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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practice-tests-datadog-fundamentals-certification/
课程评论：没有评论
**课程名称：** Practice Tests: Datadog Fundamentals Certification **课程概览：** 本课程专为准备 Datadog Fundamentals 认证的学员设计，通过提供仿真练习测试，帮助学员提升两方面的能力： 1. **检验知识覆盖面：** 大多数 Datadog 用户可能只熟悉日常工作中使用的功能，而对频率较低的功能了解不多。本练习测试可帮助您评估现有知识的掌握程度，并识别需要进一步学习的领域。每道题目均附有详细解释，并指向相关的 Datadog 文档，以便复习。 2. **熟悉题型模式：** 精通 Datadog 产品知识之余，通过多项选择题形式的认证考试本身也是一项技能。本练习测试旨在帮助您预测官方 Datadog 认证考试的提问方式，以及错误选项如何设计以干扰考生。题目风格和语调上模仿了官方认证，以提供真实的考试体验。 **课程说明：** * 本课程仅包含练习测试，**不提供讲座**。但学员可以通过复习每道题的解释来掌握 Datadog 的核心概念。 * 课程包含多个练习测试，**每个测试包含 90 道题目**，建议在 **2 小时内完成**。 * 练习测试题目均为**多项选择题**，与真实 Datadog 认证考试类型一致。每题只有一个正确答案，可能存在两个或更多干扰选项。您需要选出最能回答问题的选项。选择错误答案**不会扣分**。 **测试涵盖的主题：** * **通用计算知识：** * 理解配置文件类型及其修改 * 熟悉硬件和操作系统概念 * 解读小型程序和 Shell 命令 * 网络知识（用于发送和接收监控数据） * **注意：** 真实 Datadog 认证可能涉及 YAML 格式、基础 Python 编码等看似与 Datadog 无关的内容。这些内容与 Datadog 相关，因为 Datadog Agent 使用 YAML 进行配置，而自定义集成和自定义指标的提交通常用 Python 编写。本练习测试也将包含此类题目。 * **Datadog Agent 配置：** * 为开发配置 Datadog Agent * 在不同基础设施类型中安装 Agent 及其集成 * 使用 API 密钥和应用密钥 * 了解 Agent 使用的主机名、端口和 IP 地址 * 理解 Agent 的自动发现能力 * **数据收集：** * 通过 Datadog 爬虫和 Agent 集成收集数据 * 通过 DogStatsD 和 REST API 收集数据 * 应用数据标记的最佳实践 * **Datadog 中的数据可视化与利用：** * 理解指标（metrics）或时间序列数据 * 阅读主机地图、仪表盘和其他默认视图 * 创建自定义仪表盘 * 使用指标和标签进行查询 * **警报与监控：** * 使用监视器（monitors）进行告警 * **Datadog 监控故障排除：** * 使用 Agent 命令进行故障排除 * 通过读取 Agent 日志文件进行故障排除 * 排查 Agent 配置文件 **课程大纲：** * 无 (This is a practice tests course only so there will be no lectures.)
Are you preparing to be Datadog Fundamentals 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:General computing knowledgeUnderstanding configuration file types and modificationUnderstanding hardware and operating system conceptsInterpreting small programs and shell commandsNetworking for sending and receiving monitoring dataNote: The real Datadog certification may test you on YAML formatting, basic Python coding, etc. which may seem unrelated to Datadog. They are related because the Datadog Agent uses YAML for configuration; and custom integrations and custom metric submission are written in Python. The practice tests here will also test you on these type of questions.Configuring 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 files
