NPDC – Network Programmability for the Data Center v1.0

Short Course Description

5 Day

Course Overview

Network Programmability for the Data Center (NPDC) v1.0 is a 5 day instructor led course. This course teaches how to automate an end-to-end Cisco Data Center consisting of Nexus 7000 and 9000 switches. This course also includes Cisco ACI and UCS platforms using state of the art Model Driven API’s. Applying CCIE-style learning methods, the NPDC course places emphasis on learning via hands-on labs and hands-on demonstrations. The terms “proof-by-Python” and “proof-by-JSON or XML” will be used frequently throughout the Data Center training course. It is recommended that students who take this course have the knowledge and skills of a CCNP professional, in addition to having completed the Programming for Network Engineers (PRNE) ELT or equivalent Python programming experience. This NPDC training is intended for Data Center engineers who wish to learn how to deploy network programmability and automation using various Cisco platforms listed below.

Prerequisites

The knowledge and skills that a learner should have before attending this course are as follows:

• CCNP or Equivalent Experience
• Complete the Programming for Network Engineers (PRNE) ELT or equivalent Python programming experience

Course Objectives

Upon completing this course, the learner will be able to meet these overall objectives:

• Use Linux tools that empower network programmers
• Write and troubleshoot Python scripts in the specialized area of Network Programmability
• Understand and interact with Data Models (both the Cisco Managed Object Model and YANG models) on Nexus switches, the ACI APIC and the UCS
• Understand and interact with REST, NETCONF and RESTCONF API’s on Nexus switches, the ACI APIC and the UCS
• Understand and interact with XML and JSON on Nexus switches, the ACI APIC and the UCS
• Learn how to use DevOps tools such as GitHub, VIRL and services offered by Cisco DevNet
• Survey the capabilities of OpenStack and Cisco CloudCenter