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Are you preparing to be Datadog certified? Taking the practice tests here will help you in two ways: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.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 FundamentalsGeneral computing knowledgeUnderstanding configuration file types and modificationUnderstanding hardware and operating system conceptsInterpreting small programs and shell commandsNetworking for sending and receiving monitoring dataConfiguring the Datadog Agent for developmentInstalling the Agent and its integrations in different infrastructure typesUsing API keys and application keysKnowing the hostnames, ports, and IP addresses used by the AgentUnderstanding the Agent's auto-discovery capabilitiesCollecting data for monitoringCollecting data through Datadog crawlers and Agent integrationsCollecting data through DogStatsD and rest APIApplying best practices for tagging dataUnderstanding metrics or timeseries data in DatadogVisualizing and utilizing dataReading the host map, dashboards, and other default viewsCreating custom dashboardsQuerying with metrics and tagsAlerting with monitorsTroubleshooting Datadog monitoringUsing Agent commands for troubleshootingReading Agent log files for troubleshootingInvestigating Agent configuration filesDatadog Log Management FundamentalsGeneral log management knowledgeJustifying the rationale of logging systemsUnderstanding logging sources and formatsAddressing common logging use casesCollecting logsEnabling log collectionFiltering logs to be collectedObfuscating sensitive data in logsParsing and processing logsUsing log processors and log pipelinesUsing standard attributesUnderstanding the composition of a logSearching and filtering logsUnderstanding the Live Tail and Log Explorer viewsApplying log explorer functionalitiesUsing the Datadog log search syntaxVisualising and analyzing logsFiltering and/or excluding logs for analysisUsing different log aggregationsVisualising and communicating information from logsExporting logs out of DatadogOperating with log management featuresIngesting and indexing logsArchiving and rehydrating logsCreating monitors and alertsGenerating metrics from logsHandling sensitive data in logsControlling access to logsTroubleshooting logs setup issuesTroubleshooting Datadog Agent issuesTroubleshooting log ingestion issuesDatadog APM and Distributed Tracing FundamentalsGeneral APM and Distributed Tracing knowledgeJustifying the rationale of APMUnderstanding Datadog's approach to APM, including tagging and retentionUnderstanding various tracing architectures and different types of tracersCollecting distributed tracesFamiliarise with Datadog tracing libraries, instrumentation types, and Datadog AgentDistinguishing sampling versus retentionApplying best practices in APM data securityCorrelating trace, logs, RUM, and profilesVisualising APM dataUnderstanding various service views and search syntaxNavigating flame graphs, error and deployment tracking, and span summaryDifferentiating live and retained tracesDashboarding service performance, generated metrics, and Apdex scoresTroubleshooting and alerting on APM dataTroubleshooting slow endpointsApplying trace search during outagesCreating monitors and SLOs

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