|Industry||Software, computer storage|
Number of locations
|Anand Babu (AB) Periasamy (CTO) and Hitesh Chellani (CEO)|
Number of employees
Gluster Inc. was a software company that provided an open source platform for scale-out public and private cloud storage. The company was privately funded and headquartered in Sunnyvale, California, with an engineering center in Bangalore, India. Gluster was funded by Nexus Venture Partners and Index Ventures. Gluster was acquired by Red Hat on October 7, 2011.
The name Gluster combined GNU and cluster. Despite the similarity in names, Gluster is not related to the Lustre file system and does not incorporate any Lustre code. Gluster based its product on GlusterFS, an open-source software-based network-attached filesystem that deploys on commodity hardware. The initial version of GlusterFS was written by Anand Babu Periasamy, Gluster's founder and CTO. In May 2010 Ben Golub became the president and chief executive officer.
Red Hat became the primary author and maintainer of the GlusterFS open-source project after acquiring the Gluster company in October 2011. The product was first marketed as Red Hat Storage Server, but in early 2015 renamed to be Red Hat Gluster Storage since Red Hat has also acquired the Ceph file system technology.
The GlusterFS architecture aggregates compute, storage, and I/O resources into a global namespace. Each server plus attached commodity storage (configured as direct-attached storage, JBOD, or using a storage area network) is considered to be a node. Capacity is scaled by adding additional nodes or adding additional storage to each node. Performance is increased by deploying storage among more nodes. High availability is achieved by replicating data n-way between nodes.
Public cloud deployment
For public cloud deployments, GlusterFS offers an Amazon Web Services (AWS) Amazon Machine Image (AMI), which is deployed on Elastic Compute Cloud (EC2) instances rather than physical servers and the underlying storage is Amazon's Elastic Block Storage (EBS). In this environment, capacity is scaled by deploying more EBS storage units, performance is scaled by deploying more EC2 instances, and availability is scaled by n-way replication between AWS availability zones.
Private cloud deployment
A typical on-premises, or private cloud deployment will consist of GlusterFS installed as a virtual appliance on top of multiple commodity servers running hypervisors such as KVM, Xen, or VMware; or on bare metal.
|Developer(s)||Red Hat, Inc.|
3.12.9 / 22 August 2018
4.1.4 / 6 September 2018
|Operating system||Linux, OS X, FreeBSD, NetBSD, OpenSolaris|
|Type||Distributed file system|
|License||GNU General Public License v3|
GlusterFS is a scale-out network-attached storage file system. It has found applications including cloud computing, streaming media services, and content delivery networks. GlusterFS was developed originally by Gluster, Inc. and then by Red Hat, Inc., as a result of Red Hat acquiring Gluster in 2011.
In June 2012, Red Hat Storage Server was announced as a commercially supported integration of GlusterFS with Red Hat Enterprise Linux. Red Hat bought Inktank Storage in April 2014, which is the company behind the Ceph distributed file system, and re-branded GlusterFS-based Red Hat Storage Server to "Red Hat Gluster Storage".
GlusterFS aggregates various storage servers over Ethernet or Infiniband RDMA interconnect into one large parallel network file system. It is free software, with some parts licensed under the GNU General Public License (GPL) v3 while others are dual licensed under either GPL v2 or the Lesser General Public License (LGPL) v3. GlusterFS is based on a stackable user space design.
GlusterFS has a client and server component. Servers are typically deployed as storage bricks, with each server running a glusterfsd daemon to export a local file system as a volume. The glusterfs client process, which connects to servers with a custom protocol over TCP/IP, InfiniBand or Sockets Direct Protocol, creates composite virtual volumes from multiple remote servers using stackable translators. By default, files are stored whole, but striping of files across multiple remote volumes is also supported. The final volume may then be mounted by the client host using its own native protocol via the FUSE mechanism, using NFS v3 protocol using a built-in server translator, or accessed via gfapi client library. Native-protocol mounts may then be re-exported e.g. via the kernel NFSv4 server, SAMBA, or the object-based OpenStack Storage (Swift) protocol using the "UFO" (Unified File and Object) translator.
Most of the functionality of GlusterFS is implemented as translators, including file-based mirroring and replication, file-based striping, file-based load balancing, volume failover, scheduling and disk caching, storage quotas, and volume snapshots with user serviceability (since GlusterFS version 3.6).
The GlusterFS server is intentionally kept simple: it exports an existing directory as-is, leaving it up to client-side translators to structure the store. The clients themselves are stateless, do not communicate with each other, and are expected to have translator configurations consistent with each other. GlusterFS relies on an elastic hashing algorithm, rather than using either a centralized or distributed metadata model. With version 3.1 and later of GlusterFS, volumes can be added, deleted, or migrated dynamically, helping to avoid configuration coherency problems, and allowing GlusterFS to scale up to several petabytes on commodity hardware by avoiding bottlenecks that normally affect more tightly coupled distributed file systems.
GlusterFS provides data reliability and availability through various options of replication: replicated volumes and Geo-replication. Replicated volumes ensure that exists at least one copy of each file across the bricks, thus if one fails, data can be still accessed. Geo-replication provides a master-slave model of replication, where volumes are copied across geographically distinct locations. This happens asynchronously and it is useful for backup of data in case of failure.
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