download Kube Config
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          • Create New Pod
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          • Create New Deployment
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          • How to Create a New Deployment use CLI
        • DaemonSets
          • Create a New DaemonSet
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      • Services
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        • Storage Class
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          • Create a New Persistent Volume Claim
          • How to Create a New Persistent Volume Claim use CLI
    • Deka GPU: VMs
      • Operating System
      • GPU Type
      • Machine Type
      • Namespace Type
      • Storage Class
      • How to Create a Virtual Machine on Service Portal
      • How to Manually Create a Virtual Machine
        • Download Kube Config
        • Running Kube Config
        • Configuration file dv.yaml
        • Configuration file vm.yaml
        • Configuration file svc.yaml
      • Feature Overview of Virtual Machine
        • Detail a Virtual Machine
        • Open Console
        • Turn Off a VM Instance
        • Turn On a VM Instance
        • Restart a Virtual Machine
        • How to Access Console
        • Show YAML File
      • Delete a Virtual Machine
    • Deka GPU: Registry
      • Create Registry
      • Quota
      • Detail Registry
        • Summary
        • Repository
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        • Tag Immutability
        • Member
        • Resize Storage Registry
      • Delete Registry
    • Deka GPU: Security
      • Deka Guard
        • Introduction
        • Create Guard to Deny All Ingress
        • Create Guard to Allow Ingress
        • Create Guard to Allow Ingress with port
        • Create Guard to Allow Ingress with IP/CIDR
        • Create Guard to Deny All Egress
        • Create Guard to Allow Egress
        • Create guard to Allow Egress with Port
        • Create Guard to Allow Egress with IP/CIDR
    • Deka GPU: Service
      • Ingress
        • Install Ingress nginx
        • Install Cert Manager
        • Create Cluster Issuer
        • Create Ingress with TLS
    • Deka GPU: Autoscaling
      • Basic Autoscaling
    • Deka GPU: Network
      • Deka VPC
    • Deka GPU: MLOps
      • Introduction
      • Notebook
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      • Volumes
      • Endpoints
        • Create Endpoint
        • Delete Endpoint
      • Experiments (AutoML)
        • Create Experiments (AutoML)
        • Create Experiments (AutoML) using Python SDK
        • Get Experiments Results
      • Experiments (KFP)
        • Create Experiment
      • Pipelines
      • Runs
        • Create Run
        • Delete Active Run
      • Recurring Runs
        • Create Recurring Run
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        • Home
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  • Deka LLM
    • Introduction
    • Check Project Type
    • Create a New LLM
    • Detail Deka LLM
      • Overview Tab
      • Keys Tab
        • Create a New Key
        • Detail a Key
        • Edit a Key
        • Get a Secret Key
        • Delete a Key
      • Usage Tab
      • Top Up Coin
    • API Deka LLM
      • Model Management
      • Completions
      • Embedding
    • Delete Deka LLM
    • How to Create Simple Prompt with Deka LLM
      • Create Deka LLM
      • Get URL API Deka LLM
      • Get Secret Key
      • Access API Deka LLM using Postman
      • Get Model
      • Post Chat Completions
  • Deka Notebook
    • Introduction
    • Namespace Type
    • Create a New Notebook
    • Detail Deka Notebook
      • Configuration Deka Notebook
      • Start Deka Notebook Service
      • Stop Deka Notebook Service
      • Get Token
      • Login Deka Notebook
      • Logout Deka Notebook
    • Delete Deka Notebook
  • Reference
    • How to use kubeconfig on Linux
    • How to use kubeconfig on Windows
    • Kubernetes Commands for Enhancing Security
    • How to add GPU in Kubernetes
    • How to Add GPU in VM
      • Download kubeconfig
      • Install kubectl
      • Add GPU
      • Install Driver NVIDIA
    • RAPIDS
      • How to Setup RAPIDS
      • How to make Custom Image
    • How to push image with Docker
    • Deployment LLaMA 3.1 70B with VLLM on Kubernetes
      • Getting the Hugging Face API Key
      • Requesting Access to the LLaMA Model
      • Connect Kubernetes on Computer
      • Create Namespace
      • Create PersistentVolumeClaim (PVC)
      • Create Secret for Hugging Face Token
      • Create Deployment
      • Create Service
      • Verify Deployment
      • Accessing the LLaMA Service
      • Troubleshooting
    • How to Get an API Key on NGC
    • Deployment LLM with Deka GPU + NIM
    • Deployment Deepseek R1 70B with VLLM on Deka GPU's Kubernetes
      • Prerequisites
      • Create Namespace
      • Create PersistentVolumeClaim (PVC)
      • Create Deployment
      • Create Service
      • Verify Deployment
      • Accessing the Deepsek Service
      • Troubleshooting
    • How to Upload and Download on FTP Web
  • Troubleshooting
    • Reinstall Driver NVIDIA on Linux
    • NVIDIA Driver Not Detected After Upgrade Kernel
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  1. Deka GPU
  2. Deka GPU: MLOps

Runs

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Last updated 4 months ago

The Runs menu execute a pipeline in the Service Portal Deka GPU. Each time a pipeline is executed, it is considered one run. On the Service Portal Cloudeka Deka MLOps, select the Runs menu.

In the Runs menu, there are several submenus along with their explanations as follows.

a. Active, serves to manage and monitor currently running or recently completed pipeline runs. This section provides essential functionalities to interact with ongoing experiments and evaluate their performance. The options available in the Active menu include.

  1. Refresh

    This option refreshes the list of active runs, ensuring that you have the most up-to-date information displayed.

  2. Archive

    This functionality allows you to archive runs that are no longer active, helping to keep your workspace organized by removing completed runs from the active list.

  3. Clone Run

    This option lets you duplicate an existing run, making it easier to rerun experiments with the same configuration without manually re-entering the details.

  4. Compare Runs

    This feature enables you to compare the results of different runs side by side, helping you analyze the performance and outcomes of various experiments effectively.

  5. Create Runs

    This feature allows you to initiate a new run of a pipeline. When you select "+ Create Run" you will be prompted to fill out necessary details, such as the pipeline to be used, run type (one-off or recurring), and any parameters required for the execution. This is the starting point for executing your machine learning workflows in Kubeflow Pipelines.

b. Archived, you will find only the Refresh option. The purpose of this option is to update the archived runs list, ensuring that any newly archived runs are visible. Since the archived runs are not actively running, there are no additional management options provided in this menu. The focus is on keeping the archived data current without cluttering the interface with unnecessary functionalities.

Runs Menu
Runs Menu
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