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

Best practices

Between the Datadog-provided integrations and the hooks it provides to roll out your own custom integrations, there are many options available to you and so it's better to follow the best practices instead of implementing something that works but is suboptimal:

  • Explore all the Datadog-provided integrations fully and check whether you could meet the monitoring requirements using those. Custom code and configurations are costly to develop, error-prone, and hard to deploy and maintain, in the context of monitoring, and you should consider writing custom code as the last resort.
  • If Datadog-supported integrations are not readily available, check in the big collection of community-maintained integrations.
  • If you need to tweak a community-maintained integration to get it working for you, consider collaborating on that project and commit the changes publicly, as that will help to obtain useful feedback from the Datadog community.
  • Come up with a strategy...