In today’s competitive business environment, cloud hosting for enterprise-level deployments requires a highly scalable storage solution to streamline and manage important business data. With technology and best practices rapidly moving towards cloud-based services to keep pace with evolving businesses, Ceph Storage (Ceph) emerged as a solution that meets the need for a software storage platform that supports a highly sustainable growth model.
What is Ceph Storage?
Ceph is an open-source, software-defined storage platform that unifies object, block, and file storage into a single cluster. Anyone can download the raw open-source code directly from Ceph.io. The Linux Foundation manages the open-source project to maintain neutrality, while IBM, Canonical, and specialized storage companies distribute commercial, supported versions of it to enterprises. Ceph runs on standard, commodity hardware and is commonly used in modern cloud and virtualization environments such as Kubernetes and OpenStack.
For a complete overview of Ceph Storage, read the blog: Ceph Block Storage [A Complete Explanation]
What are the pros and cons of Ceph storage?
Ceph Storage is highly valued for its scalability and unified architecture (object, block, and file). However, its primary drawbacks are extreme operational complexity, steep learning curves, and higher network latency. It is ideal for small, general-purpose workloads such as batch jobs, archives, general file service and non-latency sensitive workloads. But for business-critical, latency-sensitive databases, real-time analytics, and high-transactional workloads, Ceph doesn’t perform best or is cost-inefficient.
Pros of Ceph Storage (Advantages)
- Unified Storage Ecosystem
- Horizontal Scalability
- High Availability and Self-Healing
- No Vendor Lock-In
- Cloud Integration: integration with orchestration platforms such as Kubernetes and OpenStack
Cons of Ceph Storage (Disadvantages)
- High Operational Complexity
- Network & Performance Overhead
- Resource and Node Overhead
- Expensive Recovery Operations
- Suboptimal Flash Utilization
What are common operational challenges in managing Ceph clusters?
Ceph is practically unmatched in its ability to secure data safe on cheap, commodity hardware, but it requires continuous monitoring, aggressive recovery throttling, and rigorous network discipline to keep the cluster from competing for resources with your business-critical production workloads.
Managing a cluster on Day 2 is often described by systems engineers as “infrastructure on hard mode,” because it is completely its resilience relies on complex internal logic that can easily trigger operational headaches if not meticulously managed. The most common operational challenges encountered when managing Ceph clusters include:
- Node failure and recovery. If not tightly throttled, Ceph’s self-healing process can devour your cluster’s internal network bandwidth and disk I/O. The impact on your business is that production applications experience massive latency spikes and performance degradation.
- Capacity thresholds. When a cluster reaches ~95% capacity, Ceph blocks all incoming write operations entirely. The implications are for downstream applications that will instantly crash or throw errors. Ironically, because the cluster is locked, deleting data to free up space becomes a stressful exercise, as even the metadata generated during deletion requires write permissions.
- Network fragility. Ceph is essentially a network application disguised as a storage system; it requires absolute network perfection. To maximize throughput, administrators often enable Jumbo Frames. If a single switchport, NIC, or Kubernetes CNI component along the data path is misconfigured and drops back to a standard MTU, large packets will silently drop.
- The Knowledge Tax. Out-of-the-box defaults are rarely optimized for mixed production workloads. Furthermore, performing major version upgrades across hundreds of active production nodes requires flawless execution. Managing Ceph without automated orchestrators requires writing custom playbooks for everything from a routine disk swap to architecture updates. Organizations must invest heavily in highly specialized SREs to manage Ceph implementations.
Ceph’s Hidden Tax
While Ceph is a powerful and flexible storage platform, it carries a heavy “operational tax” in the form of extreme day-2 management complexity. Running Ceph in production requires specialized engineering resources to continuously handle multi-daemon architectures, placement group tuning, and strict recovery throttles to prevent automatic data rebalancing from severely impacting client application performance.
Ceph is inefficient for modern, high-performance NVMe over TCP (NVMe/TCP) block storage workloads. Instead of a native connection, Ceph relies on an external gateway layer to translate its block images into NVMe namespaces, which adds extra infrastructure to size and maintain, introduces a network tax, and creates performance bottlenecks.
As a leaner alternative, Lightbits LightOS embeds NVMe/TCP natively into the storage platform without a translation layer, delivering up to 16X faster performance for block workloads, reducing TCO by over 50%, and requiring up to 5X less hardware footprint than a comparable Ceph deployment.
How does Ceph performance compare to NVMe-based storage?
When comparing the performance of Ceph to Lightbits LightOS, it boils down an architectural difference: a highly versatile, general-purpose unified storage system (Ceph) vs. a lean, purpose-built, ultra-low latency block storage system (LightOS).
The performance differences come down to several critical architectural factors:
- The Data Path: Native NVMe/TCP vs. Gateway Translation. The primary reason Lightbits outperforms Ceph is the way data moves from the client application to the physical drive.
- IOPS and Throughput Density. Because Lightbits strips away the software translation layers, it achieves much higher performance density per RU.
- Tail Latency Consistency. Average latency is less important than tail latency, which causes applications to stutter. Lightbits uses specialized queue management and direct flash drive abstractions to ensure ultra-low, predictable tail latency, ensuring consistent application responsiveness even under heavy loads.
- Performance Degradation During Failures. Lightbits features decoupled data protection and intelligent flash management that isolates drive rebuilding processes. This ensures that if a hardware failure occurs, data is reconstructed efficiently with minimal impact on active client I/O.
| Performance Factor | Ceph Storage | Lightbits LightOS |
|---|---|---|
| Primary Workload Optimization | Unstructured data (Object/File) & capacity-first workloads | High-performance, latency-sensitive workloads |
| NVMe/TCP Execution | Via translation gateway (adds hops & latency) | Native (direct end-to-end NVMe transport) |
| Relative IOPS Scale | Baseline standard performance | Up to 16X higher IOPS than Ceph |
| Tail Latency | Higher, unpredictable during network/cluster jitter | Lowest & highly predictable (mimics local flash) |
For a complete explanation of head-to-head performance and resiliency analysis between Lightbits software-defined storage and Ceph Storage, download the technical white paper.
NVMe/TCP Support for Ceph
Ceph recently unveiled a technology preview for NVMe/TCP connectivity. However, this implementation involves integrating Ceph’s NVMe-oF gateway. Figure 2 illustrates how the gateway exports RADOS Block Devices (RBD) to clients over NVMe/TCP. This model introduces additional architectural complexity, leading to bottlenecks and increased storage-network latency due to the extra hop and protocol translation.
While Ceph strives to support modern high-speed protocols such as NVMe/TCP, the current approach relies on protocol gateways and translation layers atop the existing Ceph architecture. This model may improve Ceph’s interoperability, but it deviates from the initially intended design of NVMe/TCP fabric architectures. This design is implemented by Lightbits and is meticulously engineered to offer direct, high-performance host connectivity.
What are the hardware requirements for running Ceph efficiently?
Running a Ceph storage cluster efficiently in a production environment requires several computers connected to one another, at least 3 physical nodes (4–5 recommended) to establish a proper failure domain. Each of these connected computers within that cluster is known as a node. Below are some of the tasks that must be distributed among the nodes within the network:
- Monitor nodes: Ceph-MONs primarily monitor the status of individual nodes in the cluster, particularly object storage devices, managers, and metadata servers. To ensure maximum reliability, it is recommended to have at least three monitor nodes.
- Object Storage Devices: Ceph-OSDs are background applications that handle actual data management and are responsible for storage, replication, and data restoration. For a cluster, it is recommended to have at least three ODSs.
- Managers: Ceph-MGR works in tandem with Ceph-MONs to monitor system load, storage usage, and node capacity.
- Metadata servers: Ceph-MDS helps to store metadata such as file names, storage paths, and timestamps of files stored in the CephFS for several performance reasons.
How do organizations scale Ceph storage?
Organizations scale Ceph storage horizontally (scaling out rather than scaling up). Instead of buying a larger, more expensive storage chassis when they run out of capacity, organizations add more standard disks or server nodes to their existing cluster.
To scale successfully without triggering performance drops or outages, systems engineering teams follow strict architectural blueprints with Ceph Storage:
- Maintain Hardware Symmetry: Successful organizations scale Ceph in standardized building blocks (e.g., adding nodes with identical CPU, RAM, and drive configurations). Mixing asymmetrical hardware (such as combining small, old HDDs with large, new NVMe drives in the same storage tier) results in erratic performance and unpredictable data rebuild speeds.
- Pre-Provision Network Headroom: Data rebalancing creates massive amounts of internal, east-west network traffic. Organizations scaling beyond a few hundred TBs use bonded networks to ensure data rebalancing doesn’t starve client application traffic.
- Leverage the PG Autoscaler: Ceph organizes data into logical units called Placement Groups (PGs). As a cluster scales out, the data-to-PGs ratio changes. Using Ceph’s automated PG Autoscaler to scale PGs over time prevents data from “bunching up” unevenly on specific disks.
- Scale the Failure Domains: Successful organizations define failure boundaries using the CRUSH map. When scaling out, they distribute new nodes evenly across different server racks. This ensures that if an entire new rack loses power, Ceph’s data replicas are safely sitting in a completely separate physical rack.
Ceph Alternatives
While Ceph is a versatile, unified storage system, its architecture, originally designed for HDDs, can be a bottleneck for I/O-intensive workloads. Ceph’s block storage component has inherent architectural limitations that can limit its performance for extremely demanding, low-latency block workloads. When a specific workload demands the highest possible performance, minimal latency, and optimal resource utilization, the specialized alternatives listed below can provide a significant advantage.
Ceph Alternatives
| Alternative | Key Strengths | Use Case |
|---|---|---|
| GlusterFS | Traditionally file-centric, it’s a distributed storage system that can be used for block-based workloads. | Environments where a simple, effective, and open-source solution is needed, especially for file-based workloads with some block requirements. |
| Lightbits | Disaggregated and SDS architecture, high IOPS density, low latency, and efficient resource use. Natively designed with NVMe/TCP | Organizations need a flexible and scalable solution for a variety of storage workloads, with a built-in management system. |
| QuantaStor | A unified SDS platform supporting block, file, and object storage with a focus on simplifying management. | Organizations need a flexible, scalable solution for a variety of storage workloads, with built-in management. |
| OpenEBS | A container-native storage solution for Kubernetes offering various storage engines, | Kubernetes deployments where persistent storage needs to be tightly integrated with the container orchestration platform. |