Google Cloud Migration Strategy Guide | Generated by AI
Great question. Let me map out how each component of this stack would translate to Google Cloud, thinking through it practically.Now let me put together a comprehensive migration map based on the research.Now let me build the interactive migration architecture diagram:Here’s the interactive migration map — click each row to expand details and use the effort filters.
A few things worth calling out specifically given your stack:
Db2 is the hardest piece. Cloud SQL doesn’t support Db2 natively, so the real question is where each workload lands. OLTP and ledger data (the core financial processing) maps best to Cloud SQL PostgreSQL — a common approach is to use Cloud SQL PostgreSQL for new applications and migrate critical data gradually. Reporting and batch exports are a better fit for BigQuery, and tools like SHIFT™ Translator can translate Db2 SQL to BigQuery. For the CDC pipeline that keeps both sides in sync during cutover, Striim makes it possible to build data pipelines from IBM Db2 to Google Cloud with real-time data integration using change data capture.
WebSphere has first-class tooling now. Google’s Migrate to Containers supports replatforming WebSphere applications into containers using traditional WebSphere Server container images or Open Liberty community images, including detecting VMs, discovering apps via the IBM binary scanner, and splitting them into individual containers. That said, the stronger long-term move is to land on Open Liberty rather than carrying WAS licensing into the cloud.
Control-M → Composer is well-trodden. DAGify is an open-source solution that automates conversion of Control-M XML files into Airflow’s native DAG format, significantly reducing manual effort and potential errors. Given your existing Python scripting muscle and the 400+ reusable scripts, you’re well-positioned to write and maintain Airflow DAGs natively.
Vault stays flexible. You can either swap it for GCP Secret Manager (simplest) or run Vault itself on GKE if your team has deep dynamic-credential workflows — no app changes needed either way.