Book Image

Mastering Python Networking - Fourth Edition

By : Eric Chou

Book Image

Mastering Python Networking - Fourth Edition

By: Eric Chou

Overview of this book

Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In Mastering Python Networking, Fourth edition, you'll embark on a Python-based journey to transition from a traditional network engineer to a network developer ready for the next generation of networks. This new edition is completely revised and updated to work with the latest Python features and DevOps frameworks. In addition to new chapters on introducing Docker containers and Python 3 Async IO for network engineers, each chapter is updated with the latest libraries with working examples to ensure compatibility and understanding of the concepts. Starting with a basic overview of Python, the book teaches you how it can interact with both legacy and API-enabled network devices. You will learn to leverage high-level Python packages and frameworks to perform network automation tasks, monitoring, management, and enhanced network security, followed by AWS and Azure cloud networking. You will use Git for code management, GitLab for continuous integration, and Python-based testing tools to verify your network.

Preface

Who this book is for

What this book covers

To get the most out of this book

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Download a free PDF copy of this book

Review of TCP/IP Protocol Suite and Python

Review of TCP/IP Protocol Suite and Python

An overview of the Internet

The client-server model

Network protocol suites

Python language overview

Free Chapter

Low-Level Network Device Interactions

Low-Level Network Device Interactions

The challenges of the CLI

Constructing a Virtual lab

Python virtual environment

Python pexpect library

The Python Paramiko library

The Netmiko library

The Nornir framework

APIs and Intent-Driven Networking

APIs and Intent-Driven Networking

Infrastructure-as-Code (IaC)

Cisco API examples

Cisco Meraki controller

The Python API for Juniper Networks

The Arista Python API

Other libraries

The Python Automation Framework – Ansible

The Python Automation Framework – Ansible

Ansible – A More Declarative Framework

Our First Ansible Network Example

The Advantages of Ansible

Ansible Content Collections

More Ansible Network Examples

Docker Containers for Network Engineers

Docker Containers for Network Engineers

Docker Overview

Building Python applications in Docker

Container networking

Containers in the network engineering field

Docker and Kubernetes

Network Security with Python

Network Security with Python

The Syslog search

Further reading

Network Monitoring with Python – Part 1

Network Monitoring with Python – Part 1

Python for Data Visualization

Python for Cacti

Network Monitoring with Python – Part 2

Network Monitoring with Python – Part 2

Flow-based monitoring

ntop traffic monitoring

Building Network Web Services with Python

Building Network Web Services with Python

Comparing Python web frameworks

Flask and lab setup

Introduction to Flask

Network resource API

Network dynamic operations

Authentication and Authorization

Running Flask in containers

Introduction to Async IO

Introduction to Async IO

Asynchronous operations overview

Python asyncio module

The Scrapli project

AWS Cloud Networking

AWS Cloud Networking

AWS network overview

Virtual Private Cloud

Direct Connect and VPN

Network scaling services

Other AWS network services

Azure Cloud Networking

Azure Cloud Networking

Azure and AWS network service comparison

Azure administration and APIs

Azure global infrastructure

Azure virtual networks

Azure ExpressRoute

Azure network load balancers

Other Azure network services

Network Data Analysis with Elastic Stack

Network Data Analysis with Elastic Stack

What is the Elastic Stack?

Elastic Stack as a service

First End-to-End example

Elasticsearch with a Python client

Data ingestion with Logstash

Data ingestion with Beats

Search with Elasticsearch

Data visualization with Kibana

Working with Git

Working with Git

Content management considerations and Git

Introduction to Git

Git Usage Examples

Git with Python

Automating Configuration Backup

Collaborating with Git

Continuous Integration with GitLab

Continuous Integration with GitLab

The traditional change management process

Introduction to continuous integration

Installing GitLab

First GitLab example

GitLab network example

Test-Driven Development for Networks

Test-Driven Development for Networks

Test-driven development overview

Topology as code

Writing tests for networking

pyATS and Genie

Other Books You May Enjoy

Other Books You May Enjoy

Index

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First End-to-End example

One of the most common pieces of feedback from people new to Elastic Stack is the amount of detail you need to understand to get started. To get the first usable record in the Elastic Stack, the user needs to build a cluster, allocate master and data nodes, ingest the data, create the index, and manage it via the web or command line interface. Over the years, Elastic Stack has simplified the installation process, improved its documentation, and created sample datasets for new users to get familiar with the tools before using the stack in production.

Tip. Running the components in Docker containers helps with some of the pain in installation but increases complexity in maintenance. It is a balancing act to choose between running them in a virtual machine vs. containers.

Before we dig deeper into the different components of the Elastic Stack, it is helpful to look at an example that spans Logstash, Elasticsearch, and Kibana. By going over this end-to-end...