Migration

You wouldn’t load a bus
onto a cargo plane.

Yet that is exactly what lift-and-shift migration does. It takes on-premises infrastructure — designed for ground transport — and forces it into the cloud without redesigning for the new medium. Exodus takes a different approach: modernize, don’t transplant.

The analogy

Bus service vs. air travel

🚌

Bus service

On-premises / legacy

  • Fixed routes, fixed schedules
  • Passengers (workloads) stuck on one vehicle
  • Driver (ops team) handles everything manually
  • Road conditions (hardware) limit speed
  • No altitude — local reach only
  • Bus breaks down, everyone waits
✈️

Air travel

Cloud-native / OpenOva

  • Dynamic routing, global reach
  • Passengers (workloads) board any flight
  • Autopilot (Specter) handles operations
  • Altitude (cloud) removes physical limits
  • Global network of airports (regions)
  • If one plane has issues, rebook on the next
Pre-flight check

Five conditions that ground your workloads

Before any workload can fly, it needs a medical check. These five conditions are the most common blockers we find during assessment. Each has a treatment plan.

Life support dependency

Application cannot survive without a specific proprietary runtime, driver, or OS feature

Identify the dependency, find cloud-native equivalent, or containerize with compatibility layer

Siamese twin syndrome

Two or more applications are so tightly coupled they cannot be deployed independently

Map the coupling, introduce API boundaries, migrate as a unit or decouple first

Compromised immune system

Application has no health checks, no metrics, no logs. Invisible to monitoring.

Add OTel instrumentation, standardize health endpoints, integrate with Grafana stack

Fixed treatment protocol

Application requires specific manual procedures for deployment, scaling, or recovery

Codify runbooks into Kubernetes operators or Temporal workflows. Make procedures declarative.

Weak vital signs

Application performance is unknown. No baselines. No SLOs. No capacity model.

Establish baselines in current environment before migration. Set SLOs. Use KEDA/VPA for autoscaling.

Preparation

Preparing for the journey

Check-in

State management

Externalize state from applications. Move session data to Valkey, files to MinIO, databases to CNPG. No carry-on luggage in the overhead bin.

Security screening

Auth & secrets

Migrate credentials to OpenBao. Replace hardcoded secrets with External Secrets Operator. Every passenger gets screened.

Gate assignment

Service discovery

Replace static IPs and hostfiles with Kubernetes services, Cilium networking, and ExternalDNS. Dynamic gate assignment.

Flight standards

Cloud-native compliance

Enforce resource limits, pod security, network policies via Kyverno. Every flight meets safety standards before takeoff.

Flight plan

5-phase structured migration

1

ASSESS

Week 1-2

Full inventory and pre-flight medical check. Map dependencies, identify the five conditions, evaluate AI-readiness.

Current state architecture Dependency map Risk register AI-readiness scorecard
2

PLAN

Week 2-3

Design the flight plan. Target architecture, migration sequence, rollback strategy, and treatment plans for each condition.

Target architecture blueprint Migration sequence plan AI modernization roadmap Success criteria
3

PILOT

Week 3-6

First flight. Migrate a non-critical workload end-to-end to validate the approach.

Pilot migration complete Performance comparison Team trained Go/no-go decision
4

MIGRATE

Week 6-12

Full fleet transition. Phased production migration with parallel running and continuous validation.

Production workloads migrated Parallel running validated Specter operational Legacy ready to decommission
5

OPTIMIZE

Week 12+

Cruising altitude. Performance tuning, cost optimization, and legacy decommission.

Optimized platform Legacy decommissioned Team self-sufficient Support subscription active
Migration paths

From proprietary to open source

Platform migrations

Red Hat OpenShift OpenOva (K3s + Cilium + Flux)
VMware Tanzu OpenOva
Amazon EKS / GKE / AKS OpenOva (self-hosted)
Legacy VMs OpenOva (containerized)

Observability migrations

Datadog Grafana Stack
€200-400K/yr
Splunk Loki + Grafana
€150-300K/yr
New Relic OTel + Grafana
€100-250K/yr
Dynatrace OTel + Mimir + Tempo + Grafana
€150-350K/yr

Database migrations

Oracle Database CNPG (PostgreSQL)
Redis Enterprise Valkey
Confluent Kafka Strimzi (Apache Kafka)
MongoDB Atlas FerretDB on CNPG
Amazon RDS CNPG (PostgreSQL)

Security & identity migrations

Auth0 Keycloak
€50-100K/yr
Okta Keycloak
€50-150K/yr
Prisma Cloud Falco + OpenSearch SIEM + Kyverno + Specter
€100-200K/yr
Aqua Security Falco + OpenSearch SIEM + Kyverno + Specter
€80-150K/yr
Unchaining

Breaking free from vendor lock-in

The most common Exodus migrations start with unchaining from proprietary platforms. Each path has been proven in production.

VMware

vSphere tax, per-socket licensing, Broadcom uncertainty

OpenOva on bare metal / Hetzner

Eliminate hypervisor licensing entirely. K3s runs directly on bare metal. Typical savings: 60-80% on infrastructure costs.

Red Hat OpenShift

Per-core subscription, forked K8s, ecosystem restrictions

K3s + OpenOva

Pure upstream Kubernetes. Every component is the actual open-source project, not a fork. No subscription lock-in.

Oracle

License audits, per-processor fees, Java SE traps

PostgreSQL (CNPG) + OpenOva data services

Full database migration to CNPG. No license audits. No per-processor fees. MongoDB workloads via FerretDB.

Benefits

Why air travel beats bus service

Cost efficiency

Eliminate proprietary licensing. Pool infrastructure. Pay for what you use. 60-85% cost reduction.

Global reach

Multi-region deployment. Independent clusters in any geography. Disaster recovery built in.

Speed & agility

Deploy in minutes, not months. GitOps-native. Self-service via Catalyst IDP.

Professional infrastructure

Dedicated control tower (Specter). Standardized procedures. Continuous compliance.

Reference

Complete analogy mapping

Bus service (on-prem) Air travel (cloud-native)
Bus service On-premises infrastructure
Air travel Cloud-native platform (OpenOva)
Passengers Workloads / applications
Bus driver Operations team (manual)
Autopilot Specter (AI operations)
Bus routes Network topology (fixed)
Flight routes Cilium service mesh (dynamic)
Bus depot Data center
Airport Kubernetes cluster
Control tower Grafana observability stack
Baggage handling Data migration (CNPG, Valkey, Strimzi)
Check-in counter State externalization
Security screening OpenBao + ESO (secrets)
Gate assignment Service discovery + DNS
Flight standards Kyverno policies
Pre-flight medical Workload assessment
Fleet modernization Exodus migration program

Start your assessment

The pre-flight medical check starts in week 1. Zero downtime. Full modernization. Not lift-and-shift.