ea97e7767ba461705439497aa232f0093fb8aa28
VXLAN-EVPN Lab with ContainerLab
Sources
Overview
This project provides a hands-on lab environment for understanding and experimenting with VXLAN-EVPN (Ethernet VPN) technology. Using ContainerLab, the lab sets up a VXLAN topology featuring 1 spine and 2 leaves nodes. The lab can be deployed directly on a PC with ContainerLab installed or through a DevContainer environment.
Project Structure
The project directory is structured as follows:
.devcontainer/devcontainer.json: Configuration for the DevContainer environment.hosts: Directory containing host configuration files for the lab.network_images/ceos-lab-4.30.3M.tar.xz: Container image used for the lab nodes.lab_vxlan.yml: YAML file describing the VXLAN lab topology.
Prerequisites
- Docker and Docker Compose (for DevContainer setup).
- ContainerLab installed either on the host or within the DevContainer.
- Basic understanding of networking and VXLAN-EVPN concepts.
Setup and Deployment
-
DevContainer Setup (Optional):
If using DevContainer, ensure Docker and Docker Compose are installed on your machine.
Open the project in a compatible IDE (like Visual Studio Code) and start the DevContainer environment. -
ContainerLab Setup:
- Direct Installation: Install ContainerLab on your host machine.
- Via Terraform, documentation avalaible here
-
Start the Lab:
- Navigate to the project directory.
- Run
containerlab deploy -t lab_vxlan.ymlto deploy the lab topology.
Usage
- Once the lab is deployed, you can access the individual nodes (spines and leaves) via CLI or SSH to configure and test VXLAN-EVPN functionalities.
- Use the
hostsdirectory to modify or apply specific configurations.
Project evolution
To Do
- Enable Features
- Set MTU
- Map VLAN to VNI
- Routed Link
- Host Ports
- Loopback interfaces
Description
This project provides a hands-on lab environment for understanding and experimenting with VXLAN-EVPN (Ethernet VPN) technology.
sing ContainerLab, the lab sets up a VXLAN topology featuring 1 spine and 2 leaves nodes.
The lab can be deployed directly on a PC with ContainerLab installed or through a DevContainer environment.
Languages
Markdown
100%