Using Azure DevOps and Azure Pipelines in SAS® Viya®

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ENROLL

Not attempted Using Azure DevOps and Azure Pipelines with SAS Viya

Learn how Azure DevOps supports, enhances, and accelerates the Analytics lifecycle in SAS Viya.

Learn How To

Use Azure Repos and Azure Pipelines from Azure DevOps

Create a self-hosted agent that will interact with SAS Viya on Azure

Create SAS Viya data, decision, model, scoring, and configuration pipelines

Who Should Attend

Technical resources working with or interested in the Azure cloud, DevOps concepts or SAS Viya automation and integration with Git and Azure.

Prerequisites

Before attending this course, you should be familiar with;

Azure Cloud

SAS Viya fundamentals

Familiarity with bash scripting, python, Azure CLI (Command Line Interface), SAS Viya REST API (Application Programming Interfaces), SAS Viya CLI is also extremely helpful

SAS Products Covered

SAS Viya

Course Outline

Azure Pipelines Fundamentals (Microsoft hosted agent)

Create basic tasks and scripts

Work with parameters and variables

Structure the scripts in jobs and stages

Protect secrets in a pipeline

Work with an Azure Key Vault

Self Hosted Agent

Create a self-hosted agent to work with SAS Viya on Azure

Set-up a repository with necessary files. and ports

Copy certificates

Configuration pipelines: update packages, install needed python version, install sas-viya cli and pyviyatools.

SAS Viya Data Pipelines

Run SAS programs in batch (in the pipeline and from a sas file in Git)

Add a repository in SAS Studio and trigger pipelines form there

Run a SAS program that reads a CAS (Cloud Analytic Services) table and creates a file in ADLS2 (Azure Data Lake Storage Gen 2) blob storage

Import and run a SAS Studio Flow

Create a complete data pipeline that loads a CAS table, imports a flow, allows a manual step to schedule the flow, runs the flow and stores the output in ADLS2 blob storage

SAS Viya Decision Pipelines

Create a Git publishing destination with a python file

Design a multi-stage decision pipeline: Import, Publish and Deploy decisions

SAS client and secret registration in a pipeline. BASH curl REST API

Scoring the deployed decision using files stored in ADLS2 storage

SAS Viya Model Pipelines

Create an Azure publishing destination with a python file

Create a SAS Model Manager project and import models

Create a release pipeline

Automate the model import and publish steps

THIS COURSE IS PART OF

SAS Data Engineering Learning Subscription

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