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docs/getting_started/project_progress.md
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docs/getting_started/project_progress.md
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---
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title: Monitoring Project Progress
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---
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ClearML provides a comprehensive set of monitoring tools to help effectively track and manage machine learning projects.
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These tools offer both high-level overviews and detailed insights into task execution, resource
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utilization, and project performance.
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## Offerings
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### Project Dashboard
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:::info Pro Plan Offering
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The Project Dashboard app is available under the ClearML Pro plan.
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:::
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The [**Project Dashboard**](../webapp/applications/apps_dashboard.md) UI application provides a centralized
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view of project progress, task statuses, resource usage, and key performance metrics. It offers:
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* Comprehensive insights:
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* Track task statuses and trends over time.
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* Monitor GPU utilization and worker activity.
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* Analyze performance metrics.
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* Proactive alerts - By integrating with Slack, the Dashboard can notify teams of task failures
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and completions.
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For more information, see [Project Dashboard](../webapp/applications/apps_dashboard.md).
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### Project Overview
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A project's **OVERVIEW** tab in the UI presents a general picture of a project:
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* Metric Snapshot – A graphical representation of selected metric values across project tasks, offering a quick assessment of progress.
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* Task Status Tracking – When a single metric variant is selected for the snapshot, task status is color-coded (e.g.,
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Completed, Aborted, Published, Failed) for better visibility.
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Use the Metric Snapshot to track project progress and identify trends in task performance.
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For more information, see [Project Overview](../webapp/webapp_project_overview.md).
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docs/getting_started/task_trigger_schedule.md
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docs/getting_started/task_trigger_schedule.md
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---
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title: Scheduling and Triggering Task Execution
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---
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In ClearML, tasks can be scheduled and triggered automatically, enabling seamless workflow automation. This section
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provides an overview of the mechanisms available for managing task scheduling and event-based
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triggering.
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## Task Scheduling
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Task scheduling allows users to define one-shot or periodic executions at specified times and intervals. This
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is useful for:
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* Running routine operations such as periodic model training, evaluation jobs, backups, and reports.
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* Automating data ingestion and preprocessing workflows.
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* Ensuring regular execution of monitoring and reporting tasks.
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ClearML's offers the following scheduling solutions:
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* [**UI Application**](../webapp/applications/apps_task_scheduler.md) (available under the Enterprise Plan) - The **Task Scheduler** app
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provides a simple no-code interface for managing task schedules.
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* [**Python Interface**](../references/sdk/scheduler.md) - Use the `TaskScheduler` class to programmatically manage
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task schedules.
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## Task Execution Triggering
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ClearML's trigger manager enables you to automate task execution based on event occurence in the ClearML system, such as:
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* Changes in task status (e.g. running, completed, etc.)
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* Publication, archiving, or tagging of tasks, models, or datasets
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* Task metrics crossing predefined thresholds
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This is useful for:
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* Triggering a training task when a dataset has been tagged as `latest` or any other tag
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* Running an inference task when a model has been published
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* Retraining a model when accuracy falls below a certain threshold
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* And more
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ClearML's offers the following trigger management solutions:
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* [**UI Application**](../webapp/applications/apps_trigger_manager.md) (available under the Enterprise Plan) - The **Trigger Manager** app
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provides a simple no-code interface for managing task triggers .
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* [**Python Interface**](../references/sdk/trigger.md) - Use the `TriggerScheduler` class to programmatically manage
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task triggers.
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@ -95,13 +95,8 @@ module.exports = {
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{type: 'ref', id: 'webapp/applications/apps_gradio'},
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{type: 'ref', id: 'webapp/applications/apps_streamlit'},
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]},
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{"Automating Task Execution": [
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{type: 'ref', id: 'webapp/applications/apps_task_scheduler'},
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{type: 'ref', id: 'webapp/applications/apps_trigger_manager'},
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]},
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{"Monitoring Project Progress": [
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{type: 'ref', id: 'webapp/applications/apps_dashboard'},
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]},
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'getting_started/task_trigger_schedule',
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'getting_started/project_progress',
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],
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integrationsSidebar: [
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{
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@ -46,7 +46,7 @@ html {
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--ifm-code-padding-vertical: 0.2rem;
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}
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html[data-theme="dark"] {
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[data-theme=dark]:root {
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--ifm-background-color: #040506; /* body bg */
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--ifm-header-background-color: #101418; /* section 1 */
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--ifm-footer-background-color: #101418; /* section 1 */
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--ifm-footer-link-hover-color: #ffffff; /* specific footer link hover color */
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--ifm-dropdown-background-color: #242D37; /* section 2 */
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--ifm-table-stripe-background: #101418; /* section 1 */
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--ifm-toc-background-color: #242D37; /* section 2 */
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--ifm-link-color: #6AD6C0; /* specific link color */
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--ifm-link-hover-color: #AEFDED; /* specific link hover color */
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--ifm-font-color-base: #E5E5E5 /* body text */
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--ifm-font-color-base: #E5E5E5; /* body text */
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--ifm-hr-background-color: #242D37; /* section 1 */
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--ifm-toc-link-color: #E5E5E5; /* body text */
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--ifm-toc-background-color: #242D37; /* section 2 */
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--ifm-code-background: #242D37; /* section 2 */
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}
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@media (min-width: 1400px) {
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/* Expand sidebar width above 1400px */
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html[data-theme="light"],
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box-shadow: 0 0 0 2px rgba(0,0,0,0.1) inset;
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}
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html[data-theme="dark"] .table-of-contents {
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background-color: var(--ifm-toc-background-color);
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box-shadow: 0 0 0 2px rgba(0,0,0,0.4) inset;
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}
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html[data-theme="dark"] a.table-of-contents__link--active {
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@ -492,9 +495,6 @@ a.table-of-contents__link--active:before {
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border-left: 6px solid var(--ifm-color-primary);
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transform: translateY(5px);
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}
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html[data-theme="light"] .table-of-contents__link:not(.table-of-contents__link--active) {
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color: rgba(0,0,0,0.9);
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}
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/* toc: show "..." inside code tag */
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.table-of-contents code {
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}
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/* <hr> */
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.markdown hr {
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border-bottom: none;
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}
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html[data-theme="dark"] .markdown hr {
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border-color: rgba(255,255,255,0.1);
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}
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/* admonition */
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.admonition {
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overflow: hidden;
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