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

We reviewed the Datadog APIs and learned the basics of how they are called from curl and Python. Now, let's see what the best practices are for using the APIs for automating monitoring tasks:

  • As mentioned earlier, try to leverage existing integrations as much as possible before writing your own code using Datadog APIs. This is mainly because the maintenance of custom code in the long term is expensive in general.
  • If you must write code using APIs, start maintaining it in a source code control system from the very beginning.
  • As we have seen with the sample programs, consider pulling useful monitoring information from other internal systems and publishing it on the Datadog platform as metrics and events using the APIs. Datadog is an excellent platform for aggregating information from disparate sources and it should be leveraged to extend the overall monitoring capability of the organization.
  • APIs can be used to pull data out of Datadog for loading...