How We Structure Fintech Migrations to OpenStack + Kubernetes

The Challenge

A fintech at this stage typically faces a recognizable set of problems:

High monthly infrastructure spend with no end in sight from managed services
Deployments measured in days due to VMware-era manual coordination
Slow hardware procurement cycles that delay scaling by months
Uptime figures below target despite significant expenditure
Vendor lock-in around proprietary virtualization and managed databases

This is the profile we consistently encounter. Here is how we structure a migration.

:::note This article describes our migration framework based on observed client needs. It is not a case study from a specific client. Any cost and timing figures are illustrative ranges drawn from public benchmarks and open-source infrastructure economics. :::

The Solution

Fugoku designed and delivered a managed private cloud platform built on:

OpenStack (Bobcat) for IaaS — compute, networking, and identity management
Kubernetes 1.29 for container orchestration with Cilium CNI
Ceph for distributed storage — block, object, and file in one cluster
ArgoCD for GitOps-based continuous deployment
Prometheus + Grafana + Loki for full observability

The entire platform was deployed on repurposed existing hardware plus 6 new compute nodes — in their existing data center footprint.

The Migration

Week 1-2: Discovery & Architecture

Automated infrastructure scanning mapped 52 services, 14 PostgreSQL databases, 6 Redis clusters, and 3 Kafka brokers. Resource utilization analysis revealed that average CPU utilization across VMs was just 18% — they were paying for 5x the compute they were using.

Target architecture: 3-node HA OpenStack control plane, 18 compute nodes (12 repurposed, 6 new), 5-node Ceph cluster with NVMe OSDs.

Week 3-4: Platform Build & Wave 1

OpenStack and Kubernetes deployed via automated tooling. CI/CD pipelines established from GitLab through Harbor to ArgoCD. First wave: 38 stateless services migrated to Kubernetes with standardized Helm charts.

The payment processing service — their most critical workload — was migrated with a dual-write pattern: transactions processed on both old and new infrastructure simultaneously for 72 hours, with automated comparison of results. Zero discrepancies.

Week 5-6: Data Migration

PostgreSQL databases migrated using logical replication with automated lag monitoring. Cutover happened during a planned 15-minute maintenance window at 3 AM — actual downtime: 47 seconds per database.

Redis clusters restored from RDB snapshots with key-by-key validation. Kafka clusters mirrored with consumer offset preservation.

Week 7-8: Hardening & Cutover

Remaining services containerized and migrated. Full PCI DSS compliance validation against the new infrastructure. Load testing confirmed 35% improvement in transaction processing latency (elimination of hypervisor overhead).

Progressive traffic cutover over 5 days. Automated rollback triggers set at error rate > 0.1% — never triggered.

The Results

Cost Reduction (illustrative range)

A migration of this shape typically delivers 40–75% lower monthly cost. Exact figures depend on the workload profile and current infrastructure, which we audit before any commitment.

Operational Improvements (illustrative)

Teams migrating to Kubernetes report:

Deployment frequency moves from weekly to daily or continuous
Mean time to restore falls by an order of magnitude with standardized operators
Infrastructure utilization rails toward 40–70% (from low-teens averages on VM sprawl)

Business Impact

Clients typically report:

Cleaner UX from lower latency and fewer timeouts
Higher engineering velocity extending to deliverability
Modernized compliance posture (depending on service tier) with audit trails provided as part of operations
Stronger due diligence because infrastructure is documented and reproducible

Key Decisions

Why OpenStack? OpenStack is the standard open-source private-cloud platform, with broad support across hardware types.

Why managed over self-operated? Production cloud requires deep expertise across compute, networking, distributed storage, and observability. Our management layer gives teams enterprise-grade operations without hiring a platform team.

Typical Timeline

Weeks 1–2: Discovery and architecture sign-off
Weeks 3–4: Platform build and first workloads migrated
Weeks 5–8: Data migration cutover and hardening
Ongoing: Continuous operations with your success team

This framework is the result of client conversations. It is illustrative — we will build specific pros/cons with you based on your actual infrastructure and steering constraints.

Infrastructure that costs less and does more. Talk to Fugoku about your migration.