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DRBD

DRBD (Distributed Replicated Block Device) is an solution for that enables synchronous replication of devices across multiple networked nodes, providing and in clustered environments. As a module, it creates devices that mirror in between hosts, operating transparently to upper-layer applications and file systems. This ensures that remains consistent and accessible even in the event of node failure, making DRBD a foundational component for building resilient storage systems. DRBD supports three replication protocols to balance performance, reliability, and potential data loss: Protocol A for asynchronous replication, Protocol B for semi-synchronous operation with minimal buffering, and Protocol C for fully synchronous mirroring that guarantees no data loss on single-node failures. It leverages TCP/IP or RDMA (Remote Direct Memory Access) transports for efficient data transfer, including support for InfiniBand, iWARP, and RoCE, allowing deployment in both local high-performance setups and wide-area disaster recovery scenarios. User-space tools such as drbdadm for administration, drbdsetup for configuration, and drbdmeta for metadata management facilitate setup and monitoring, while the core driver avoids user-space overhead for optimal I/O performance. Originally developed in 1999 by Philipp Reisner, with Lars Ellenberg joining the development in 2003, DRBD has evolved over more than two decades, maintained by LINBIT, with version 9.0 introducing multi-node support for up to 16 replicas and integration with cloud-based storage pools. Released under the GNU General Public License version 2 (GPLv2), it is freely available and widely integrated into distributions like and for high-availability extensions. Key use cases include clustering for databases and messaging systems, of virtual machines, and software-defined storage solutions that prioritize data durability without shared hardware.

Introduction

Overview

DRBD, or Distributed Replicated Block Device, is an open-source module that provides real-time mirroring of across networked nodes, functioning as a shared-nothing replicated storage solution. Its primary purpose is to enable () and by replicating data synchronously or asynchronously between nodes, ensuring data redundancy and minimal downtime in the event of hardware failure or site outage. This replication occurs at the block device level, making DRBD transparent to upper-layer applications and file systems. Key features of DRBD include support for various block devices, such as physical disks or Logical Volume Manager (LVM) volumes, allowing it to integrate with existing storage infrastructures without requiring specialized hardware. It offers flexible replication protocols that prioritize either strict data consistency in synchronous mode or higher throughput in asynchronous mode, with additional capabilities like online verification and mechanisms to prevent . DRBD also integrates with cluster managers such as , enabling automated resource management and in multi-node environments. Development of DRBD began in 1999 by Philipp Reisner, with LINBIT founded in 2001 to further its development under the GNU General Public License version 2 (GPL v2), promoting widespread adoption in open-source ecosystems. As of November 2025, the latest stable version is 9.2.15, which includes enhancements for performance—such as Remote Direct Memory Access (RDMA) transport—and scalability, supporting up to 32 nodes in replication topologies.

History and Development

DRBD originated from the work of Philipp Reisner, who began developing it in 1999 as part of his master's thesis at the University of Technology, initially focusing on tools for handling that evolved into a distributed replicated storage system for . In November 2001, Reisner co-founded LINBIT in , , where DRBD was established as a core project to provide (HA) storage replication solutions. Lars Ellenberg joined LINBIT in 2003 to lead the efforts, contributing significantly to DRBD's maturation alongside Reisner. Early development saw the release of initial versions in the early , with DRBD 0.5 marking a foundational around , enabling device replication over networks. A major advancement came with DRBD 8 in January 2007, which broke previous performance barriers and introduced support for active/active clustering, allowing shared access to replicated storage in setups. In 2007, DRBD was introduced to address (WAN) replication challenges by buffering writes in , mitigating and limitations for long-distance scenarios. That same year, on December 8, 2009, DRBD was officially merged into the (version 2.6.33), enhancing its accessibility and integration within the ecosystem. DRBD 9, first released in 2015, brought substantial enhancements, including support for multi-node replication (up to 32 peers per resource), improved kernel compatibility, and better scalability for larger software-defined storage deployments, moving beyond traditional two-node clusters. In March 2025, LINBIT released DRBD version 4, a complete rewrite in a modern programming language that optimized performance for distributed environments, marking the first major update to the proxy in over a decade. LINBIT continues to maintain DRBD as an open-source project under the , with ongoing community contributions through its repository and mailing lists. The company provides enterprise-grade support and extensions via its (SDS) platform, which integrates DRBD with LINSTOR for automated management in production environments. As of 2025, recent updates have emphasized compatibility with emerging technologies, including enhanced NVMe over Fabrics (NVMe-oF) support for high-speed storage replication and integration with container orchestration systems like through CSI drivers for persistent volumes.

Core Functionality

Mode of Operation

DRBD functions as a kernel module that presents a virtual block device to the upper layers of the I/O stack, enabling transparent replication of data between s. In its core operational model, the primary handles all read and write operations to the underlying physical block device, while simultaneously mirroring writes to one or more secondary s over a connection using configurable transports such as TCP/IP or RDMA, ensuring either synchronously or asynchronously depending on the . Resource configuration in DRBD is managed through structured files in the /etc/drbd.d/ , where each —representing a replicated block device—is defined with parameters such as the resource name, the backing store (typically a physical like /dev/sda or an LVM logical volume), and network-related including connection endpoints and transport protocols. Administrators initialize on the backing devices using the drbdadm create-md command, which stores essential replication state information on the devices themselves to facilitate and . This configuration approach allows for flexible setup of multiple s on the same nodes, each operating independently. Failover in DRBD relies on role management between primary and secondary s, where the drbdadm enables manual or scripted switching—such as promoting a secondary to primary with drbdadm primary —to maintain service continuity during or failures. In multi- environments supporting up to 32 peers, mechanisms require a vote among connected s before allowing a primary role assumption, effectively preventing conditions where divergent data sets could emerge on isolated s. Automated recovery options during detection further mitigate risks by prioritizing the node with the most up-to-date data based on predefined policies. Data consistency is preserved through DRBD's use of an activity log, which records recent changes to enable quick resynchronization, and a that tracks all modified blocks on both nodes during outages or disconnections. Upon reconnection, the resync leverages this bitmap to transfer only the differing data blocks—either linearly or with optional checksum verification for accuracy—minimizing bandwidth usage and downtime while ensuring the secondary node catches up to the primary's state. This mechanism supports efficient handling of interruptions without requiring full data copies in most scenarios. For performance, DRBD directs all reads to the local backing store on the primary to achieve low-latency access, while writes are replicated to secondaries without blocking the primary unless synchronous mode is enforced. Optional caching strategies, such as adjustable disk flush intervals and support for /DISCARD operations, allow tuning for specific workloads, balancing replication reliability with I/O throughput in high-availability setups.

Replication Protocols

DRBD implements three primary replication protocols—A, B, and C—that dictate the level of between the primary and secondary nodes, balancing data consistency, performance, and tolerance to . These protocols are configured per resource in the DRBD (drbd.conf) under the net section using the protocol directive (e.g., protocol A;), allowing administrators to select the appropriate mode based on application requirements and infrastructure constraints. The choice of protocol directly influences the system's Recovery Point Objective (RPO), which measures potential , and Recovery Time Objective (RTO), which affects speed; asynchronous modes generally yield higher RPO but lower RTO, while synchronous modes minimize RPO at the cost of increased . Protocol A operates in an asynchronous manner, where a write on the primary completes immediately after the data is written to the local disk and placed into the send buffer for transmission to the secondary , without waiting for any from the peer. This approach is particularly suitable for environments with high network latency, such as geo-distributed setups, as it minimizes application wait times and maximizes throughput, though it carries the risk of if the primary fails before the secondary receives and applies the changes. In terms of trade-offs, Protocol A prioritizes performance over strict consistency, resulting in a higher RPO (potentially up to the volume of unacknowledged data in flight) but facilitating quicker failovers and lower RTO due to the absence of synchronization delays. Protocol B, often termed semi-synchronous or memory-synchronous replication, acknowledges writes after the local disk commit and confirmation that the secondary node has received the data packet (via acknowledgment), but before the peer writes it to its disk. This ensures the data is buffered on the secondary without blocking on disk I/O, providing a compromise between the speed of Protocol A and the reliability of stricter modes. It reduces the risk of compared to Protocol A—limited primarily to simultaneous failures of both nodes or network partitions—but introduces moderate latency from network round-trips, yielding a balanced RPO (minimal loss if the secondary survives) and RTO that is neither the fastest nor the slowest. Protocol B is ideal for scenarios where some tolerance for minor inconsistencies is acceptable to maintain good performance. Protocol C employs fully synchronous replication, where write acknowledgments are issued only after both the primary and secondary nodes confirm the data has been durably written to their respective disks, enforcing strict consistency across the cluster. This mode guarantees zero data divergence on single-node failures, making it the default and preferred choice for high-availability applications demanding strong durability guarantees, such as financial systems or critical databases. However, it incurs the highest latency due to the full round-trip including remote disk synchronization, which can impact throughput in bandwidth-constrained or high-latency networks, leading to the lowest RPO (effectively zero for surviving writes) but potentially elevated RTO from the added overhead during normal operations. Beyond the core protocols, DRBD includes advanced features to enhance efficiency and integrity. Trimming support, enabled automatically since DRBD 8.4.3 for underlying storage that handles TRIM/Discard commands (common on SSDs), allows efficient handling of unused blocks during synchronization and resynchronization, significantly reducing initial sync times—for instance, from hours to minutes for multi-terabyte volumes—without affecting runtime replication. Online verification provides a mechanism for periodic integrity checks, where block-level cryptographic digests (configurable via verify-alg options like sha1, md5, or crc32c in the net section) are compared between nodes using commands like drbdadm verify <resource>, enabling detection of silent data corruption without downtime; this is typically scheduled via cron for weekly or monthly runs to maintain long-term data fidelity. In DRBD 9.2 (stable release 9.2.14 as of June 2025), additional enhancements include support for encrypted replication using kernel TLS (kTLS) over the transport for secure without substantial penalties, and load balancing across multiple paths per to aggregate and provide link .

Comparisons

To Shared Storage

DRBD operates as a non-shared storage solution, where each maintains its own local copy of the , replicated directly between nodes via point-to-point connections over standard networks, thereby eliminating single points of failure inherent in shared media. In contrast, shared storage systems, such as Area Networks (SANs) or (NAS), rely on centralized hardware infrastructure, like fabrics, to provide a common pool accessible by multiple nodes simultaneously. Shared storage introduces limitations through its dependency on specialized centralized , which can create bottlenecks due to contention on the shared fabric and increase operational costs from and maintenance complexity. Additionally, these systems require sophisticated mechanisms to maintain data consistency during node failures or network partitions, as multiple nodes may attempt concurrent writes to the same storage, risking corruption without proper isolation. DRBD offers key advantages as a purely software-based solution integrated into the Linux kernel since version 2.6.33, requiring no proprietary hardware and enabling deployment on commodity servers. It supports both active/passive configurations for high availability and active/active modes when stacked with clustered file systems like GFS2, allowing multiple nodes to access the data concurrently while preserving replication integrity. In terms of , DRBD 9 enables multi-node replication across up to 32 nodes concurrently accessing the same , leveraging network for distribution without the fabric limitations of shared storage. Shared storage , however, is often constrained by the aggregate and of the central interconnect, making it less efficient for large-scale or distributed deployments. DRBD excels in use cases emphasizing geo-redundancy, such as asynchronous replication across distant sites for , whereas shared storage is better suited for multi-writer environments like clusters requiring low-latency shared access for .

To RAID-1

DRBD and traditional RAID-1 both achieve through bit-for-bit , ensuring that identical copies of are maintained to protect against failures. In RAID-1, is duplicated across multiple local disks within a single system, providing a straightforward mechanism for without upon the failure of one disk. Similarly, DRBD replicates block-level across networked nodes, effectively emulating RAID-1 functionality in a distributed to deliver the same level of . A primary distinction lies in their scope and implementation: RAID-1 operates locally using hardware controllers or software like Linux's , which combines disks into a mirrored array confined to one machine with no dependency. In contrast, DRBD extends mirroring across separate nodes over a , enabling setups where occurs in between hosts, rather than within a local storage subsystem. This networked approach in DRBD supports multi-node configurations, potentially up to 32 replicas, while RAID-1 is typically limited to two or more disks on a single controller. Performance characteristics differ significantly due to these architectural variances. Local RAID-1 arrays deliver low-latency reads and writes, as operations are handled directly by the system's controller or software without external communication, often achieving near-native disk speeds. DRBD, however, introduces overhead, particularly in synchronous modes like Protocol C, where writes are acknowledged only after replication to the remote node, potentially reducing throughput compared to local RAID-1 but allowing for seamless in clustered environments. In terms of , RAID-1 can sustain a single disk failure within its local array, automatically redirecting I/O to the surviving mirror without interrupting operations on the host. DRBD enhances this by tolerating entire node or network failures, maintaining data consistency across surviving nodes and supporting automatic resynchronization upon recovery, which extends beyond local boundaries. DRBD can be stacked atop RAID-1 configurations to combine local and remote redundancy, where a RAID-1 array serves as the backing device for DRBD replication, providing protection against both disk failures and node outages in a layered manner. This integration has been supported since DRBD 8.3.0, enabling scenarios like three-way replication for enhanced resilience.

To Other Replication Solutions

DRBD operates at the block level, replicating raw I/O between nodes, which makes it suitable for applications requiring low-latency synchronous mirroring, such as databases, whereas tools like focus on file-level synchronization for backups and are more efficient for incremental file transfers over networks but lack consistency guarantees. Similarly, GlusterFS provides file-level replication for distributed storage, enabling scalability across multiple nodes without a central server, but it introduces performance overhead for small files and is less ideal for block-oriented workloads compared to DRBD's direct block mirroring. In contrast to Ceph, which delivers distributed object, block, and file storage with built-in replication via the algorithm for automatic data placement across large clusters, DRBD excels in simplicity for two-node synchronous setups, offering full data copies akin to RAID-1 with no dependency on a running for recovery, though it scales less effectively for massive, multi-access environments. ZFS replication, primarily asynchronous and snapshot-based, complements DRBD by layering filesystem features atop replicated blocks, but DRBD provides tighter real-time synchronization without the need for manual snapshot coordination, making it preferable for high-availability scenarios over 's periodic send/receive model. Proprietary solutions like InfoScale offer comprehensive high-availability clustering with graphical management interfaces and broad application integration, such as for and , but at significant licensing costs, while DRBD remains free and open-source with native embedding for efficient deployment without . EMC's replication technologies, such as SRDF, rely on hardware-assisted synchronous mirroring for enterprise environments, providing robust multi-site but requiring specialized infrastructure, unlike DRBD's software-only approach that avoids such hardware dependencies. DRBD's strengths include its kernel-native implementation for minimal overhead in synchronous replication and seamless with clustering tools, enabling high-performance block devices for virtual machines and databases. However, it is limited to platforms and, while supporting multi-node clusters up to 32 nodes, lacks native multi-writer capabilities, often requiring stacked clustered filesystems like for concurrent access from multiple nodes. Recent enhancements in DRBD 9.x, including for multi-node consistency and LINSTOR , improve for clusters beyond two nodes as of 2025. As of 2025, DRBD Proxy version 4 enhances wide-area network (WAN) replication by buffering and compressing data in memory using Zstandard, achieving up to 14:1 ratios and faster connections over high-latency links, outperforming tools like LVM mirroring that can block I/O without such optimizations.

Applications and Integration

High Availability Use Cases

DRBD is commonly deployed in two-node active/passive clusters to provide high availability for critical applications, such as databases. In these setups, DRBD performs synchronous block-level replication between a primary and secondary node, ensuring data consistency, while Pacemaker serves as the cluster resource manager to monitor resources and automate failover. For instance, MySQL databases can be configured with DRBD replicating the data volumes, allowing Pacemaker to promote the secondary node to primary in case of failure, achieving near-zero data loss and minimizing downtime to seconds. Similar configurations apply to PostgreSQL, where DRBD mirrors the database storage, and Pacemaker handles resource migration, supporting workloads requiring strict durability like transactional systems. For multi-node active/active scenarios, DRBD can be stacked in dual-primary mode with clustered filesystems such as , enabling shared access to replicated storage across multiple nodes without a . This approach allows simultaneous read/write operations from all nodes, ideal for distributed applications like shared storage in enterprise environments, with managing resource promotion and fencing to prevent scenarios. By layering atop stacked DRBD resources, clusters achieve scalable , supporting up to dozens of nodes while maintaining through mechanisms. In contexts, DRBD enables asynchronous replication over wide-area networks () using DRBD , which buffers writes to mitigate and bandwidth limitations, facilitating geo-redundant sites. This setup reduces recovery time objectives (RTO) to minutes by allowing quick promotion of the remote upon primary site failure, without impacting production performance. For example, organizations can replicate block devices across data centers, ensuring business continuity for applications spanning continents, with configurable throttling to optimize network usage. DRBD integrates seamlessly with virtualization platforms to deliver high availability for virtual machines (VMs) and containers. In KVM environments, DRBD replicates backing for live-migrating VMs, combined with for automatic failover, ensuring VMs remain accessible during host failures. Similarly, Xen hypervisors leverage DRBD for mirrored block devices, supporting clustering with identical hardware on nodes to maintain VM uptime. For container orchestration, LINSTOR—built on DRBD—provides persistent in Kubernetes clusters as of 2025, automating volume replication and scheduling for stateful workloads. Real-world deployments highlight DRBD's role in mission-critical sectors. In , a major bank transitioned to DRBD-based LINBIT HA from proprietary solutions like Veritas Volume Replicator, achieving zero-downtime replication for data-processing services on , with lower and no . In healthcare, the National Library of Medicine utilizes DRBD and LINSTOR for compliant data mirroring of its vast biomedical resources, ensuring for billions of annual searches and supporting reliable access to health-related data for research and clinical use.

Linux Kernel Inclusion and Ecosystem

DRBD was integrated into the mainline as a loadable with 2.6.33, released in February 2010, enabling native support for distributed replicated devices without requiring external packages. This inclusion marked a significant milestone, allowing DRBD to leverage updates for enhanced stability and performance across a broad range of distributions. As of November 2025, DRBD maintains compatibility with kernels up to at least 6.17, with ongoing testing and verification ensuring seamless operation on modern releases. Configuration and management of DRBD resources are handled primarily through dedicated tools: drbdadm serves as the high-level administrative utility, parsing configuration files to orchestrate resources, connections, and devices, while drbdsetup provides low-level control for direct interaction with the kernel module, such as adjusting paths or resizing volumes. For monitoring, drbdmon offers real-time status checks and automated actions on DRBD resources via a user-friendly , complementing integration with exporters that expose metrics like replication status, I/O throughput, and connection health for centralized observability in cluster environments. Within the ecosystem, DRBD integrates tightly with clustering frameworks such as Corosync for reliable messaging and for resource management, facilitating automated and high-availability setups in multi-node configurations. LINBIT's LINSTOR acts as a software-defined storage orchestrator, automating DRBD provisioning, , and snapshotting for scalable deployments in virtualized or cloud-native environments, including (SDN) infrastructures. Extensions like DRBD enhance this ecosystem by enabling event-driven scripting through plugins, allowing custom responses to state changes such as peer disconnections or role promotions without full cluster stack dependency. DRBD also demonstrates strong with contemporary filesystems, including for its snapshot capabilities and for high-performance workloads, ensuring replicated block devices can support diverse storage needs. In September 2025, DRBD 9.2.15 was released, incorporating various fixes and enhancements for improved stability and . DRBD continues to support broader architecture , including optimized performance on ARM64 systems, aligning with growing adoption in data centers and .

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