Course Overview
CDP Public Cloud Administrator Training provides participants with a comprehensive understanding of all the steps required to configure, operate, and maintain CDP Public Cloud instances. This four (4) day instructor-led course covers everything from setup to configuring various data services to execute workloads on the cloud on all major cloud providers using Cloudera Management Console. It also covers various configuration options using the web interface and automation scenarios using Ansible. On the optimization side, it covers load balancing and tuning CDP PC instances. This Cloudera training course is the best preparation for the real-world challenges faced by administrators running CDP Public Cloud.
Prerequisites
This course is best suited to cloud systems administrators and operators who have at least basic Linux and AWS/Azure/GCP experience. Prior knowledge of CDP, nor earlier platforms such as Cloudera’s CDH or Hortonworks HDP, is not required but will be helpful.
Students are highly recommended to go through the free OnDemand courses to make the best of the instructor-led classroom learning experience:
- Introducing AWS for CDP Public Cloud (FREE!)
- Cloudera Essentials for CDP (FREE!)
- Introducing - CDP Public Cloud Administration (FREE!)
- Quickstart: Azure for CDP (FREE!)
- Quickstart: AWS for CDP (FREE!)
Course Objectives
Through instructor-led discussion and interactive, hands-on exercises, you will learn how to:
- Evaluate and select the appropriate deployment option
- Setup CDP Public Cloud using Cloudera Management Console
- Setup and configure various data services
- Configure and monitor instances using Cloudera Manager
- Optimize cluster performance and security
- Detect, troubleshoot, and repair problems with the cluster
- Auto scale Data Hub clusters and Data Services
Course Content
- Installation Overview (Quick Start)
- CDP Architecture
- Control Plane Overview
- CDP CLI (Command Line Interface)
- Managing CDP Access
- Data Hubs Overview
- Managing Data Hubs
- Data Services Overview
- DataFlow
- Data Engineering
- Data Warehouse
- Operational Database
- Machine Learning
- Monitoring and Management
- Data Management
- Observability