Discovery
Inventory applications, infrastructure, data, integrations, traffic and owners.
CLOUD & KUBERNETES MIGRATION
Kubernetes migration services built around a migration strategy you can test, roll back and operate.
We inventory dependencies, risks and change windows before execution. Then we migrate in stages, validate, document and leave a rollback strategy proportionate to the environment.
THE PROBLEM
One missed dependency can block the entire migration.
Moving servers or containers is only one part. Data, DNS, certificates, networks, integrations, change windows and teams all need to be considered before anything moves.
WHEN TEAMS CALL US
Different migrations often begin with similar problems.
We need to move on-premise infrastructure to cloud.
We want to change provider without repeating current problems.
An application needs to move to AKS, EKS or GKE.
The current cluster is old or hard to maintain.
A legacy platform is blocking product changes.
We need to reduce disruption and have a clear way back.
WHAT WE DO
We turn an intention to migrate into a plan that can be tested.
We do not assume everything should move the same way. We classify workloads, dependencies and risk to choose the right sequence.
Dependencies
Identify communication paths and the order that constrains migration.
Target design
Define the AWS, Azure, GCP or Kubernetes destination and operating changes.
Phased plan
Group workloads, windows, owners, success criteria and decision points.
Testing
Validate connectivity, deployment, performance, data, backups and operations.
Execution
Automate and coordinate migration with traceable steps.
Validation
Check service, data, observability and dependencies after each phase.
Rollback
Document when and how to return if validation criteria are not met.
Workload
An application, service or process that needs to run on the platform.
Cutover
The moment traffic or operations switch to the new environment.
Rollback
The plan for returning to the previous environment if validation fails.
DISRUPTION AND EXPECTATIONS
We do not promise “zero downtime” as a generic claim.
Where architecture allows it, we can design strategies to minimise or avoid disruption. This must be assessed case by case.
Source
On-premise, current cloud provider, virtual machines or existing Kubernetes.
Destination
AWS, Azure, GCP, EKS, AKS, GKE or another agreed platform.
Automation
Terraform, OpenTofu, Docker, Helm and GitOps.
Operations
Observability, backups, recovery, access and post-migration procedures.
STAGEDISCOVER→
STAGEPLAN→
STAGETEST→
STAGEMIGRATE→
STAGEVALIDATE
Every phase has entry criteria, validation and a clear decision on how to proceed.
HOW WE WORK
Migration moves forward on evidence, not blind confidence.
Discover
Build the inventory and dependency map.
Design
Agree destination, phases, risks and acceptance criteria.
Prepare
Create infrastructure, automation, observability and tests.
Migrate
Execute in phases and record each change.
Handover
Validate, document and transfer operations to the team.
WHAT THE CLIENT RECEIVES
An operational destination and the information needed to maintain it.
Delivery does not end when the last data is copied.
- Inventory and dependency map.
- Architecture and migration plan.
- Risk matrix and validation criteria.
- Infrastructure and deployment code.
- Cutover and rollback procedures.
- Environment documentation and handover.
WHEN IT MAKES SENSE
When staying on the current platform has a clear cost or risk.
- Hardware, versions or contracts are nearing end of life.
- The current platform blocks delivery or growth.
- You need to change cloud provider.
- You want Kubernetes for a concrete reason.
- The migration affects services that cannot move casually.
OUTCOME
A tested migration with known risks and a way back.
- Fewer unknowns before change.
- Clear phases and ownership.
- A reproducible destination.
- Technical and operational validation.
- Documentation for the next step.
CLOUD & KUBERNETES MIGRATION
What needs to move, and what cannot go wrong during the change?
We can turn the current environment into an inventory, identify dependencies and design a controlled first phase.