Project Overview
The project entailed deploying SAS Viya in an Azure Cloud environment, a significant stride in cloud-based analytics. My roles as a Cloud Architect and DevOps Engineer were instrumental in both the planning and execution phases.
Challenges & Solutions
Key tasks and solutions in this deployment included:
- Azure Cloud Infrastructure Provisioning: Setting up the necessary cloud infrastructure in Azure for optimal performance.
- VPN Connection Setup: Establishing a VPN connection to integrate local resources into the cloud environment.
- Kubernetes-based Deployment: Utilizing Kubernetes for the deployment of SAS Viya, ensuring scalability and manageability.
- Third-Party Tools Integration: Seamlessly integrating various third-party tools to enhance functionality.
- Data Sources Connection: Linking multiple data sources to SAS Viya for comprehensive analytics.
- Azure Entra ID Integration: Implementing Azure Entra ID as the identity provider for secure access management.
Technologies Employed
This project leveraged:
- Orchestration and Containerization: Kubernetes, Docker, Helm
- Cloud Services: Azure, Azure AKS
- Security and Networking: VPN, Cert-Manager
- Analytics Platform: SAS Viya
- Scripting and Automation: Linux, shell scripting, Terraform
- Version Control: Git
Impact and Outcome
This deployment significantly enhanced the analytical capabilities in the cloud, marked by:
- Robust Analytical Platform: Providing a powerful, scalable analytics environment.
- Integrated Infrastructure: Seamless integration of cloud and local resources.
- Enhanced Data Accessibility: Connecting various data sources for richer insights.
- Secure Access Management: Implementing robust identity management with Azure Entra ID.
Conclusion
The successful deployment of SAS Viya in an Azure Cloud environment underscored the importance of sophisticated cloud architecture and DevOps skills in enhancing cloud-based analytical capabilities.
