Streamlining Multi-Database Workloads on Azure with Infrastructure Automation for SQL Server and MongoDB Using Terraform

• Author(s): Padma Rama Divya Achanta
• Paper ID: 1709408
• Page: 465-470
• Published Date: 31-12-2022
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 6 December-2022

Abstract

With an ever more complicated digital ecosystem, businesses tend to use several database systems—like SQL Server for structured relational data and MongoDB for unstructured or semi-structured document-based data—to serve various application needs. Provisioning such heterogeneous environments is a challenge, especially when installed on cloud platforms like Microsoft Azure. Automation of infrastructure through Infrastructure as Code (IaC) solutions, particularly Terraform, is a very attractive solution with the potential for consistent, repeatable, and scalable deployment. This study discusses integration and automation of multi-databases workloads—SQL Server and MongoDB—on Azure via Terraform. It assesses the operational efficiencies achieved, including less human intervention, faster provisioning, and greater consistency across environments. The research explores different architectural models, provisioning methods, and best practices for deploying and managing such databases with Terraform modules. Focus is given to realizing Azure's services such as Azure SQL Database, Virtual Machines for SQL Server, Azure Cosmos DB for MongoDB API, and how they can be orchestrated using Terraform. The paper also delves into the advantages of IaC based on automation, compliance, infrastructure governance, and scalability, particularly for hybrid and DevOps-oriented organizations. Various case studies and business reports are examined to measure performance improvements, deployment time, and error reduction due to automation of infrastructure. Some challenges, like tool complexity, learning, and integration issues between Terraform, Azure CLI, and database services, are also described in the study. The results show that automation of infrastructure significantly simplifies workload management, reduces deployment time, and maintains infrastructure parity in development, staging, and production environments. In summary, this study promotes the use of Terraform-based automation to govern multi-database environments in Azure and proposes best practices to practitioners who want to transform their data infrastructure operations.

Citations

IRE Journals:
Padma Rama Divya Achanta "Streamlining Multi-Database Workloads on Azure with Infrastructure Automation for SQL Server and MongoDB Using Terraform" Iconic Research And Engineering Journals Volume 6 Issue 6 2022 Page 465-470

IEEE:
Padma Rama Divya Achanta "Streamlining Multi-Database Workloads on Azure with Infrastructure Automation for SQL Server and MongoDB Using Terraform" Iconic Research And Engineering Journals, 6(6)