Add Model Deployment overview

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revital
2025-02-19 11:00:36 +02:00
parent 3e8b6665d9
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---
title: Model Deployment
---
Model deployment is a critical step in the machine learning lifecycle, enabling trained models to be accessible for
real-world applications. ClearML provides a comprehensive suite of tools for seamless model deployment, which supports
features including:
* Version control
* Automatic updates
* Performance monitoring
ClearML's offerings optimize the deployment process
while ensuring scalability and security. The solutions include:
* **Model Deployment UI Applications** (available under the Enterprise Plan) - The UI applications simplify deploying models
as network services through secure endpoints, providing an interface for managing deployments--no code required.
See more information about the following applications:
* [vLLM Deployment](webapp/applications/apps_model_deployment.md)
* [Embedding Model Deployment](webapp/applications/apps_embed_model_deployment.md)
* [Llama.cpp Model Deployment](webapp/applications/apps_llama_deployment.md)
* **Command-line Interface** - `clearml-serving` is a CLI for model deployment and orchestration.
It supports integration with Kubernetes clusters or custom container-based
solutions, offering flexibility for diverse infrastructure setups.
For more information, see [ClearML Serving](clearml_serving/clearml_serving.md).
## Model Endpoint Monitoring
All deployed models are displayed in a unified **Model Endpoints** list in the UI. This
allows users to monitor endpoint activity and manage deployments from a single location.
For more information, see [Model Endpoints](webapp/webapp_model_endpoints.md).
![Model Endpoints](img/webapp_model_endpoints_monitor.png#light-mode-only)
![Model Endpoints](img/webapp_model_endpoints_monitor_dark.png#dark-mode-only)

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]
},
{
"Model Deployment": [
type: 'category',
collapsible: true,
collapsed: true,
label: 'Model Deployment',
link: {type: 'doc', id: 'deploying_models'},
items: [
{
type: 'category',
collapsible: true,