Book Image

Datadog Cloud Monitoring Quick Start Guide

By : Thomas Kurian Theakanath
Book Image

Datadog Cloud Monitoring Quick Start Guide

By: Thomas Kurian Theakanath

Overview of this book

Datadog is an essential cloud monitoring and operational analytics tool which enables the monitoring of servers, virtual machines, containers, databases, third-party tools, and application services. IT and DevOps teams can easily leverage Datadog to monitor infrastructure and cloud services, and this book will show you how. The book starts by describing basic monitoring concepts and types of monitoring that are rolled out in a large-scale IT production engineering environment. Moving on, the book covers how standard monitoring features are implemented on the Datadog platform and how they can be rolled out in a real-world production environment. As you advance, you'll discover how Datadog is integrated with popular software components that are used to build cloud platforms. The book also provides details on how to use monitoring standards such as Java Management Extensions (JMX) and StatsD to extend the Datadog platform. Finally, you'll get to grips with monitoring fundamentals, learn how monitoring can be rolled out using Datadog proactively, and find out how to extend and customize the Datadog platform. By the end of this Datadog book, you will have gained the skills needed to monitor your cloud infrastructure and the software applications running on it using Datadog.
Table of Contents (19 chapters)
Section 1: Getting Started with Datadog
Section 2: Extending Datadog
Section 3: Advanced Monitoring


By now, you should be aware of all the important integration options available in Datadog for a variety of use cases; let's recap what we covered in this chapter specifically.

Many Datadog client libraries targeting popular programming languages are available, both officially maintained and at the community level. There are two types of client libraries – ones that provide a language wrapper to the Datadog REST API and libraries that provide support interfacing with Datadog via the StatsD-compatible DogStasD service. Also, there are community-level efforts to integrate with Datadog that are available on GitHub.

There are other types of Datadog client libraries that are not discussed here, such as APM and distributed tracing libraries, libraries that support serverless computing resources such as AWS Lambda, and client libraries that specifically target the log management feature of Datadog. The usage of these libraries is not different from how the core API...