Ultimate Practice Tests: All Datadog Certifications 2024

Are you preparing to be Datadog certified? Taking the practice tests here will help you in two ways:

1. Test the coverage of your knowledge - Most Datadog users master the features that they use in their day-to-day work but are less familiar with functionalities that they need less frequently. You can use the practice test to test how much you already know and which topics you need to learn more about. Each question in the practice tests includes an explanation and/or points to the relevant Datadog documentation for you to review.

2. Familiarize you with the question patterns - Getting certified through a multiple choice test is a skill on top of your Datadog product knowledge. You can use the practice test to help anticipate how questions are phrased and how wrong choices are presented to distract you from the correct answer. The questions are designed to mimic the tone and style of the official Datadog certification to simulate the testing experience.

Note: This is a practice tests course only so there will be no lectures. Although there are no lectures, you can master Datadog concepts by reviewing the explanation on each question.

This course contains multiple practice tests with 90 questions each. Each practice test should be taken in under 2 hours.

The practice test only contains multiple choice type of question similar to the real Datadog certification. There's one correct response and two or more incorrect responses. You need to select the response that best answers the question posed. There are no deductions for choosing incorrect answers.

The practice tests will test your knowledge on the following topics.

Datadog Fundamentals

• General computing knowledge

  • Understanding configuration file types and modification

  • Understanding hardware and operating system concepts

  • Interpreting small programs and shell commands

  • Networking for sending and receiving monitoring data

• Configuring the Datadog Agent for development

  • Installing the Agent and its integrations in different infrastructure types

  • Using API keys and application keys

  • Knowing the hostnames, ports, and IP addresses used by the Agent

  • Understanding the Agent's auto-discovery capabilities

• Collecting data for monitoring

  • Collecting data through Datadog crawlers and Agent integrations

  • Collecting data through DogStatsD and rest API

  • Applying best practices for tagging data

  • Understanding metrics or timeseries data in Datadog

• Visualizing and utilizing data

  • Reading the host map, dashboards, and other default views

  • Creating custom dashboards

  • Querying with metrics and tags

  • Alerting with monitors

• Troubleshooting Datadog monitoring

  • Using Agent commands for troubleshooting

  • Reading Agent log files for troubleshooting

  • Investigating Agent configuration files

Datadog Log Management Fundamentals

• General log management knowledge

  • Justifying the rationale of logging systems

  • Understanding logging sources and formats

  • Addressing common logging use cases

• Collecting logs

  • Enabling log collection

  • Filtering logs to be collected

  • Obfuscating sensitive data in logs

• Parsing and processing logs

  • Using log processors and log pipelines

  • Using standard attributes

  • Understanding the composition of a log

• Searching and filtering logs

  • Understanding the Live Tail and Log Explorer views

  • Applying log explorer functionalities

  • Using the Datadog log search syntax

• Visualising and analyzing logs

  • Filtering and/or excluding logs for analysis

  • Using different log aggregations

  • Visualising and communicating information from logs

  • Exporting logs out of Datadog

• Operating with log management features

  • Ingesting and indexing logs

  • Archiving and rehydrating logs

  • Creating monitors and alerts

  • Generating metrics from logs

  • Handling sensitive data in logs

  • Controlling access to logs

• Troubleshooting logs setup issues

  • Troubleshooting Datadog Agent issues

  • Troubleshooting log ingestion issues

Datadog APM and Distributed Tracing Fundamentals

• General APM and Distributed Tracing knowledge

  • Justifying the rationale of APM

  • Understanding Datadog's approach to APM, including tagging and retention

  • Understanding various tracing architectures and different types of tracers

• Collecting distributed traces

  • Familiarise with Datadog tracing libraries, instrumentation types, and Datadog Agent

  • Distinguishing sampling versus retention

  • Applying best practices in APM data security

  • Correlating trace, logs, RUM, and profiles

• Visualising APM data

  • Understanding various service views and search syntax

  • Navigating flame graphs, error and deployment tracking, and span summary

  • Differentiating live and retained traces

  • Dashboarding service performance, generated metrics, and Apdex scores

• Troubleshooting and alerting on APM data

  • Troubleshooting slow endpoints

  • Applying trace search during outages

  • Creating monitors and SLOs