World Wide Technology, DevNet Associate Study Group
This repository provides a foundation for exam preparation the Cisco DevNet Associate. The learning material is focused on Software Development Kit (SDKs), Cisco product APIs, the Meraki SDK, and an Introduction to Python.
Initally we targeted a cloud instance (AWS EC2) to host the Jupyter Notebook. That implementation does not require any software on the student laptop (workstation) other than an SSH client, as Docker is running in the cloud instance.
It has been updated to use Visual Studio Code (a source-code editor made by Microsoft for Windows, Linux and macOS) and the Docker Dev Container extension and Docker Desktop.
A companion presentation (initially developed using the cloud instance) for SDK/APIs is available at https://www.slideshare.net/joelwking/devnet-study-group-using-a-sdk.
The presentation developed for the Introduction to Python using the Dev Container is available at https://www.slideshare.net/joelwking/devnet-associate-python-introduction-249397611.
Jupyter Notebook Tutorial: https://www.dataquest.io/blog/jupyter-notebook-tutorial/.
Using the Dev Container eliminates the need to configure and pay for cloud compute resources. Additionally, is is much simplier to get the server up and running quickly.
Clone this repository git clone ... to your local machine.
Install the required software and the remote container extension on your laptop (workstation).
- Docker Desktop. Download and install Docker Desktop for your target development environment, https://www.docker.com/products/docker-desktop
- Visual Studio Code, Download and install it and the Visual Studio Code Remote Development Extension Pack.
Select the 'Extensions' sidebar menu item and enter remote in the Search Extensions in Marketplace dialog box and install this extension (ms-vscode-remote.remote-containers).
You can also locate and install the Visual Studio Code Remote - Containers from the web link.
Note: You may need to restart VS code after installing the Extension Pack for the extension to be recognized.
From VS Code, issue a File -> Open Workspace, and select the workspace.code-workspace in this directory and follow the prompts to build the Docker image and container.
When you see the window "Starting Dev Container (show log):", click on the link to open the terminal prompt.
The .devcontainer/devcontainer.json configuration file will start the server after the container is built. You will see the notebook start and display the URL (with access token) to access the web interface. Click on the PORTS window tab, verify the Local Address and substitute the host port for the port 8888 specified in the URL if necessary, and launch the notebook using a web browser on your laptop.
I 13:38:29.294 NotebookApp] Serving notebooks from local directory: /workspaces/devnet-sdk
[I 13:38:29.294 NotebookApp] Jupyter Notebook 6.4.0 is running at:
[I 13:38:29.295 NotebookApp] http://21d5ed265e0f:8888/?token=e6ca46bd2dca2d3bb4984161b68d68a282b8c400c0d3819f
[I 13:38:29.295 NotebookApp] or http://127.0.0.1:8888/?token=e6ca46bd2dca2d3bb4984161b68d68a282b8c400c0d3819f
[I 13:38:29.296 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[W 13:38:29.308 NotebookApp] No web browser found: could not locate runnable browser.
[C 13:38:29.309 NotebookApp]
To access the notebook, open this file in a browser:
file:///root/.local/share/jupyter/runtime/nbserver-175-open.html
Or copy and paste one of these URLs:
http://21d5ed265e0f:8888/?token=e6ca46bd2dca2d3bb4984161b68d68a282b8c400c0d3819f
or http://127.0.0.1:8888/?token=e6ca46bd2dca2d3bb4984161b68d68a282b8c400c0d3819f
If you stop the running server, you can restart by opening a terminal window. You should see a prompt similar to:
root@d2644c744933:/workspaces/devnet-sdk#Enable the Python virtual environment and start the notebook service in that environment:
source /opt/jupyter/bin/activate && jupyter notebook --port=8888 --ip=0.0.0.0 --allow-rootor by executing the shell script source ./start_jupyter.sh.
Select the notebook files you wish to examine.
In the root directory, SANDBOX.md provides instructions on creating an AWS EC2 instance and installing Docker CE, either manually or using the Ansible playbook playbooks/install_docker.yml.
In the library/notebooks directory, README.md provides instructions on how to install and run the Docker image specified in library/notebooks/Dockerfile. The running container is used to execute an instance of Jupyter notebooks. Within the container, Python3, the Meraki SDK, a sample notebook (library/notebooks/Using_a_SDK.ipynb) and Python program (library/notebooks/using_meraki_sdk.py) are referenced in the lab guide library/notebooks/MERAKI_README.md.
There is a notebook showing an implementation of rate limiting logic to address any 429 errors. Refer to the notebook under library/notebooks/Meraki_Rate_Limiting_example.ipynb.
joel.king@wwt.com (@joelwking)