What leaders see
The system is in the cloud, but risk still feels local.
Performance, outage exposure, security questions, backup confidence, and monthly spend are still hard to explain.
Cloud Migration · Planning
Plan the migration so it doesn't plan you. Cloud migration without a plan is a weekend outage waiting to happen. We map every dependency, sequence every workload, define every cutover window, and document every rollback procedure -- so migration day is a non-event, not a crisis.
01
The Problem
Cloud problems usually start when infrastructure is moved before ownership, recovery, cost control, and data dependencies are designed around the AI, ERP, and integration workloads.
What leaders see
Performance, outage exposure, security questions, backup confidence, and monthly spend are still hard to explain.
What is actually happening
Workload behavior, recovery requirements, network paths, observability, and operating accountability were not designed together.
What gets worse
The business pays for flexibility without gaining a stronger foundation for AI, ERP control, reporting, and data readiness.
02
What Changes
Cloud migration without a plan is a weekend outage waiting to happen. We map every dependency, sequence every workload, define every cutover window, and document every rollback procedure -- so migration day is a non-event, not a crisis.
Map every application-to-application, application-to-database, and application-to-network dependency. Identify hidden dependencies that break when one system moves and another doesn't.
Assign each application the right migration strategy: rehost (lift-and-shift), replatform (minor modifications), refactor (re-architect), or replace (move to SaaS). Not everything gets the same treatment.
Group workloads into migration waves based on dependencies, business criticality, and risk tolerance. Each wave has a defined scope, timeline, and success criteria.
Detailed cutover runbooks for each wave -- task sequences, timing, responsible parties, validation steps, and communication plans. Rehearsed before execution.
Documented rollback plan for every migration wave with clear triggers and execution steps. If something breaks, you can revert without data loss or extended downtime.
Risk register for each migration wave with probability, impact, mitigation strategies, and contingency plans. Risks are managed proactively, not discovered during cutover.
03
How It Fits Your Operations
Related Foundations
Follow the dependencies behind this service instead of treating it as an isolated project.
Define identity, access, monitoring, protection, evidence, and operating controls for the cloud environment.
Explore next stepConnect cloud architecture to the databases, pipelines, reporting, and operating data it must support.
Explore next stepExplore the packaged Odoo, AWS, integration, data, and managed-operations path when the Roadmap supports it.
Explore next stepAssess readiness, dependencies, risk, architecture, and implementation order before engineering begins.
Explore next stepLaunchpad Before Engineering
Launchpad assesses the business and turns discovery into priorities, risks, readiness, architecture, and an implementation Roadmap. Metrotechs then engineers and supports the approved solution.
04
Delivery sequence
Cloud migration without a plan is a weekend outage waiting to happen. We map every dependency, sequence every workload, define every cutover window, and document every rollback.
Catalog every system, database, and service. Document owners, criticality, dependencies, and current performance baselines.
Evaluate each application and assign the appropriate migration strategy. Present recommendations with rationale and effort estimates.
Group applications into migration waves. Sequence waves to minimize risk and dependency conflicts. Define success criteria and rollback triggers for each wave.
Build detailed cutover and rollback runbooks for each wave. Rehearse critical waves in a test environment before production execution.
05
FAQ
Straight answers to what operators ask before committing budget to this work.
Typically 3-6 weeks depending on the number of applications and complexity of dependencies. This investment prevents weeks of unplanned downtime and rework during execution.