The Datadog Learning Center provides free, interactive courses to help you get started with or learn more about different Datadog features and their use cases. If you’re new to Datadog or would like to direct your studies to a specific topic, the Learning Center offers Learning Paths, which are recommended groupings of courses based on a persona, a product, or a related set of skills.
We’re excited to announce 14 new Learning Paths in our general curriculum and three new Learning Paths for certification preparation that feature new and updated course material. To help you quickly discover the courses that are most relevant to your needs, Learning Paths are now separated into the following categories:
In this post, we’ll discuss these new learning paths and how they can help you better align your coursework and your learning goals.
Our Universal, Persona-Based, and Product-Based Learning Paths that make up the Learning Center’s general curriculum are the best place to familiarize yourself with key Datadog products and workflows. In this section, we’ll cover each of these three Learning Path categories and what you can expect from their courses.
If you’re new to Datadog or want to build a strong foundation before jumping into more advanced courses, we recommend that you begin with our Universal Learning Paths. The Core Skills Learning Path introduces you to core Datadog workflows, such as searching for and analyzing metrics data, creating dashboards to help you visualize your services, and configuring monitors that alert you when issues arise. If you’re onboarding Datadog for your organization, this is the perfect starting point to help you get started with baseline monitoring and alerts for your environment.
The Datadog Agent is the key component that helps you visualize granular metrics from your applications and correlate telemetry data across your environment. Our Configuration Learning Path teaches how to configure and optimize the Datadog Agent across diverse environments so you can make the most out of our Agent-enabled features. This includes courses on how to run the Agent on a host versus a container, how to get started with our 850+ Agent integrations, and how to navigate our Software Catalog by using Universal Service Tags.
One of the frequent requests we’ve received is for course recommendations based on personas. To address this, we’ve implemented Persona-Based Learning Paths, with the following six engineering personas currently available and more in active development: backend, frontend, SRE, application security, cloud security, and cloud security with a focus on Cloud SIEM.
Persona-Based Learning Paths enable you to develop your understanding of the Datadog platform in ways that most directly relate to your job. For example, in the Application Security Engineer Learning Path, we offer courses that teach you not only how to detect common attacks against your web application with our out-of-the-box detection rules, but also how to defend against them in real time by using Remote Configuration to update your in-app web application firewall (WAF) to block traffic that matches patterns from known attacks.
Select Product-Based Learning Paths were previously available in the Learning Center, but we’ve now expanded them to include new Learning Paths that focus on how to effectively visualize and customize your dashboards and how to detect, investigate, and respond to application attacks and security threats. Additionally, we’ve enriched our existing Product-Based Learning Paths with new and advanced course materials that enable you to dive deeper into the products you may already be using on a daily basis. For example, the Log Querying & Analytics Learning Path (previously a part of Log Fundamentals) now dives deeper into building complex log queries and aggregations, enhancing your queries with reference tables, and querying for one set of logs within a secondary query. These advanced courses all include hands-on lab exercises so that you can validate these workflows by using practice examples before applying them to your production environment.
After completing each of these Learning Paths, you’ll receive a Credly badge as proof of completion. If you’d like to be rewarded for demonstrating a deeper understanding of the Datadog platform, consider enrolling for a Datadog Certification exam, which we’ll discuss in the following section.
If you want to demonstrate a deeper proficiency in the Datadog platform and knowledge of industry-standard monitoring practices, Datadog currently offers certification exams for three different subject areas: Datadog Fundamentals, Log Management Fundamentals, and APM and Distributed Tracing Fundamentals.
The Datadog Learning Center now offers Certification Preparation Learning Paths for each of the three certification exams. These Learning Paths group together course materials that are relevant to the topics covered in their corresponding exams, eliminating some of the guesswork involved when you browse the Learning Center’s library for relevant study material. When you prepare for each exam, we also recommend that you review the exam guide—which contains information about the scope and format of the exam, along with additional recommended preparation material—and take our practice exam that features 25 multiple-choice questions similar to the ones you will find on the official certification exam.
Note: While the Certification Preparation Learning Paths serve as the perfect starting point for your exam preparation, they are not intended to be comprehensive. Completing them does not guarantee a passing score.
The Datadog Learning Center offers interactive course material for users of all different backgrounds and experience levels. By enrolling in our Learning Paths today, you can begin to deepen your understanding of the topics most relevant to your role and the products you work with. If you’re interested in taking a Datadog Certification exam, you can learn more in our blog post.
If you don’t already have a Datadog account, sign up for a free 14-day trial today.
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。