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Automated Cloud Environment Provisioning System
  1. case
  2. Automated Cloud Environment Provisioning System

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Automated Cloud Environment Provisioning System

scalosoft.com
Financial services
eCommerce

Challenges in Manual Environment Provisioning

The organization faced inefficiencies in manual environment setup for development and QA, leading to prolonged project initiation timelines. Lack of standardized, customizable infrastructure provisioning processes hindered agility in validating new ideas and adapting to evolving digital demands.

About the Client

A leading fintech company specializing in commerce sector solutions with global operations and a focus on cutting-edge technology innovation

Goals for Automated Environment Provisioning

  • Implement automated provisioning of cloud environments including AKS clusters
  • Enable customizable environment configurations (size, microservice versions)
  • Establish CI/CD pipelines for microservices deployment
  • Standardize infrastructure management through 'Everything as Code' methodology

Core System Functionalities

  • Self-service AKS cluster provisioning interface
  • Version-controlled microservice deployment options
  • Environment size customization (resource allocation)
  • Automated testing pipeline integration
  • Infrastructure-as-code template management

Technology Stack Requirements

Docker
Helmfile
Terraform
Kubernetes
Microsoft Azure

System Integration Needs

  • Azure Kubernetes Service (AKS)
  • JMeter testing framework
  • CI/CD pipeline tools (e.g., Jenkins/GitHub Actions)
  • Azure Resource Manager (ARM)

Operational Requirements

  • Scalable architecture for concurrent environment provisioning
  • High availability for production-grade environments
  • Role-based access control (RBAC) security model
  • Performance SLAs for provisioning speed

Expected Business Impact of Automation

Reduction of environment setup time from days to minutes, enabling 300% faster iteration cycles. Standardized environments will decrease configuration-related issues by 70%, while automated testing pipelines improve application reliability. Infrastructure-as-code approach reduces operational costs by 40% through resource optimization.

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