Datadog Cloud Monitoring Quick Start Guide: Proactively create dashboards, write scripts, manage alerts, and monitor containers using Datadog

Description

A comprehensive guide to rolling out Datadog to monitor infrastructure and applications running in both cloud and datacenter environments Key FeaturesLearn Datadog to proactively monitor your infrastructure and cloud servicesUse Datadog as a platform for aggregating monitoring efforts in your organizationLeverage Datadog's alerting service to implement on-call and site reliability engineering (SRE) processesBook Description 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. What you will learnUnderstand monitoring fundamentals, including metrics, monitors, alerts, and thresholdsImplement core monitoring requirements using Datadog featuresExplore Datadog's integration with cloud platforms and toolsExtend Datadog using custom scripting and standards such as JMX and StatsDDiscover how proactive monitoring can be rolled out using various Datadog featuresUnderstand how Datadog can be used to monitor microservices in both Docker and Kubernetes environmentsGet to grips with advanced Datadog features such as APM and Security MonitoringWho this book is for This book is for DevOps engineers, site reliability engineers (SREs), IT Production engineers, software developers and architects, cloud engineers, system administrators, and anyone looking to monitor and visualize their infrastructure and applications with Datadog. Basic working knowledge of cloud and infrastructure is useful. Working experience of Linux distribution and some scripting knowledge is required to fully take advantage of the material provided in the book. Table of ContentsIntroduction to MonitoringDatadog AgentDatadog DashboardAccount ManagementMetrics, Events and TagsMonitoring InfrastructureMonitors and AlertsIntegrating with Platform ComponentsUsing Datadog HTTP APIWorking with Monitoring StandardsIntegrating with DatadogAdvanced Container MonitoringLog Management using DatadogMiscellaneous Monitoring Features Datadog Cloud Monitoring Quick Start Guide Contributors About the author About the reviewer Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews Section 1: Getting Started with Datadog Chapter 1: Introduction to Monitoring Technical requirements Why monitoring? Proactive monitoring Implementing a comprehensive monitoring solution Setting up alerts to warn of impending issues Having a feedback loop Monitoring use cases All in a data center Application in a data center with cloud monitoring All in the cloud Monitoring terminology and processes Host Agent Metrics Up/down status Check Threshold Monitor Alert Alert recipient Severity level Notification Downtime Event Incident On call Runbook Types of monitoring Infrastructure monitoring Platform monitoring Application monitoring Business monitoring Last-mile monitoring Log aggregation Meta-monitoring Noncore monitoring Overview of monitoring tools On-premises tools SaaS solutions Cloud-native tools Summary Chapter 2: Deploying the Datadog Agent Technical requirements Installing the Datadog Agent Runtime configurations Steps for installing the agent Agent components Agent as a container Deploying the agent – use cases All on the hosts Agent on the host monitoring containers Agent running as a container Advanced agent configuration Best practices Summary Chapter 3: The Datadog Dashboard Technical requirements Infrastructure List Events Metrics Explorer Dashboards The main Integrations menu Integrations APIs Agent Embeds Monitors Creating a new metric monitor Advanced features Summary Chapter 4: Account Management Technical requirements Managing users Granting custom access using roles Setting up organizations Implementing Single Sign-On Managing API and application keys Tracking usage Best practices Summary Chapter 5: Metrics, Events, and Tags Technical requirements Understanding metrics in Datadog Metric data Flush time interval Metric type Metric unit Query Tagging Datadog resources Defining tags Tagging methods Customizing host tag Tagging integration metrics Tags from microservices Filtering using tags Defining custom metrics Monitoring event streams Searching events Notifications for events Generating events Best practices Summary Chapter 6: Monitoring Infrastructure Technical requirements Inventorying the hosts CPU usage Load averages Available swap Disk latency Memory breakdown Disk usage Network traffic Listing containers Viewing system processes Monitoring serverless computing resources Best practices Summary Chapter 7: Monitors and Alerts Technical requirements Setting up monitors Managing monitors Distributing notifications Configuring downtime Best practices Summary Section 2: Extending Datadog Chapter 8: Integrating with Platform Components Technical requirements Configuring an integration Tagging an integration Reviewing supported integrations Implementing custom checks Best practices Summary Chapter 9: Using the Datadog REST API Technical requirements Scripting Datadog curl Python Reviewing Datadog APIs Public cloud integration Dashboards Downtime Events Hosts Metrics Monitors Host tags Programming with Datadog APIs The problem Posting metric data and an event Creating a monitor Querying the events stream Best practices Summary Chapter 10: Working with Monitoring Standards Technical requirements Monitoring networks using SNMP Consuming application metrics using JMX Cassandra as a Java application Using Cassandra integration Accessing the Cassandra JMX interface Working with the DogStatsD interface Publishing metrics Posting events Best practices Summary Chapter 11: Integrating with Datadog Technical requirements Using client libraries REST API-based client libraries DogStatsD client libraries Evaluating community projects dog-watcher by Brightcove kennel Managing monitors using Terraform Ansible modules and integration Developing integrations Prerequisites Setting up the tooling Creating an integration folder Running tests Building a configuration file Building a package Deploying an integration Best practices Summary Section 3: Advanced Monitoring Chapter 12: Monitoring Containers Technical requirements Collecting Docker logs Monitoring Kubernetes Installing the Datadog Agent Using Live Containers Viewing logs using Live Tail Searching container data Best practices Summary Chapter 13: Managing Logs Using Datadog Technical requirements Collecting logs Collecting logs from public cloud services Shipping logs from containers Shipping logs from hosts Filtering logs Scrubbing sensitive data from logs Processing logs Archiving logs Searching logs Best practices Summary Chapter 14: Miscellaneous Monitoring Topics Technical requirements Application Performance Monitoring (APM) Sending traces to Datadog Profiling an application Service Map Implementing observability Synthetic monitoring Security monitoring Sourcing the logs Defining security rules Monitoring security signals Best practices Summary Why subscribe? 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