intellimetrics Learning
Cloud Modernization Patterns

Cloud Modernization Patterns

Modernize legacy applications with AI CLI tools — assessment, platform selection, containerization, data migration, and production readiness.

6 modules · 22 lessons · ~6.9 hours · Application teams, architects, SRE/operations

Chapter 1 in the Meridian sequence · 9 live so far · continues in Zero Trust Implementation

Follow the modernization of a fictional utility company's legacy estate — a load-bearing low-code app, a .NET Framework monolith with an Oracle database, and a decade of file-share reporting data — from first assessment to production cutover, and then keep it modern. Every lesson uses AI CLI tools to do the real work.

The Curriculum

01

Size It Up

Decide before you build

Assess the legacy estate, weigh build vs adopt vs extend, and sequence a roadmap that survives contact with reality

02

Where Should It Run?

PaaS first, Kubernetes last

The platform decision ladder, containerizing a .NET Framework monolith, managed container services, and the one workload that genuinely needs Kubernetes

03

Move the Data

Exact seams, no orphans

Contract-driven migration: watermark handoffs, reconciliation before cutover, and manifests as your audit trail

04

Make It Production

Ship it and own it

Hardening, the role-by-scenario test matrix, environment promotion, and the Day-2 operations you keep

05

Modernize With AI

The 2026 operating model

Agent-driven assessment, AI-executed porting behind characterization tests, and owning the fleet AI builds

06

Stay Modern

Make it stick

Secretless pipelines, golden paths, policy-as-code with drift detection, and compliance evidence as code

New to AI CLI tools?

This training assumes you can drive an AI CLI (Claude Code, Codex CLI, Antigravity CLI, or Copilot CLI). If that's new, these modules from our AI-Powered Development training are the fastest preparation — most students need only the first one: