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Mastering Python Networking

Mastering Python Networking

By : Eric Chou
4.5 (89)
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Mastering Python Networking

Mastering Python Networking

4.5 (89)
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.
Table of Contents (19 chapters)
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6
Network Security with Python
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7
Network Monitoring with Python – Part 1
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8
Network Monitoring with Python – Part 2
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10
Introduction to Async IO
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16
Test-Driven Development for Networks
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17
Other Books You May Enjoy
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18
Index
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Data ingestion with Beats

As good as Logstash is, the data ingestion process can get complicated and hard to scale. If we expand on our network log example, we can see that even with just network logs, it can get complicated trying to parse different log formats from IOS routers, NXOS routers, ASA firewalls, Meraki wireless controllers, and more. What if we need to ingest log data from Apache web logs, server host health, and security information? What about data formats such as NetFlow, SNMP, and counters? The more data we need to aggregate, the more complicated it can get.

While we cannot completely get away from aggregation and the complexity of data ingestion, the current trend is to move toward a more lightweight, single-purpose agent that sits as close to the data source as possible. For example, we can have a data collection agent installed directly on our Apache server specialized in collecting web log data; or we can have a host that only collects, aggregates, and organizes...

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