Skip to content

Developing Data Source and Data Target Jobs

A goal of this Nautobot app is to make it relatively quick and straightforward to develop and integrate your own system-specific Data Sources and Data Targets into Nautobot with a common UI and user experience.

Familiarity with DiffSync and with developing Nautobot Jobs is recommended.

Quickstart Example

The following code presents a minimum viable example for syncing VLANs from a remote system into Nautobot. You will have to adapt the following things to make this work for your use case:

  • Swap out any mention of a "remote system" for your actual remote system, such as your IPAM tool
  • Implement any models that you need, unless you are actually only interested in VLAN data
  • Your load function in the remote adapter will probably be a little harder to implement, check the example integrations in this repository (under nautobot_ssot/integrations)

It contains 3 steps:

  • Data modeling
  • Adapters
    • Nautobot
    • Remote
  • Nautobot Job
# example_ssot_plugin/jobs.py
from typing import Optional

from diffsync import DiffSync
from nautobot.ipam.models import VLAN
from nautobot.extras.jobs import Job
from nautobot_ssot.contrib import NautobotModel, NautobotAdapter
from nautobot_ssot.jobs import DataSource
from remote_system import APIClient  # This is only an example


# Step 1 - data modeling
class VLANModel(NautobotModel):
    """DiffSync model for VLANs."""
    _model = VLAN
    _modelname = "vlan"
    _identifiers = ("vid", "group__name")
    _attributes = ("description",)

    vid: int
    group__name: Optional[str] = None
    description: Optional[str] = None

# Step 2.1 - the Nautobot adapter
class MySSoTNautobotAdapter(NautobotAdapter):
    """DiffSync adapter for Nautobot."""
    vlan = VLANModel
    top_level = ("vlan",)

# Step 2.2 - the remote adapter
class MySSoTRemoteAdapter(DiffSync):
    """DiffSync adapter for remote system."""
    vlan = VLANModel
    top_level = ("vlan",)

    def __init__(self, *args, api_client, **kwargs):
        super().__init__(*args, **kwargs)
        self.api_client = api_client

    def load(self):
        for vlan in self.api_client.get_vlans():
            loaded_vlan = self.vlan(vid=vlan["vlan_id"], group__name=vlan["grouping"], description=vlan["description"])
            self.add(loaded_vlan)

# Step 3 - the job
class ExampleDataSource(DataSource, Job):
    """SSoT Job class."""
    class Meta:
        name = "Example Data Source"

    def load_source_adapter(self):
        self.source_adapter = MySSoTRemoteAdapter(api_client=APIClient())
        self.source_adapter.load()

    def load_target_adapter(self):
        self.target_adapter = MySSoTNautobotAdapter()
        self.target_adapter.load()

jobs = [ExampleDataSource]

Note

This example is able to be so brief because usage of the NautobotModel class provides create, update and delete out of the box for the VLANModel. If you want to sync data from Nautobot to another remote system, you will need to implement those yourself using whatever client or SDK provides the ability to write to that system. For examples, check out the existing integrations under nautobot_ssot/integrations

The following sections describe the individual steps in more detail.

Step 1 - Defining the Models

The models use DiffSync, which in turn uses Pydantic for its data modeling. Nautobot SSoT comes with a set of classes in nautobot_ssot.contrib that implement a lot of functionality for you automatically, provided you adhere to a set of rules.

The first rule is to define your models tightly after the Nautobot models themselves. Example:

from nautobot.tenancy.models import Tenant
from nautobot_ssot.contrib import NautobotModel

class DiffSyncTenant(NautobotModel):
    """An example model of a tenant."""
    _model = Tenant
    _modelname = "tenant"
    _identifiers = ("name",)
    _attributes = ("description",)

    name: str
    description: str

As you can see when looking at the source code of the nautobot.tenancy.models.Tenant model, the fields on this model (name and description) match the names of the fields on the Nautobot model exactly. This enables the base class NautobotModel to dynamically load, create, update and delete your tenants without you needing to implement this functionality yourself.

The above example shows the simplest field type (an attribute on the model), however, to build a production implementation you will need to understand how to identify different variants of fields by following the modeling docs.

Step 2.1 - Creating the Nautobot Adapter

Having created all your models, creating the Nautobot side adapter is very straight-forward:

from nautobot_ssot.contrib import NautobotAdapter

from your_ssot_app.models import DiffSyncDevice, DiffSyncPrefix, DiffSyncIPAddress


class YourSSoTNautobotAdapter(NautobotAdapter):
    top_level = ("device", "prefix")

    device = DiffSyncDevice
    prefix = DiffSyncPrefix
    ip_address = DiffSyncIPAddress  # Not in the `top_level` tuple, since it's a child of the prefix model

The load function is already implemented on this adapter and will automatically and recursively traverse any children relationships for you, provided the models are defined correctly.

Step 2.2 - Creating the Remote Adapter

Regardless of which direction you are synchronizing data in, you need to write the load method for the remote adapter yourself. You can find many examples of how this can be done in the nautobot_ssot.integrations module, which contains pre-existing integrations with remote systems.

Note

As the features in nautobot_ssot.contrib are still very new, most existing integrations do not use them. The example job in nautobot_ssot/jobs/examples.py can serve as a fully working example.

Step 3 - The Job

Develop a Job class, derived from either the nautobot_ssot.jobs.base.DataSource or nautobot_ssot.jobs.base.DataTarget classes provided by this Nautobot app, and implement the methods to populate the self.source_adapter and self.target_adapter attributes that are used by the built-in implementation of sync_data. This sync_data method is an opinionated way of running the process including some performance data (more about this in the next section), but you could overwrite it completely or any of the key hooks that it calls.

The methods calculate_diff and execute_sync are both implemented by default, using the data that is loaded into the adapters through the respective methods. Note that execute_sync will only execute when dry-run is set to false.

Optionally, on your Job class, also implement the lookup_object, data_mapping, and/or config_information APIs (to provide more information to the end user about the details of this Job), as well as the various metadata properties on your Job's Meta inner class. Refer to the example Jobs provided in this Nautobot app for examples and further details. Install your Job via any of the supported Nautobot methods (installation into the JOBS_ROOT directory, inclusion in a Git repository, or packaging as part of an app) and it should automatically become available!

Extra Step: Implementing create, update and delete

If you are synchronizing data to Nautobot and not from Nautobot, you can entirely skip this step. The nautobot_ssot.contrib.NautobotModel class provides this functionality automatically.

If you need to perform the create, update and delete operations on the remote system however, it will be up to you to implement those on your model.

Note

You still want your models to adhere to the modeling guide, since it provides you the auto-generated load function for the diffsync adapter on the Nautobot side.