Scalable Analytics: Multi-Environment SAS Viya 4 Deployment in Azure

Cloud ArchitectDevOps Engineer

Project Overview

As a Cloud Architect and DevOps Engineer in the industry sector, my project involved deploying SAS Viya 4 in Azure across multiple environments (Development, Testing, Production). The project included AKS cluster installation, container registry setup, and security enhancements.

Challenges & Solutions

The project tasks included:

  • AKS Cluster Installation: Setting up an Azure Kubernetes Service cluster for different environments - Dev, Test, and Prod.
  • SAS Viya 4 Deployment: Implementing Viya 4 in Azure, ensuring scalability and seamless operation across environments.
  • Container Registry Setup: Establishing a container registry in Azure for managing Docker containers used in Viya 4 deployment.
  • Database Integration in SAS Viya: Integrating existing databases with SAS Viya for consistent data access and analysis.
  • Configuration of SAML and SSO: Implementing Single Sign-On (SSO) and Security Assertion Markup Language (SAML) for enhanced security and streamlined authentication.

Technologies Employed

The project utilized:

  • Container Orchestration and Management: Kubernetes, Docker
  • Cloud Platform and Services: Azure, Azure DevOps, Azure Data Lake, Synapse
  • Security and Authentication: SAML, SSO, LDAP
  • Networking and Storage: NFS, NGINX
  • Version Control: Git
  • Infrastructure Automation: Infrastructure as Code principles

Impact and Outcome

The deployment resulted in:

  • Robust Multi-Environment Setup: Efficient deployment of SAS Viya 4 across development, testing, and production environments in Azure.
  • Enhanced Data Integration: Seamless integration with existing databases, facilitating better data management and analysis.
  • Improved Security Measures: Stronger security and authentication mechanisms with the implementation of SAML and SSO.


This project showcases the effective deployment of SAS Viya 4 in a multi-environment setting within Azure, emphasizing the importance of robust infrastructure, integrated data sources, and enhanced security in cloud-based analytics solutions.