Teh Guide

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====== Datadog Fundamentals Exam Guide (January 2025) ======

From: https://www.datadoghq.com/pdf/datadog-fundamentals-exam-guide-jan25.pdf

===== 1. Introduction =====

The Datadog Fundamentals certification assesses individuals’ foundational knowledge of the Datadog ecosystem. It covers a broad range of topics, from Linux command line basics to metric visualization strategies. Certification earners know how to use Datadog effectively for common use cases and are well equipped to learn more advanced topics specific to their roles.

This exam will test and validate knowledge on the following topics:

  * Computer fundamentals such as CPUs, RAM, data storage
  * Linux operating system basics
  * YAML, JSON, Python, and shell scripts
  * Networking basics including IP addresses and protocols such as HTTP, TCP, and UDP
  * Install and configure the Datadog Agent in multiple environments
  * Install and configure Datadog integrations
  * Common techniques for troubleshooting Datadog
  * Aggregate and visualize data in the Datadog application
  * Search and filter events, logs, and metrics using tags and facets
  * Create Datadog monitors with targeted notifications
  * Familiarity with the Datadog API

Each exam has a maximum seat time of 2 hours.

===== 2. Target Candidates =====

Candidates should be entry-level Datadog users who understand observability principles. They should be frequent users of Datadog’s core products and features.

**Recommended Datadog Knowledge:**

  * General computing knowledge (CPU, RAM, Data storage, etc.)
  * Linux Basics
  * Reading YAML, JSON, Python, Shell Scripts
  * Basic Networking
  * Datadog:
    * Agent
      * Configuration
      * Commands
    * Integrations
    * API
    * Metrics
    * Tags
    * Host Map
    * Monitors
    * Log Search & Filter
    * Metric Search & Filter

===== 3. Out of Scope =====

The following is a list (non-exhaustive) of specific job tasks that earners will not be required to perform:

  * Programming
  * Systems Architecture
  * Testing

===== 4. Exam Content and Outline =====

==== Question Type ====

The exam only contains one type of question:

  * **Multiple choice:** Has one correct response and two or more incorrect responses (distractors)

Select the response that best answers the question posed. Incorrect answers, also known as distractors, are options that can be a plausible response for the question’s content area. Unanswered questions are scored as incorrect.

The exam includes 75 questions that will affect your score.

==== Pre-Test Items ====

The exam includes 15 pre-test (unscored) questions that do not affect your score. Datadog collects information about candidate performance on pre-test questions to evaluate them for future use on exam forms. Pre-test questions are not identified to the candidate on the exam.

==== Content Outline ====

The Exam Content Outline includes the knowledge domains and related subdomains of content on the exam.

=== Essential Concepts ===

  * Config File Modification
  * Hardware Concepts
  * Metadata
  * Networking
  * Datadog Observability

=== Infrastructure Development ===

  * Agent Installation
  * API Key
  * Application Key
  * Running the Agent
  * Agent Hostname

=== Networking & Agent Configuration ===

  * Datadog Ports
  * Datadog IP Addresses
  * Auto-discovery

=== Data Collection ===

  * DogStatsD
  * Crawlers
  * Agent Integrations
  * API Endpoints
  * Tagging Best Practices
  * Metrics & Timeseries

=== Troubleshooting Datadog ===

  * Agent Commands
  * Agent Logs
  * Agent Config Files

=== Data Visualization & Utilization ===

  * Host Map
  * Dashboards
  * Using Metrics
  * Using Tags
  * Monitors and Alerts

===== 5. Study and Preparation =====

//TehGuide note: see [[DD Fundamentals Certification Study Guide]]//

It is expected that you have done some preparation for the exam. This can include not only using the platform but also taking some of Datadog’s recommended courses and reading relevant documentation. Below please find a list of recommended materials to go over to get you started.

==== Courses ====

  * Intro to Datadog: Dev + SRE
  * Introduction to Observability

==== Documentation ====

  * Getting Started
  * Datadog Agent
  * Metrics
  * Infrastructure List
  * API and Application Keys
  * Integrations
  * Docker Daemon
  * Query to the graph
  * Docker Agent
  * Metrics API
  * Monitor types
  * DogStatsD
  * ddtrace
  * Canonical Hostnames


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For more information and resources, you can visit the [[https://www.datadoghq.com/certification/overview/|Datadog Certification Overview]] and the [[https://learn.datadoghq.com/bundles/datadog-fundamentals-certification-learning-path|Datadog Fundamentals Certification Learning Path]].