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Tonight – Live on YouTube with Du’An “Lab Every Day” Lightfoot !

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Merlin 3D: Cisco Product Security Incident Response Team (PSIRT) 3D Report!

I have been very silent on this blog lately – apologies – your best way to follow my development work now is likely Twitter or YouTube

However! I have been using Blender to make 3D Animations from Network State Data

I’ve recently figured out how to make these animations Web-ready !

Check it out! This is the PSIRT Report for the Cisco DevNet Sandbox Nexus 9k as a 3D Blender

Click here for the full page version – Verge3D Web Interactive (automateyournetwork.ca)

Much more to come!

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Merlin Feature: WebEx #chatbots with pyATS

With all the big WebEx news – including a new logo – I wanted to revisit the basic #chatbots I have working using pyATS, Python requests, and the WebEx API after the conversation came up in the #pyATS WebEx Community space today:

First, let’s take a look at what this does, and this is not limited to Merlin; any pyATS job has this capability

If you create the pyats.conf file as Takashi suggests and add the [webex] information it will enable the pyATS job to report the job summary into the WebEx space you provide the config file.

This looks something like this inside of WebEx:

This in itself is pretty handy! And all you need to do is go to the Cisco WebEx for Developers portal and either make a Bot under My Apps

Or, right from the browser, grab one of the 12 hour tokens

The easiest way to get one of these is to go to the Documentation

Find the API Reference

Find Messages

Pick POST

COPY THIS BEARER TOKEN

Paste that into your pyats.conf

But how do I get the Room / Channel / Space ID?

If you browse to Rooms

You can GET your current Room list

This will give you the JSON list – here is the Merlin Room ID

Thats it you are ready to connect your pyATS jobs for a job summary as a WebEx message!

Adding Network State Data

With the above foundational WebEx integration with pyATS and WebEx’s simplicity I thought I would integrate a few sample commands into a Merlin pyATS job for the community to see how you can send Network State data to WebEx!

I want the message to be in Markdown so I am going to use a Jinja2 template to craft the JSON we can POST with Python requests after pyATS has parsed or learned the function

We don’t need a lot to make this happen either here is everything I import

  • Update – I’ve also come to discover we need 1 more import and pip install requests_toolbelt in order to attach files to WebEx messages

We setup our WebEx room and token (12 hour or bot) as variables we can call later

The general_functionalities are important these are object oriented code that gets reused per pyATS learn or parse library call.

Then for this example I will do 2 learn functions, platform and routing and see if I can transform real network state data into meaningful WebEx messages

I tell Python where to find the Jinja2 templates and setup a variable I can use later to load said templates

We then setup our pyATS framework and connect (testbed.connect) to our topology

Again the testbed file looks like this

Now that we have connected we can begin our Test Steps ultimately looping (for) over each device in our topology (testbed)

Yes in this Sandbox there is only 1 device but this could scale to X devices. Just add them to the testbed.

Now we can learn platform

As of right now we have the following JavaScript Object Notation (JSON) data inside the self.learned_platform variable

Our goals:

  1. Send a log of our pyATS Merlin job to a WebEx Room or Individual
  2. Send this data as a human friendly message
  3. Create an XLSX spreadsheet we can attach to our message

Now we start our test steps

We will get a boolean pass/fail from the Create CSV and Sent to WebEx WebEx step

Next I set up a few variables – namely the Jinja2 references, the directory for the XLSX file, and the file name.

Also – for attachments we will declare another variable, the MultipartEncoder with the information required to attach the Learned_Platform.csv file

Next we template the .xlsx file from the Jinja2 template

Which looks like this:

That renders the file that looks like this

We will use 2 more Jinaj2 templates for the actual message we will send. Because The JSON body we post to WebEx is a single line, and in Markdown a header row starts with a # symbol, to avoid making the whole thing a header we will send it first.

Here is the line in Python

And the matching Jinja2 template

Remember, we are sending a long single line / string, as markdown, so if we want multi-line we need to add <br/> the Markdown linebreak command

Here is how we send the header

Which looks like this in WebEx:

Now let’s go ahead and template the Markdown

Which looks like:

Important! I had to “trim” this from what is in the “full” Markdown as there *is* a character limit so watch for that!

But that is also why we can attach the full CSV

So go get #chatbotting using real network state data!

Reach out if you hit any snags and watch for the full development video!

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Creating a Network Search Engine

Imagine being able to use a keyword search engine against your network ? A Google-like query for “VLAN 100”, a MAC address, IP address, even an ACL or simply the keyword “Down” that returns real time search results !

It sounds far-fetched but that is exactly what I’ve been able to do in the latest addition to my open source project Merlin ! I’ve made this available as open source!

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merlin (this link opens in a new window) by automateyournetwork (this link opens in a new window)

Network Magic: Transforming the CLI and REST API using Infrastructure As Code automation

4 Subscribers 16 Watchers 6 Forks Check out this repository on GitHub.com (this link opens in a new window)

High Level Goals

  1. Use the pyATS framework and Genie SDK to:
    a. Learn features
    b. Parse show commands
  2. With the JavaScript Object Notation (JSON) we get back from pyATS
    a. Index the JSON into a database
    b. Index the JSON into a search engine
    c. Visualize the database

Enter: Elastic

As you may know Merlin already creates a no-SQL document database using TinyDB – a serverless database that is very easy to use. My only problem is that I haven’t found (and confirmed by TinyDB author) a UI or frontend to consume and present the TinyDB.

Poking around the Internet I found Elastic – a suite of tools that seem like a perfect fit for my goals. “Elastic – Free and Open Search”

I suggest you start here and read about the ELK Stack

The Solution – Elastic Setup:

I setup a 14-day trial in the Elastic Cloud for the purposes to getting going. Elastic can also be run in a local Docker container or hosted on Linux.

  • Note – I tried using WSL Ubuntu but systemd is not currently supported and you will get this error:
System has not been booted with systemd as init system

Once you have logged into Elastic, you can use a Google account for this, you will want to setup a Deployment

Here is Merlin as a Deployment

Which then opens up a full menu of amazing features and capabilities

Some key information:

When you first setup your Deployment you will get one-time displayed credentials you *need* make sure you capture this information!

Your Endpoint (the URL to your database) is available in a click copy here in the main dashboard. You can also launch Kibana and Enterprise Search / copy their unique endpoint URLs here.

Since we are using Elastic Cloud make note of the Cloud ID

As we need this in Python to connect to our endpoints.

In order to setup the Search Engine click Enterprise Search and then when presented with the option Elastic App Search

Create an Engine

Name your engine (I would suggest whatever you named your deployment -engine or -search)

Now the next screen will present you with four methods of populating the Search Engine with JSON

We are going to be Indexing by API and if you pay attention to the Example it will give you what you need to do this and a sample body of JSON

(You get your URL and Bearer Token; make note of both we need them in the Python)

The Solution – The Python:

Here is the relevant Python / pyATS code you need to build your own Elastic index (Deployment) and then also the ElasticSearch search engine !

First you need to pip install pyATS, Elasticsearch, and elastic_enterprise_search

pip install pyATS[full]
pip install elasticsearch
pip install elastic_enterprise_search

Next, in the actual Python, you will need to import the above libraries into Python

As well as the pyATS framework

Next in the Python we need to setup a few things to interact with Elastic

Now we get into the actual pyATS job first setting up the AE Test section and using testbed.connect to establish our SSH connection to the network device

Next we setup our Test Case and define self, testbed, section, and steps. Each Step is a boolean test in pyATS.

For device in testbed kicks off the loop that runs the commands per device in the testbed topology (list of devices in the testbed file)

Now I have defined a function that can be reused that has a step and try to device.learn(function_name).info (and fail gracefully if the function could not be learned)

Now we simply feed this function the various features we want to learn

In this case it was written for the Cisco DevNet Sandbox – NXOS – Nexus 9k which only supports a limit number of features. In a real environment we can learn even more!

Then we use a different function for the parsed show commands

And run a variety of show commands

Now Merlin has, to date, created business-ready documents (CSV, markdown, HTML) and experimental documents (Mind Maps, Network Graphs) from the JSON we have inside all of these variables.

Now here is how we send the JSON to be Indexed in Elastic

Lets take a few examples – learn BGP – as a second fail-safe check in case it did parse correctly but for some reason was empty I first check if its not None

If its not none, we index it in our Deployment

Then we index it in our Search Engine

Here is show ip interface brief

Its easy and repetitive code – so much so that I will likely write another function for these 6 lines of code and just feed it the learn / show command.

The Outcome – Elastic

In order to confirm your Elastic Deployment is up – you can use cURL or Postman or the Elastic API Console

Wait what? I have just built a database that has an API I can query with Postman???

Y E S !

Check this out

Launch Postman and setup a new Collection called Elastic

Add your username and password (the one-time displayed stuff I told you to write down!) under the Authorization – Type – Basic Auth

Add a Request called Deployment

Copy and Paste your Elastic endpoint ID

Paste it in as a GET in your Deployment Requst

You should get a 200 Status back

And something like this

In Elastic – You can do the same thing!

Launch the API Console

If you leave the field empty and click Submit you get the same status data back

What about our Network Data?!

Now if you pay close attention to the pyATS and Python logs – you will see this call and URL (and status) when you send the data to your Deployment to be Indexed

The 200 means it was successful – but you can take this string into Postman / Elastic API Console !

Back in Postman

Which gives us:

And in the API Console we just GET /devnet_sandbox_nexus9k/_doc/show_ip_interface_brief

Now – check this out – make your next GET against just the base index

In the DevNet Sandbox there is almost 35,000 rows of data ! WHAT !?

The full state as JSON

Over in API Console

Very cool what about the Search Engine??

Well the engine is now populated with Documents and Fields

Which look like this

We can filter on say VRF documents and the search engine magic starts

Now lets check out keyword searches in the Query Tester

VRF

How about an IP Address

What about “Up”?

Visualizations

I want to be open I have not totally developed out any visualizations but I want to show you Kibana and the absolutely incredible dashboards we can create using the Elastic Deployment data

Launch Kibana and then select Kibana again

Now take a look at the incredible things we can do

As I said I have barely scratched the surface but lets look at what we could do in a Dashboard

First thing we have to do is create an Index Pattern

I’ve selected the devnet_sandbox_nexus9k to be my index pattern

Now I have 6670 fields (!) to work with in Kibana Dashboards

Now it becomes, for a beginner like me, a little overwhelming simply because of the vast choices we have to work with this data

Summary

Kibana discovery and learning aside my adventure into network search engines was fun and I learned a lot along the way. I’ve made a video of my development process here if you would like to check it out before you try it yourself.

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ipSpace.net Must Read !

When I was tagged on Twitter about @ioshints (Ivan Pepelnjak (CCIE#1354 Emeritus)) latest blog post I thought somebody was telling me I should read the latest blog

I flagged this as “Hey what a coincidence I was just writing about #chatbots with Discord – I gotta read this later”

Turns out it was my article that was Worth Reading!

Why this is so special to me is that I started my automation journey with an ipSpace.net subscription which was a very key part of my early success with Ansible and Cloud automation specifically. Ivan has also personally helped me write better code and taken a personal interest in my success.

I am so incredibly humbled and thankful for Ivan’s recognition but even more by his commitment to be honest and open with his vast knowledge.

In a lot of ways I am trying to emulate Ivan’s approach and appreciate having a virtual mentor of such quality and capability.

Thanks!

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Discussing the Future of Network Operations with #init6

I had a chance to meet some of my heroes at #init6 including Daren Fulwell!

Make sure you checkout my open source project fueling the demo

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magic_carpet (this link opens in a new window) by automateyournetwork (this link opens in a new window)

Transforming the classic Command-Line Interface

1 Subscriber 5 Watchers 2 Forks Check out this repository on GitHub.com (this link opens in a new window)