Cloud migration and modernization
We build the landing zone on Google Cloud, move applications in waves and modernize the ones worth it, with the security and audit evidence written as the work happens.
Updated October 19, 2026
Moving to the cloud is a decision about control, not about servers.
Part of your estate already runs on Google Cloud and part does not. The first wave moved; the waves still waiting hold the applications with the most dependencies and the least documentation.
Two estates at once
Your teams run the old data center and the new landing zone side by side, with two sets of tools, two on-call rotations and two security models. Every month in the middle adds cost without adding capability.
What waiting costs: the business case that approved the move erodes before the move is finished.
Dependencies nobody mapped
An application moves and a batch job, a file share or a hard-coded address it relied on stays behind. The failure shows up after cutover, in a system nobody thought was involved.
What waiting costs: a rollback in the middle of the night, and a business that stops believing the next cutover date.
Evidence after the fact
The controls were set up correctly, but nobody recorded who approved them or how they were tested. Rebuilding that record takes longer than doing the work did.
What waiting costs: a finding that holds the next wave until the paperwork catches up.
Migrations stall in the middle, not at the start. The easy applications move first, the dependency map was never finished, and security and audit ask for evidence the team did not write down as it went. Every pause leaves you paying for two estates.
What is stopping the next wave, and who decided it could wait?
Three waves, one held back
We put the controls in the landing zone before the first workload, move applications in rehearsed waves, and modernize only where it pays, with the evidence written as each step happens. The organizations that finish a migration are the ones that decided early what not to move.
Identity, network, logging and policy set up before the first workload lands, with each control described, tested and approved.
You hold: an approved foundation and the evidence your security team signed.
Security and responsible AIDependency maps, grouping by business service, rehearsed cutovers and a rollback plan for each wave, agreed with your operations team before anything moves.
You hold: a wave plan your operations team agreed, and an evidence pack for every wave that lands.
How work reaches productionContainers on GKE or Cloud Run for the applications worth rebuilding, data moved to BigQuery where analytics or agents need it, and APIs on Apigee in front of what stays where it is.
You hold: a list of what to move, rebuild or retire, with the reason for each.
Apigee and APIsEasy to start
Choose one workflow, name one owner, and give us time with the people who sign it off.
We bring engineers and the gateway design, we work inside your environment under your security rules, and we write the review pack alongside the build.
A good first step is one migration wave with a fixed scope and its cutover plan agreed before it starts. See the fixed-price ways to start.
What the work feels like
One workflow is chosen and one person owns it. The questions your reviewers will ask are written down before any build starts. Your operations team rehearses the first cutover with us before a single application moves.
Governance goes in before the first agent does: the gateway, the audit trail and the access rules. Your risk team sees them working.
A working demo you can show your own review board, not a status slide.
A decision log that can rebuild any action, and a go-live date that was agreed at the start.
Seen it before
Production readiness check
A short readiness check on a live or planned agent workflow. You get a score and the practices worth another look.
Take the readiness checkBy dependency and business service, not by team or by server. Each wave has a mapped set of applications, a rehearsed cutover and a rollback plan agreed with your operations team before it starts.
Each application is assessed on what it does for the business, its technical condition, its dependencies and what it costs to run. You get the list with a reason for every decision, and the decisions stay yours.
Yes. This practice moves and modernizes workloads on Google Cloud, and plans the ones that should stay where they run.
We put APIs in front of them and leave them where they run. Apigee gives new applications and agents a governed way to reach them, so an old system stops being the reason the rest waits.
The controls go into the landing zone before the first workload, and the evidence is written with each wave: control descriptions, test results and approvals. Your security and audit teams see it as it is produced, not at the end.
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