Solutions
Data & Storage
Run stateful workloads on Kubernetes with the right storage architecture for their reliability and performance requirements. We help teams evaluate what should run on-cluster versus managed services, design backup and migration paths, and build operational runbooks for the day-two questions that follow initial deployment.
The Business Problem
Stateful workloads that are difficult to operate, migrate, or recover in containerized environments
The Challenge
Kubernetes was designed for stateless workloads. Stateful workloads — databases, message queues, object stores, caches — have always required more careful thought. Storage performance, data durability, backup and recovery, and migration paths all become harder in container environments, especially when the team’s Kubernetes expertise outpaces their distributed storage experience.
Organizations often reach an inflection point: they’ve successfully containerized their applications, but their databases are still running on bare metal or managed cloud services with no clear path to modernization. Or they’ve moved too fast and are running stateful workloads on Kubernetes without adequate reliability engineering.
Our Approach
We help teams find the right balance between control and operational overhead for their data systems. That often means evaluating whether a workload should run on Kubernetes at all, or whether a managed cloud service is the right fit. Not everything benefits from containerization.
When stateful workloads do run on Kubernetes, we focus on storage class selection, performance benchmarking, backup strategy, and operational runbooks. We avoid one-size-fits-all answers: a high-throughput analytics database has different requirements than a low-traffic relational store backing a web application.
We also design data migration paths. Moving from a legacy storage system to a new architecture without downtime requires careful planning — dual-write strategies, cutover validation, and rollback capability.
Technology Options
- Rook-Ceph — software-defined storage for Kubernetes, providing block, object, and file storage from on-cluster hardware
- Longhorn — lightweight distributed block storage for Kubernetes with built-in replication and snapshots
- OpenEBS — CNCF-graduated storage with multiple storage engines for different performance profiles
- MinIO & Alternatives — S3-compatible object storage for on-prem or self-hosted environments
- CloudNativePG — Kubernetes operator for PostgreSQL with high availability, backup, and failover built in
- Vitess — horizontal sharding for MySQL, used by teams that have outgrown single-server database capacity
- Redis / Valkey — in-memory caching and message brokering with Kubernetes operator support
- Managed alternatives — Amazon RDS, Google Cloud SQL, Azure Database — evaluated and integrated where they reduce operational burden