Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Python Networking

You're reading from   Mastering Python Networking Your one-stop solution to using Python for network automation, programmability, and DevOps

Arrow left icon
Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781839214677
Length 576 pages
Edition 3rd Edition
Languages
Tools
Concepts
Arrow right icon
Author (1):
Arrow left icon
Eric Chou Eric Chou
Author Profile Icon Eric Chou
Eric Chou
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Review of TCP/IP Protocol Suite and Python 2. Low-Level Network Device Interactions FREE CHAPTER 3. APIs and Intent-Driven Networking 4. The Python Automation Framework – Ansible Basics 5. The Python Automation Framework – Beyond Basics 6. Network Security with Python 7. Network Monitoring with Python – Part 1 8. Network Monitoring with Python – Part 2 9. Building Network Web Services with Python 10. AWS Cloud Networking 11. Azure Cloud Networking 12. Network Data Analysis with Elastic Stack 13. Working with Git 14. Continuous Integration with Jenkins 15. Test-Driven Development for Networks 16. Other Books You May Enjoy
17. Index

Network Data Analysis with Elastic Stack

In Chapter 7, Network Monitoring with Python – Part 1, and Chapter 8, Network Monitoring with Python Part – 2, we discussed the various ways in which we can monitor a network. In the two chapters, we looked at two different approaches for network data collection: we can either retrieve data from network devices such as SNMP or we can listen for the data sent by network devices using flow-based exports. After the data is collected, we will need to store the data in a database, then analyze the data to gain insights in order to decide what the data means. Most of the time, the analyzed results are displayed in a graph, whether that be a line graph, bar graph, or a pie chart. We can use individual tools such as PySNMP, Matplotlib, and Pygal for each of the steps, or we can leverage all-in-one tools such as Cacti or Ntop for monitoring. The tools introduced in those two chapters allowed us to have basic monitoring...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image