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Cloud Services / Storage

Google Cloud Offers POSIX-Compliant File Storage Through Red Hat Gluster

Feb 18th, 2016 9:05am by
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Red Hat’s data management software package, Red Hat Gluster Storage (RHGS) in the cloud, is on the Google Cloud Platform (GCP).

“Red Hat Gluster Storage offers a highly available and fault tolerant shared file system that can scale vertically and horizontally,” wrote Vic Iglesias, Google cloud solutions architect, in a blog post announcing the availability. “Red Hat Gluster Storage makes use of compute instances with disks attached in order to provide a distributed, scale-out file system.

The arrival or RHGS on GCP is a continuation of the partnership between Google and Red Hat. Back in 2014, Red Hat Enterprise Linux (RHEL) was made available on Google Cloud Platform allowing customers to run RHEL on GCP as if they were running it on premise. More recently, the two companies brought Red Hat’s OpenShift — managed container application platform — to GCP customers.

“Think of it as next wave of solutions. Storage can now be served up on Google Compute Cloud,” Ranga Rangachari, Red Hat vice president and general manager of storage and big data said in a phone interview.

RHGS is Red Hat’s commercially supported distribution of the open source GlusterFS scale-out network-attached storage file system. With Google’s participation, Red Hat Gluster Storage is now available on all three major public cloud platforms — AWS, Microsoft Azure and Google Cloud Platform.

Red Hat Gluster Storage is fully POSIX compliant. Rangachari said that the POSIX-compatible distributed file system makes deploying a variety of applications to Google Cloud Platform possible by providing a compatible, universal storage platform without having to rewrite applications.

RHGS also enables system designers to deploy the same storage technology on premises as well as on public cloud platforms like Google Cloud, with elastic scalability.

Now GCP customers can create a single, more secure and highly available storage pool that can scale to petabytes of data in minutes without disruption by aggregating multiple Google Persistent Disks.

“Each node in your cluster can leverage disks of up to 64TB in size and with up to 15,000 IOPS,” Iglesias wrote.

“The great thing with Red Hat Gluster Storage is that customers can run it in physical environment, virtual environments; public and private cloud environments. It enables organizations to run whatever they choose based on their workload and things like SLAs,” said Rangachari.

It empowers admins to manage storage with unprecedented ease as it doesn’t matter where the data or application is; they can easily move their workload between on-premise and public cloud.

Rangachari shared some use cases of Red Hat Gluster Storage. There are Red Hat customers in the media rendering space — graphic and movie studio type of environments — where they want scale both on compute and storage side. That these customers typically do is run such operations in these public clouds because then they are not restrained by the four walls of a data center.

Many customers start off with in-house infrastructure. But when they need excess capacity, instead of going out and building their own storage structure they just exploit the scalable nature of RHGC and expand, like an accordion, to the public cloud.

One interesting use-case is disaster recovery. Since RHGC has inherent replication and distributed file capabilities, it can be integrated with the disaster recovery plan. It actually replicated the data from private data centers to the public cloud. And if there is any disaster, customers can switch to the cloud and start using it nearly instantly.


Also easing the path to cloud use if Red Hat’s Certified Cloud and Service Provider (CCSP) program, which assures that all of the Red Hat products that run as part of CCSP are fully supported by the company.

All the value that they get through Red Hat subscription moves with them to these public clouds.

Red Hat is a sponsor of The New Stack

Feature image via Pexels.

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