Ceph: The Reference Architecture for Scalable Cloud-Native Storage

TL;DR

Storage has traditionally been the heaviest “anchor element” in cloud architecture. Using AWS EBS or S3 ties your data physically and economically to a provider. Ceph breaks this model as a “Unified Storage Solution” (Block, File, Object). It runs on standard hardware and scales linearly into the exabyte range. With full S3 compatibility and Kubernetes integration, Ceph enables true data portability without reliance on proprietary cloud storage systems.

1. The Architectural Principle: Unified Distributed Storage

Traditional storage systems (SAN/NAS) or cloud services (EBS) are often specialized for a single data type. Ceph, on the other hand, is a “Software Defined Storage” (SDS) that unites three worlds in one cluster:

1. Block Storage (RBD): High-performance storage for databases and volumes (comparable to AWS EBS).
2. Object Storage (RGW): S3-compatible storage for unstructured data, backups, and media (comparable to AWS S3).
3. File System (CephFS): Shared filesystem access for many pods simultaneously (comparable to AWS EFS).

The core is the CRUSH algorithm. Instead of using central tables to know where data is located (which creates bottlenecks), clients and servers calculate the storage location algorithmically. This eliminates the single point of failure and allows unlimited scaling.

2. Core Feature: Self-Healing and Hardware Independence

Proprietary cloud storage is often a black box. If an AWS EBS volume fails or degrades in an availability zone (AZ), the user is powerless.

Ceph, however, is designed for failure as a normal state. Data is replicated by default (usually threefold) and distributed across various failure domains (disks, servers, racks).

• Self-Healing: If a disk or an entire node fails, Ceph immediately detects it. The cluster automatically begins restoring the missing data replicas from the remaining copies on other nodes.
• Commodity Hardware: Ceph does not require expensive specialized arrays. It transforms standard servers with local NVMe/SSD disks into an enterprise storage cluster.

3. S3 Compatibility as Standard

A strategic advantage of Ceph is the RADOS Gateway (RGW). It provides an API compatible with Amazon S3. This means applications written for the cloud (expecting S3) can run against a local Ceph cluster without code changes. You simply change the endpoint in the config – data sovereignty returns to the company.

4. Operating Models Compared: AWS Storage (EBS/S3) vs. ayedo Managed Ceph

Here, the question of Data Gravity is decided: Data has mass. The more data you store with a hyperscaler, the harder (and more expensive) it becomes to ever move it again.

Scenario A: AWS EBS & S3 (The Egress Trap)

Those who rely on native AWS storage services enjoy convenience but pay with strategic inflexibility.

• The Egress Lock-in: Storing data in S3 is cheap, but retrieving it (download) is extremely expensive (egress fees). This makes migrations economically impossible beyond a certain data volume.
• AZ Binding (EBS): An EBS volume is firmly tied to an availability zone. If the zone fails, the data is not readily available in another zone.
• The Result: Your data is in a “golden cage”. The application may be portable (container), but the state (databases, files) is stuck to AWS. Switching providers is akin to a data evacuation against ransom (egress fees).

Scenario B: Ceph with Managed Kubernetes by ayedo

In the ayedo App Catalog, Ceph is provided as a portable storage layer.

• Full Data Sovereignty: The data resides on the disks of the worker nodes. You have physical access to the state, no matter where the cluster runs.
• No Internal Egress Costs: Since traffic between nodes is often cheaper or included, the high S3 API costs for internal traffic are eliminated.
• Cross-AZ Replication: Ceph can be configured to synchronously replicate data across zones. If a zone fails, access continues seamlessly (Zero RPO).
• True Portability: Since the storage is software-defined, the exact same stack can run on-premise, at Hetzner, or on AWS.

Technical Comparison of Operating Models

FAQ: Ceph & Storage Strategy

Isn’t Ceph too complex to operate?

Ceph has traditionally been considered complex to manage (“Day 2 Operations”). This is where the value of a managed platform comes in. In an environment like the ayedo stack, Ceph is pre-configured and automatically deployed. Users consume storage simply via Kubernetes PersistentVolumeClaims (PVCs), without worrying about the underlying complexity of OSDs and monitors.

Can Ceph really replace AWS S3?

Yes. The Ceph Object Gateway offers a highly compatible S3 API. For most use cases (uploading user content, backups, log storage, Terraform state), Ceph behaves exactly like AWS S3 – but without transfer costs and with full data control.

When is Ceph worthwhile compared to Managed Block Storage?

As soon as you need scaling or independence. Managed Block Storage (like EBS) becomes very expensive with large data volumes and is technically inflexible (no multi-attach with standard volumes, AZ lock). Ceph allows the use of cheap “raw storage” and software-based enterprise features (replication, snapshots). It is also the basis for true hybrid cloud scenarios.

How is the performance?

Ceph is distributed network storage. This means there are minimal latencies due to the network. For extreme high-performance databases (high-frequency trading), local storage is often better. For 95% of all cloud-native workloads, however, Ceph on modern NVMe hardware is more than performant enough and offers high availability that local storage does not.

Conclusion

Data is the gravitational center of any infrastructure. Those who store their data exclusively in proprietary AWS silos like EBS and S3 make their architecture immobile. Ceph breaks these chains. It provides an enterprise storage platform that is fully based on open-source standards. With the ayedo Managed Stack, companies gain the robustness of hyperscaler storage while retaining full control over costs, performance, and most importantly: the physical location of their data.