NetAsCode DC VXLAN (nac_dc_vxlan) Ansible Collection for configuring Cisco VXLAN EVPN fabrics using the Cisco Nexus Dashboard Fabric Controller (NDFC). This collection simplifies the configuration of VXLAN fabrics by abstracting the automation using a data model that represents the desired state of the fabric. With this collection, an operator only needs to modify the configuration state in the data model instead of creating custom playbooks with modules and the associated parameters.
This approach allows for consistent and repeatable configuration of VXLAN fabrics and aligns with Infrastructure as Code (IaC) methodology, where the configuration state of NDFC is saved in a version control system and managed as code.
Infrastructure as code (IaC) is a DevOps methodology that uses code to manage and provision IT infrastructure, bypassing manual procedures. IaC uses a descriptive coding language to automate the provisioning of servers, operating systems, network devices and more.
In easy-to-understand YAML the NetAsCode VXLAN EVPN collection allows you to configure data structures describing the configuration state of a VXLAN fabric for Cisco Nexus datacenters and then deploys this state using Ansible and the Cisco Nexus Dashboard. With little to no knowledge about automation, you can use this collection to instantiate a VXLAN EVPN fabric.
YAML files are created that contain a pre-determined data schema which is translated into underlying Ansible modules and resources. The core Ansible Collection is open source and available. This collection is designed to be used in a CI/CD pipeline in order to drive this declarative method of configuring a VXLAN fabric.
Note
For complete support and additional capabilities, Cisco provides a professional services capability under the Services as Code portfolio of services which can provide feature creation, end to end support and more.
Role: cisco.nac_dc_vxlan.validate
The validate role ensures that the data model is correct and that the data model can be processed by the subsequent roles. The validate role reads all the files in the host_vars directory and creates a single data model in memory for execution.
As part of the VXLAN as Code service from Cisco, you will also be able to utilize the semantic validation feature to make sure that the data model matches the intended expected values. This is a powerful feature that allows you to ensure that the data model is correct before it is deployed to the network. Additonally the validate role allows creation of rules that can be used to prevent operators from making specific configurations that are not allowed in the network. These can be as simple as enforcing proper naming conventions to more complex rules for interconnectivity issues that should be avoided. These rules are coded in Python and can be constructed as part of the Services as Code offer.
Role: cisco.nac_dc_vxlan.dtc.create
The create role builds all of the templates and variable parameters required to deploy the VXLAN fabric and creates fabric state in NDFC. The data model is converted into the proper templates required by the Ansible modules used to communicate with the NDFC controller and manage the fabric state. The create role has a dependency on the validate role.
Role: cisco.nac_dc_vxlan.dtc.deploy
The deploy role deploys the fabric state created using the Create role to the NDFC managed devices. The deploy role has a dependency on the validate role.
Role: cisco.nac_dc_vxlan.dtc.remove
The remove role removes state from the NDFC controller and the devices managed by the NDFC controller. When the collection discovers managed state in NDFC that is not defined the the data model it gets removed by this role. For this reason this role requires the following variables to be set to true under the group_vars directory. This avoids accidental removal of configuration from NDFC that might impact the network. The remove role has a dependency on the validate role.
Inside the example repository under group_vars/ndfc is a file called ndfc.yaml that contains the variables:
# Control Parameters for 'Remove' role tasks
interface_delete_mode: false
network_delete_mode: false
vrf_delete_mode: false
inventory_delete_mode: false
vpc_delete_mode: false
link_vpc_delete_mode: false
policy_delete_mode: falseWarning
These variables are set to false by default to avoid accidental removal of
configuration from NDFC that might impact the network.
These roles when run in sequence (validate, create, deploy, remove) are
designed to build out the entire fabric and can be executed by a pipeline. The
roles can also be run in isolation by simply commenting out the roles that are
not required during testing and fabric buildout to validate incremental changes.
The following control variables are available in this collection.
| Variable | Description | Default Value |
|---|---|---|
force_run_all |
Force all roles in the collection to run | false |
interface_delete_mode |
Remove interface state as part of the remove role | false |
network_delete_mode |
Remove network state as part of the remove role | false |
vrf_delete_mode |
Remove vrf state as part of the remove role | false |
inventory_delete_mode |
Remove inventory state as part of the remove role | false |
link_vpc_delete_mode |
Remove vpc link state as part of the remove role | false |
vpc_delete_mode |
Remove vpc pair state as part of the remove role | false |
policy_delete_mode |
Remove policy state as part of the remove role | false |
These variables are described in more detail in different sections of this document.
The default settings can be overridden in group_vars.
Installation of a Python virtual environment is needed in order to install the collection and its requirements. We recommend pyenv which provides a robust Python virtual environment capability that also allows for management of different Python versions. The following instructions are detailed around using pyenv. For pipeline execution please refer to the pipeline section which is documented at container level.
To simplify getting started with this collection we provide you with an example repository. Simply clone this repo from GitHub to create the required skeleton, including examples for pipelines. Cloning the repository requires the installation of git client which is available for all platforms.
Run the following command in the location of interest.
git clone https://github.com/netascode/ansible-dc-vxlan-example.git nac-vxlanThis will clone the example repository into the directory nac-vxlan. Next delete the .git repository to remove the connection to the example repository. Now you can create your own repository from this pre-built structure.
In this directory create a new virtual environment and install a Python version of your choice. At the time writing, Python version 3.10.13 is commonly used. Command pyenv install 3.10.13 will install this version. For detailed instructions please visit the pyenv site.
cd nac-vxlan
pyenv virtualenv <python_version> nac-ndfc
pyenv local nac-ndfcExecuting command pyenv local nac-ndfc sets the environment so that whenever the directory is entered it will change into the right virtual environment.
Included in the example repository is the requirements file to install ansible. First upgrade PIP to latest version.
pip install --upgrade pip
pip install -r requirements.txtThe default placement of the ansible galaxy collections would be in your home directory under .ansible/collections/ansible_collections/. To install the collection in the default location run the following command:
ansible-galaxy collection install -r requirements.yamlIf you wish to install the galaxy collection inside the repository you are creating with this example repository, you can run the following command:
ansible-galaxy collection install -p collections/ansible_collections/ -r requirements.yamlThe ansible.cfg file needs to be configured to point to the location of the collection.
This is the path for all the python modules and libraries of the virtual environment that were created. If you look in that directory, you will find the collections package locations. Here is the base ansible.cfg, you will need to adjust the collections_path to your environment paths:
[defaults]
collections_path = ./collections/ansible_collections/
If you wish to add any ansible callbacks (those listed below expand on displaying time execution) you can add the following to the ansible.cfg file:
callback_whitelist=ansible.posix.timer,ansible.posix.profile_tasks,ansible.posix.profile_roles
callbacks_enabled=ansible.posix.timer,ansible.posix.profile_tasks,ansible.posix.profile_roles
bin_ansible_callbacks = TrueVerify that the ansible configuration file is being read and all the paths are correct inside of this virtual environment.
ansible --version
ansible [core 2.16.3]
config file = /Users/username/tmp/nac-vxlan/ansible.cfg
configured module search path = ['/Users/username/.ansible/plugins/modules', '/usr/share/ansible/plugins/modules']
ansible python module location = /Users/username/.pyenv/versions/3.10.13/envs/nac-ndfc/lib/python3.10/site-packages/ansible
ansible collection location = /Users/username/path/to/collections/ansible_collections
executable location = /Users/username/.pyenv/versions/nac-ndfc/bin/ansible
python version = 3.10.13 (main, Oct 29 2023, 00:04:17) [Clang 15.0.0 (clang-1500.0.40.1)] (/Users/username/.pyenv/versions/3.10.13/envs/nac-ndfc/bin/python3.10)
jinja version = 3.1.4
libyaml = TrueAs is standard with Ansible best practices, inventory files provide the destination targets for the automation. For this collection, the inventory file is a YAML file that contains the information about the devices that are going to be configured. The inventory files is called inventory.yaml and is located in the root of the repository.
The inventory file is going to contain a structure similar to this:
---
all:
children:
ndfc:
hosts:
nac-ndfc1:
ansible_host: "{{ lookup('ansible.builtin.env', 'ND_HOST') }}"This structure creates two things in Ansible, a group called ndfc and a host called nac-ndfc1:. These are tied back to the directory structure of the repository that contains two folders in the top directory:
graph
root-->group_vars
root-->host_vars
group_vars-->ndfc
ndfc-->connection.yaml
host_vars-->nac-ndfc1
nac-ndfc1-->data_model_files
The data model is required to exist under the host_vars directory structure. The inventory file organizes how the variables are read through both the group_vars and the host_vars. Under the group_vars is where you will set the connection.yaml file that has the credentials of the NDFC controller. Under the host_vars is where we will place the inventory.
The collection is pre-built to utilize the group_vars and host_vars matching what is already constructed in the repository. Currently this methodology is a 1:1 relationship between code repository and NDFC fabric. For more complex environments, the inventory file can be expanded to include multiple groups and hosts including the usage of multi-site fabrics as explained in a separate document.
In the provided inventory.yaml file in the project's root directory, update
the ansible_host variable to point to your NDFC controller by replacing "{{ lookup('ansible.builtin.env', 'ND_HOST') }}" with the IP address of the
NDFC controller or setting the ND_HOST environment variable as described
in Step 3.
In the directory group_vars/ndfc is a file called connection.yaml that contains example data as:
---
# Connection Parameters for 'ndfc' inventory group
#
# Controller Credentials
ansible_connection: ansible.netcommon.httpapi
ansible_httpapi_port: 443
ansible_httpapi_use_ssl: true
ansible_httpapi_validate_certs: false
ansible_network_os: cisco.dcnm.dcnm
# NDFC API Credentials
ansible_user: "{{ lookup('env', 'ND_USERNAME') }}"
ansible_password: "{{ lookup('env', 'ND_PASSWORD') }}"
# Credentials for devices in Inventory
ndfc_switch_username: "{{ lookup('env', 'NDFC_SW_USERNAME') }}"
ndfc_switch_password: "{{ lookup('env', 'NDFC_SW_PASSWORD') }}"
This file is going to contain the connection parameters for reachability to the
NDFC controller. The ansible_user, and ansible_password are set to establish
connection to the NDFC controller. For the devices, you will set separate
variables also configured as environment variables.
Important
The usage of environment variables is done for security reasons, so that the credentials are not stored in plain text in the repository. Accidentally including your credentials in a repository is very hard to remove. Hence, the usage of environment variables is recommended as a starting point.
Also, if you plan to eventually utilize a pipeline, the environment variables can be set in the pipeline configuration in a secure manner that is not exposed to the repository.
The usage of Ansible vault is also possible to encrypt the contents of the connection file or simply encrypt the variables.
The environment variables are set in the shell that is going to execute the playbook. The environment variables are configured via the export command in the shell (bash). Using this template, set the environment variables to the correct credentials for the NDFC controller and the devices in the inventory on your topology.
# These are the credentials for ND/NDFC
export ND_HOST=10.15.0.11
export ND_DOMAIN=local
export ND_USERNAME=admin
export ND_PASSWORD=Admin_123
# These are the credentials for the devices in the inventory
export NDFC_SW_USERNAME=admin
export NDFC_SW_PASSWORD=Admin_123The following quickstart repository is available to provide a step by step guide for using this collection.
This collection is intended for use with the following release versions:
NDFC Release 12.2.1or later.
This collection has been tested against following Ansible versions: >=2.14.15.
Plugins, roles and modules within a collection may be tested with only specific Ansible versions. A collection may contain metadata that identifies these versions. PEP440 is the schema used to describe the versions of Ansible.
The following playbook for the NDFC as Code collection is the central execution point for this collection. Compared to automation in other collections, this playbook is designed to be mostly static and typically will not change. What gets executed during automation is based entirely on changes in the data model. When changes are made in the data model, the playbook will call the various roles and underlying modules to process the changes and update the NDFC managed fabric.
The playbook is located in the root of the repository and is called vxlan.yaml. It contains the following:
---
# This is the main entry point playbook for calling the various
# roles in this collection.
- hosts: nac-ndfc1
any_errors_fatal: true
gather_facts: no
roles:
# Prepare service model for all subsequent roles
#
- role: cisco.nac_dc_vxlan.validate
# -----------------------
# DataCenter Roles
# Role: cisco.netascode_dc_vxlan.dtc manages direct to controller NDFC workflows
#
- role: cisco.nac_dc_vxlan.dtc.create
tags: 'role_create'
- role: cisco.nac_dc_vxlan.dtc.deploy
tags: 'role_deploy'
- role: cisco.nac_dc_vxlan.dtc.remove
tags: 'role_remove'The host is defined as nac-ndfc1 which references back to the inventory.yaml file. The roles section is where the various collection roles are called.
The first role is cisco.nac_dc_vxlan.validate which is going to validate the data model. This is a required step to ensure that the data model is correct and that the data model is going to be able to be processed by the subsequent roles.
The subsequent roles are the cisco.nac_dc_vxlan.dtc.create, cisco.nac_dc_vxlan.dtc.deploy, and cisco.nac_dc_vxlan.dtc.remove roles. These roles are the primary roles that will invoke changes in NDFC as described earlier.
Warning
For your safety as indicated earlier, the remove role also
requires setting some variables to true under the group_vars directory.
This is to avoid accidental removal of configuration from NDFC that might
impact the network. This will be covered in more detail below.
The playbook can be configured to execute only the roles that are required. For example, as you are building your data model and familiarizing yourself with the collection, you may comment out the deploy and remove roles and only execute the validate and create roles. This provides a quick way to make sure that the data model is structured correctly.
Role Level Tags:
To speed up execution when only certain roles need to be run the following role level tags are provided:
| Tag Name | Description |
|---|---|
| role_validate | Select and run cisco.nac_dc_vxlan.validate role |
| role_create | Select and run cisco.nac_dc_vxlan.create role |
| role_deploy | Select and run cisco.nac_dc_vxlan.deploy role |
| role_remove | Select and run cisco.nac_dc_vxlan.remove role |
Note
The validate role will automatically run if tags role_create, role_deploy, role_remove are specified.
Tip
Example: Selectively run cisco.nac_dc_vxlan.create role alone.
ansible-playbook -i inventory.yaml vxlan.yaml --tags role_createSelective Execution based on Model Changes
This collection has the capability to selectively run only sections within each role that changed in the data model. This requires at least one run where all of the roles and sections are executed creating previous state. On the next run only the sections that changed in the data model will be executed. For example, if VRFs and Networks are added/changed/removed in the model data files only the VRF and Networks sections will be run.
This capability is not available under the following conditions:
- Control flag
force_run_allunder group_vars is set totrue. - When using ansible tags to control execution.
- When one of the following roles failed to complete on the previous run.
cisco.nac_dc_vxlan.validatecisco.nac_dc_vxlan.createcisco.nac_dc_vxlan.deploycisco.nac_dc_vxlan.remove
If any of these conditions is true then all roles/sections will be run.
- Ansible Using collections for more details.
Ongoing development efforts and contributions to this collection are focused on new roles when needed and enhancements to current roles.
We welcome community contributions to this collection. If you find problems, please open an issue or create a PR against the Cisco netascode_dc_vxlan collection repository.
MIT License
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