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

Reviewing supported integrations

It has been already mentioned that Datadog provides integrations for a lot of third-party platform components. Some of them, such as Apache, NGINX, Docker, MySQL, and the like, are more important than the rest because of their ubiquitous use across a variety of software applications. In this section, we will look at the important integrations and call out points of any importance.

Datadog provides three different options for integrating platform components:

  • Agent-based: In the example we saw earlier in this chapter, the Datadog Agent configuration had to be updated to enable the integration. That is required because the platform component, NGINX in the example, runs on a host. It could be run as a microservice also and yet an agent is needed to monitor that environment. Essentially, the integration in that case is managed by the local agent. The Datadog Agent is shipped with official integrations and they are readily available as we saw in...