Automating ONTAP REST APIs with Python (RSTPY)

 

Course Overview

Discover how to automate administration of a NetApp® ONTAP® based storage system by using modern ONTAP REST APIs and Python. Explore how to use the Python client library (PCL) in your Python program to automate storage administration tasks. Also, learn how to configure your system for SMB, NFS, Simple Storage Service (S3), and SAN protocols by writing Python programs.

Who should attend

Sales, customer success manager, solutions engineer (SE), architect, support engineer, implementation engineer, and professional services

Prerequisites

Python programming experience (required) ONTAP Cluster AdministrationONTAP Cluster Administration (ONTAP9ADM)

Course Objectives

This course focuses on enabling you to do the following:

  • Analyze ONTAP REST APIs and Python frameworks
  • Illustrate how to use PCL calls from within your Python program to automate storage administration tasks
  • Configure SMB, NFS, S3, and SAN protocols programmatically by using Python programs
  • Identify the performance metrics of an ONTAP based system

Prezzo & Delivery methods

Online Training

Durata
2 Giorni

Prezzo
  • 1.900,– €
  • NetApp Training Units: 24 NTU
    NTUs may not have the same redemption value if used in a country other than where they were purchased.
Formazione in Aula

Durata
2 Giorni

Prezzo
  • Italia: 1.900,– €
  • NetApp Training Units: 24 NTU
    NTUs may not have the same redemption value if used in a country other than where they were purchased.

Schedulazione

Al momento non esistono edizioni in italiano.

Inglese

Fuso orario: Central European Summer Time (CEST)   ±1 Ora

Online Training Fuso orario: Greenwich Mean Time (GMT)
Instructor-led Online Training:   Questo è un corso Online
Questo è un corso FLEX, erogato sia in aula che in remoto, contemporaneamente.

Al momento non ci sono date italiane disponibili.

Europa

Svizzera

Zürich
Zürich
Zürich
Zürich
Zürich
Zürich

Germania

Berlino
Amburgo
Questo è un corso FLEX, erogato sia in aula che in remoto, contemporaneamente.