Book Image

Mastering Python Networking - Third Edition

By : Eric Chou
Book Image

Mastering Python Networking - Third 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, Third edition, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This new edition is completely revised and updated to work with Python 3. In addition to new chapters on network data analysis with ELK stack (Elasticsearch, Logstash, Kibana, and Beats) and Azure Cloud Networking, it includes updates on using newer libraries such as pyATS and Nornir, as well as Ansible 2.8. 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 Azure and AWS Cloud networking. Finally, you will use Jenkins for continuous integration as well as testing tools to verify your network.
Table of Contents (18 chapters)
16
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17
Index

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 in order 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.

Before we dig deeper into the different components of the Elastic Stack, it is helpful to look at an example that spans across Logstash, Elasticsearch, and Kibana. By going over this end-to-end example, we will become familiar with the function that each component provides. When we look at each component in more detail later in the chapter, we will be able to compartmentalize where the particular component...