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09-25-2025
10:50 AM
Hello, I am not sure I understand what you are trying to do. Those ports are already established when a Cloudera AI session starts up, you can see this by starting a session, then in the code editor, type: !env | grep -i port You can then use these in your code, like in the example here: https://docs.cloudera.com/machine-learning/1.5.4/projects/topics/ml-projects-embedded-web-applications-example-flask-application.html
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06-22-2025
10:49 PM
Hello @SalimAlhajri Thank you for reaching out to Cloudera community Have you tried the steps suggested in the below document https://docs.cloudera.com/machine-learning/1.5.4/runtimes/topics/ml-creating-a-customized-runtimes-image.html Thank you Kshitij Upadhyay
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06-17-2025
11:13 PM
Dear All, I hope you are doing well. I would like your help in understand how I can secure the deployed application. Public Applications By default, authentication for applications is enforced on all ports and users cannot create public applications. If desired, the Admin user can allow users to create public applications that can be accessed by unauthenticated users. To allow users to create public applications on an Cloudera AI Workbench: As an Admin user, turn on the feature flag in Admin > Security by selecting Allow applications to be configured with unauthenticated access. When creating a new application, select Enable Unauthenticated Access. For an existing application, in Settings select Enable Unauthenticated Access. To prevent all users from creating public applications, go to Admin > Security and deselect Allow applications to be configured with unauthenticated access. All existing public applications will immediately stop being publicly accessible. Transparent Authentication Cloudera AI can pass user authentication information to an application, if the application expects an authenticated request. The REMOTE-USER and REMOTE-USER-PERM HTTP headers will be injected to the application hosted by the user. For example: Remote-user=<username>
Remote-user-perm=<RO/RW/Unauthorized> How can I implement and integrate the Transparent Authentication in the deployed application script? Best wishes, Salim
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Cloudera Machine Learning (CML)
06-16-2025
04:25 AM
Hello @SalimAlhajri Thank you for reaching out to cloudera community You can use the copy-docker script to copy the images to your registry. While adding the data services cluster you would get the option to download the script Or else you can try the steps below when you download ECS, download both parcels and images make sure you adjust the manifest.json's http_path to the local http(s) server of the local repo use CM's generateCopyDocker API to generate the version spec copy-docker.sh script adjust the script if needed, in terms of: custom location for image temp storage custom location for pod load temp storage set PODMAN_OR_DOCKER explicitly if podman also identifies itself as docker. Finally run the script to load images from repo server into image registry to access the image registry to load ECS images make sure the user who runs the script is logged into the registry I am attaching a demo script from my cluster. If you have any further queries Please help our community grow. If you found any of the suggestions/solutions provided helped you with solving your issue or answering your question, please take a moment to login and click "Accept as Solution" on one or more of them that helped.
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06-10-2025
10:52 PM
Dear Mike, Thank you for your support. I would like to highlight that I do not have internet access within CDSW, as our Cloudera environment is fully air-gapped. From your previous message, I understand that you are suggesting I create a custom Docker image and run it accordingly. I have already created a custom Docker image — however, I would appreciate it if you could review it and provide your feedback. Additionally, could you clarify your expectations regarding the base operating system for the container image? and the Base image? For your reference, we are using CDSW version 1.10.5. Best wishes, Salim ### **Description of the Docker Image** This Docker image is a **customized environment** tailored for Cloudera Data Science Workbench (CDSW) in an **air-gapped (offline)** setting. It includes the following components: 1. **Base Image**: - Starts with `docker.repository.cloudera.com/cdsw/engine:8` , ensuring compatibility with CDSW. 2. **Operating System**: - **Ubuntu 20.04 LTS**, a lightweight and stable Linux distribution. 3. **MySQL 8.0.4**: - A milestone release of MySQL, installed from pre-downloaded `.deb` packages (no internet required). 4. **Python 3.8.18**: - Compiled from source to ensure version compatibility. 5. **Node.js 22.16.0**: - Installed via a pre-extracted binary archive. 6. **Grafana Enterprise 11.6.0**: - Installed using a `.deb` package for enterprise-grade monitoring. 7. **Ollama**: - A pre-downloaded binary for running large language models locally. 8. **Python Packages**: - Installed **offline** from a pre-downloaded `requirements.txt` file and local wheels (`.whl` or `.tar.gz`) . 9. **Exposed Ports**: - MySQL (3306), Python apps (8000), Grafana (3000), and Ollama (11434). --- ### **Requirements to Build the Image** To build this image in an **air-gapped environment**, you must pre-download and include the following: 1. **Pre-downloaded Dependencies**: - **MySQL 8.0.4 `.deb` packages** (from Cloudera or MySQL archives). - **Python 3.8.18 source tarball** (from [python.org](https://www.python.org/ftp/python/3.8.18/)). - **Node.js 22.16.0 Linux x64 binary** (from [nodejs.org](https://nodejs.org/dist/v22.16.0/)). - **Grafana Enterprise 11.6.0 `.deb` package** (from Grafana’s enterprise download page). - **Ollama binary** (from [ollama.ai/download](https://ollama.ai/download)). 2. **Offline Python Packages**: - Use `pip download -r requirements.txt -d python_packages/` in an online environment to fetch all dependencies locally . 3. **Directory Structure**: Ensure the following files/directories exist in the build context: ```bash . ├── Dockerfile ├── requirements.txt ├── ollama # Pre-downloaded Ollama binary └── dependencies/ ├── mysql-8.0.4/ # MySQL .deb packages ├── python/ # Python 3.8.18 source ├── node-v22.16.0-linux-x64.tar.xz ├── grafana-enterprise-11.6.0.deb └── python_packages/ # Pre-downloaded Python wheels ``` 4. **Build Command**: Run: ```bash docker build -t custom-cdsw:latest . ``` 5. **Push to Private Registry (Optional)**: For CDSW integration, push the image to a registry accessible by CDSW: ```bash docker tag custom-cdsw:latest <your-registry>/custom-cdsw:latest docker push <your-registry>/custom-cdsw:latest ``` --- ### **Key References** - Docker images contain application code, libraries, tools, and dependencies . - Use `docker inspect` to view details about the image . - Dockerfiles are often shared in repositories for transparency . Let me know if you need further clarification!
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