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Author: yaronha

README.md

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+<p align="left"><img src="_static/images/MLRun-logo.png" alt="MLRun logo" width="150"/></p>
+
+
+# The Open Source MLOps Orchestration Framework
+
+MLRun **simplifies & accelerates** the production pipeline design using a modular strategy, where the different parts contribute to a continuous, automated, and far simpler path from research and development to scalable production pipelines, without refactoring code, adding glue logic, or spending significant efforts on data and ML engineering.
+
+MLRun uses **Serverless Function** technology: write the code once, using your preferred development environment and simple “local” semantics, and then run it as-is on different platforms and at scale. MLRun automates the data processing and movement, build process, execution, scaling, versioning, parameterization, outputs tracking, CI/CD integration, deployment to production, monitoring, and more.
+
+
+## Configure Your Environment
+
+MLRun  backend service can run locally or over Kubernetes (preferred), see the instructions for installing it [**locally** using Docker](https://docs.mlrun.org/en/latest/install/local-docker.html) or [over **Kubernetes** Cluster](https://docs.mlrun.org/en/latest/install/kubernetes.html). Alternatively, you can use [Iguazio's **managed** MLRun service](https://www.iguazio.com/docs/latest-release/).
+
+This Jupyter Notebook server is designed to work with the different options, it works out of the box with the **local** deployment mode.<br> 
+In order to work with remote MLRun service (Kubernetes or managed) you need to edit and save the [**mlrun.env**](./mlrun.env) file in the following way:
+
+```sh
+# set remote MLRun service address, username and access-key
+MLRUN_DBPATH=https://<service-address>
+V3IO_USERNAME=<user>
+V3IO_ACCESS_KEY=<access-key>
+```
+
+**Once You are done, save the file using the menu or `ctrl + s`, you may need to restart existing Notebooks for the changes to take effect.**
+
+## Tutorials and Examples
+
+Open the [**quick-start.ipynb**](quick-start/quick-start.ipynb) Notebook and follow the instructions in it.
+
+See the more detailed tutorial under the [**tutorial folder**](./tutorial/index.md).
+
+You can find different end to end demos in under the [**demos folder**](./demos/README.md).
+
+Or go through interactive MLRun [**Katacoda Scenarios**](https://www.katacoda.com/mlrun) which teach how to install and use MLRun. 
+
+
+
+```python
+
+```