Book Image

Network Automation with Go

By : Nicolas Leiva, Michael Kashin
Book Image

Network Automation with Go

By: Nicolas Leiva, Michael Kashin

Overview of this book

Go’s built-in first-class concurrency mechanisms make it an ideal choice for long-lived low-bandwidth I/O operations, which are typical requirements of network automation and network operations applications. This book provides a quick overview of Go and hands-on examples within it to help you become proficient with Go for network automation. It’s a practical guide that will teach you how to automate common network operations and build systems using Go. The first part takes you through a general overview, use cases, strengths, and inherent weaknesses of Go to prepare you for a deeper dive into network automation, which is heavily reliant on understanding this programming language. You’ll explore the common network automation areas and challenges, what language features you can use in each of those areas, and the common software tools and packages. To help deepen your understanding, you’ll also work through real-world network automation problems and apply hands-on solutions to them. By the end of this book, you’ll be well-versed with Go and have a solid grasp on network automation.
Table of Contents (18 chapters)
1
Part 1: The Go Programming Language
6
Part 2: Common Tools and Frameworks
10
Part 3: Interacting with APIs

Data plane telemetry aggregation

After collecting and parsing data plane telemetry, we need to think about what to do with it next. Looking at raw data is not always helpful because of the sheer number of flows and lack of any meaningful context. Hence, the next logical step in a telemetry processing pipeline is data enrichment and aggregation.

Telemetry enrichment refers to the process of adding extra metadata to each flow based on some external source of information. For example, these external sources can provide a correlation between a public IP and its country of origin or BGP ASN, or between a private IP and its aggregate subnets or device identity.

Another technique that can help us interpret and reason about the telemetry we collect is aggregation. We can combine different flow records either based on the IP prefix boundary or flow metadata, such as a BGP ASN, to help network operators draw meaningful insights and create high-level views of the data.

You could build...