Eliminating Click-Ops & Deployments From Local Machines
Click-Ops, Bottlenecks, and Deployments to Prod from VS Code
The firm had a team of over 30 engineers and operations staff and was five years into their Azure adoption. Applications were running. The cloud was being used. But the risk profile of their operating model was deteriorating across multiple dimensions.
Infrastructure was provisioned manually through the Azure Portal with no automated policy checks, no peer review, and no guaranteed consistency. Configurations drifted between environments. Code tested in development behaved differently in production. There was no version-controlled record of what had changed, when, or by whom. Developers deployed code to production directly from VS Code on local machines.
The bottleneck was severe. Every infrastructure request flowed through a small operations team that was already at capacity. Developers had begun to internalize the delays as normal. Some had stopped requesting new environments entirely because they knew the wait would be measured in weeks. When leadership began planning an internal AI platform, it became clear the manual process couldn’t support the pace the initiative demanded.
Infrastructure provisioned manually through the Azure Portal with no version control, policy checks, or peer review
Configurations drifted between environments, causing inconsistent behavior across dev and production
Developers deployed code to production directly from VS Code on local machines
A small operations team was the bottleneck for every infrastructure request, with wait times measured in weeks
An Internal Developer Platform Built on IaC & CI/CD
Terraform Module Library
Over 30 custom Terraform modules aligned with Azure Well-Architected Framework best practices. These modules encoded organizational standards and business requirements, enabling teams to provision compliant, cost-optimized infrastructure through code rather than portal clicks.
CI/CD Foundation
A suite of CI/CD templates in GitLab standardized how infrastructure, backend services, and frontend applications are built and deployed across environments. Templates introduced quality gates, static code analysis, and approval workflows that ensure code meets defined standards before reaching production.
Cloud Architecture
Applications migrating to the new deployment model were brought in line with Well-Architected Framework standards and Guidelines for AI Workloads, ensuring they complied with the latest recommended standards in an ever-changing environment.
A Foundation for Future Growth
In the first year, three major products were migrated to the Infrastructure-as-Code and CI/CD workflow. Beyond implementation, collaboration with development teams across the organization facilitated adoption of new processes and standards.
Infrastructure is now provisioned through code rather than manual portal configuration. The client reported zero outages since implementation. Year-two plans include transitioning from GitLab to GitHub and expanding automation to Auth0 and other cloud providers.
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