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)
1
Section 1: Getting Started with Datadog
9
Section 2: Extending Datadog
14
Section 3: Advanced Monitoring

What this book covers

Chapter 1, Introduction to Monitoring, describes industry-standard monitoring terminology and defines different types of monitoring that are in practice. It also provides an overview of popular monitoring tools and platforms currently in use.

Chapter 2, Deploying the Datadog Agent, discusses the workings of the Datadog Agent and its role in the Datadog monitoring platform. The process of installing the Datadog Agent is explained with sample steps.

Chapter 3, Datadog Dashboard, covers the Datadog dashboard that Datadog users and administrators use. This chapter describes various features of the Datadog UI that a regular user of Datadog would use on a regular basis.

Chapter 4, Account Management, explains various administrative tasks that a Datadog user would perform to maintain their account.

Chapter 5, Metrics, Events, and Tags, describes metrics and tags, two of the most important concepts that Datadog relies on for publishing, monitoring statuses, and organizing data and resources. It also covers monitoring events.

Chapter 6, Monitoring Infrastructure, covers in detail what Datadog does in terms of infrastructure monitoring, an important category of monitoring. It also describes different infrastructure types and components and the related group of metrics that Datadog publishes.

Chapter 7, Monitors and Alerts, covers monitors and alerts, which are essential parts of any monitoring tool. This chapter explores in detail how these concepts are implemented in Datadog.

Chapter 8, Integrating with Platform Components, describes in detail the multiple ways to integrate Datadog with other infrastructure and software components, with examples.

Chapter 9, Using the Datadog REST API, covers the Datadog REST API, which is used to access Datadog programmatically. This chapter describes typical use cases explaining the use of the Datadog API, complete with a tutorial.

Chapter 10, Working with Monitoring Standards, looks at industry standards for integrating monitoring tools with applications. In this chapter, three integration standards, SNMP, JMX, and StatsD, are discussed with the help of examples.

Chapter 11, Integrating with Datadog, looks at some of the commonly used official and community-developed programming libraries that are available to integrate applications directly with Datadog.

Chapter 12, Monitoring Containers, discusses the Datadog tools available for monitoring containers, in both Docker and Kubernetes environments.

Chapter 13, Managing Logs Using Datadog, covers the standard log aggregation, indexing, and search features provided by log management, which is a recent addition to the Datadog platform.

Chapter 14, Miscellaneous Monitoring Topics, discusses some of the new features, such as APM, security monitoring, observability, and synthetic monitoring, on the Datadog platform, which continues to grow.