Restructure docs for platform components and use case clarity (#1048)

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Noam Wasersprung
2025-02-23 17:33:55 +02:00
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title: Model Deployment
---
Model deployment makes trained models 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)