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

Archiving logs

Having logs at a central location is itself a significant advantage for a business as access to the collected logs is simplified and logs from multiple sources can easily be correlated and analyzed. For monitoring and reporting the aggregated information, it is good enough and there is no need to retain the old logs. However, for compliance purposes and future audits, businesses may need to retain logs for longer periods. As old, raw logs are not needed for active use, those logs could be archived away with the option to retrieve them on demand.

Datadog provides archival options with public cloud storage services as the backend storage infrastructure. To set up an archive for a subset of logs collected by Datadog, the general steps are as follows:

  • Set up an integration with cloud service: This step requires setting up integration with a public cloud storage service: AWS S3, Azure Storage, or Google Cloud Storage.
  • Create a storage bucket: This storage bucket...