The Software-Defined Storage Foundation:

In many industrial and analytics environments, unstructured data volumes, model artifacts, and ingest archives are growing exponentially. The traditional response of enterprise IT—constantly expanding proprietary SAN/NAS appliances or uncontrolled outsourcing to US hyperscaler buckets—leads to a dead end: hardware expansions demand six-figure CapEx investments, while cloud object storage with opaque API calls and egress fees drain the IT budget.

The architectural solution lies in the software-defined abstraction of storage directly at the platform level. By operating Ceph via the Rook Operator on the ayedo Managed Kubernetes platform, companies transform off-the-shelf standard hardware into a highly available, horizontally scalable, and S3-compatible object storage foundation—software-defined, multi-tenant, and fully under their own control.

1. The Problem: The Limits of Traditional Enterprise Storage

Classic hardware appliances and proprietary storage protocols create significant hurdles for modern, data-intensive Cloud-Native workloads:

• 1. Silo formation due to incompatible access patterns: Legacy storage systems often offer only block (iSCSI, Fibre Channel) or file storage (NFS), but fail at performant, HTTP-based S3 object interfaces that modern data pipelines like Airflow, PyTorch, or ClickHouse natively require.
• 2. The cost and capacity trap when scaling: Proprietary hardware forces companies into rigid licensing and support contracts. When additional storage is needed, expensive, vendor-specific disk shelves must be retrofitted instead of purchasing cheaper standard NVMe and HDD drives commonly available on the market.
• 3. The lack of orchestration transparency: Traditional storage is managed outside the Kubernetes cluster. Dynamic provisioning of Persistent Volume Claims (PVCs) requires manual interfaces, slows down automated CI/CD pipelines, and complicates granular cost monitoring per namespace.

2. The Solution: The Declarative Rook-Ceph Architecture

ayedo operates Ceph fully containerized within the Kubernetes cluster. Through the Kubernetes-native Rook Operator, the management of physical drives is automated and provided as a unified storage pool.

• 1. Hardware-independent storage pooling via CRDs: Rook abstracts the physical storage media on the worker nodes via Kubernetes Custom Resources. Ceph Object Storage Daemons (OSDs) directly integrate NVMe, SSD, and SAS drives and form logically separated performance and capacity pools without being tied to specific controllers.
• 2. The native S3 and RadosGW gateway: Through the integrated Ceph Rados Gateway (RGW), the platform provides highly available, S3-compatible endpoints internally within the cluster and over mTLS-secured ingress routes. Data science pipelines and ETL workloads read and write data via standardized S3 APIs with native multi-tenancy support.
• 3. Automated self-healing and rebalancing: If a physical drive or an entire storage node fails, Ceph detects the data loss at the block level and automatically starts rebalancing in the background via the Placement Groups (PGs). Kubernetes workloads access replicated data sets without interruption while the operator replaces faulty hardware during operation.

3. Strategic and Economic Value

Establishing software-defined storage based on Ceph delivers measurable commercial efficiency and guarantees long-term regulatory security:

• Drastic reduction of storage TCO by up to 60%: By using standardized commodity hardware and avoiding expensive enterprise storage licenses, acquisition and operating costs are significantly reduced.
• 100% GDPR, NIS-2, and BSI-C5 compliance: All data sets, ingest archives, and model checkpoints are physically encrypted on their own infrastructure in European data centers—without access possibilities for foreign authorities.
• Complete independence from hyperscaler egress costs: Large datasets for AI training runs are moved internally without data transfer fees between pipelines, GPU nodes, and storage.
• Audit-proof traceability and audit security: By defining storage as declarative code via GitOps, all bucket policies, quotas, and lifecycle rules are completely versioned and traceable.

Conclusion

Future-proof data engineering requires storage that dynamically adapts to software requirements instead of stifling innovation through rigid hardware boundaries. With a managed Rook-Ceph architecture on Kubernetes , ayedo demonstrates that highly scalable, S3-compatible object storage can be operated economically, reliably, and with full sovereignty in one’s own data center.

FAQ: Practical Questions about Ceph on Kubernetes

How does Ceph compare to dedicated cloud S3 storage in terms of latency and throughput?

In the local network and on NVMe-based pools, Ceph often offers significantly lower latencies and higher throughput rates than public cloud buckets, as WAN routes and artificial API rate limits are eliminated. In compute-intensive ML training runs, data is streamed directly over 25G/100G Ethernet networks, drastically minimizing GPU wait times.

What administrative effort is involved in operating Ceph in the Kubernetes cluster?

By using the Rook Operator, typical operational tasks such as OSD provisioning, storage allocation, failover, and rolling updates are fully automated. ayedo takes over continuous platform monitoring and lifecycle management, allowing the internal team to focus solely on using the S3 APIs and PVCs.

How is failover ensured in the event of multiple disk or node failures?

Ceph typically uses a 3x replication or configurable erasure coding profiles (e.g., k=4, m=2). This allows the system to withstand the simultaneous failure of up to two physical storage nodes without data loss or interruption of read and write access.