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

The following are the best practices related to creating and maintaining metrics and tags:

  • Make sure that all the tags available through various integrations are enabled. This mainly involves inheriting tags from source platforms such as public cloud services, Docker, and Kubernetes. When complex applications are part of your environment, it is better to have more tags to improve traceability.
  • Add more tags from the Datadog Agent and integrations to partition your metrics data easily and to track the environment, services, and owners efficiently.
  • Have a namespace schema for your custom metrics using periods so that they can be grouped and located easily – for example, mycompany.app1.role1.*.
  • Format the names and values of metrics and tags according to the guidelines. Datadog silently makes changes to names and values if their format is not compliant. Such altered names could cause confusion on the ground as they will be different from the expected...