Red Hat Ceph Storage: Object storage performance and sizing guide

Red Hat Ceph Storage is a proven, petabyte-scale, object storage solution designed to meet the scalability, cost, performance, and reliability challenges of large-scale, media-serving, savvy organizations. Designed for web-scale object storage and cloud infrastructures, Red Hat Ceph Storage delivers the scalable performance necessary for rich media and content-distribution workloads.

While most of us are familiar with deploying block or file storage, object storage expertise is less common. Object storage is an effective way to provision flexible and massively scalable data storage without the arbitrary limitations of traditional proprietary or scale-up storage solutions. Before building object storage infrastructure at scale, organizations need to understand how to best configure and deploy software, hardware, and network components to serve a range of diverse workloads. They also need to understand the performance and scalability they can expect from given hardware, software, and network configurations.

This reference architecture/performance and sizing guide describes Red Hat Ceph Storage coupled with QCT (Quanta Cloud Technology) storage servers and networking as object storage infrastructure. Testing, tuning, and performance are described for both large-object and small-object workloads. This guide also presents the results of the tests conducted to evaluate the ability of configurations to scale to host hundreds of millions of objects.

After hundreds of hours of [Test ⇒ Tune ⇒ Repeat] exercises, this reference architecture provides empirical answers to a range of performance questions surrounding Ceph object storage, such as (but not limited to):

  • What are the architectural considerations before designing object storage?
  • What networking is most performant for Ceph object storage?
  • What does performance look like with dedicated vs. co-located Ceph RGWs?
  • How many Ceph RGW nodes do I need?
  • How do I tune object storage performance?
  • What are the recommendations for small/large object workloads?
  • What should I do? I’ve got millions of objects to store.

And the list of questions goes on. You can unlock the performance secrets of Ceph object storage for your organization with the help of the Red Hat Ceph Storage/QCT performance and sizing guide.

Library of Ceph and Gluster reference architectures – Simplicity on the other side of complexity

The Storage Solution Architectures team at Red Hat develops reference architectures, performance and sizing guides, and test drives for Gluster- and Ceph-based solutions. We’re a group of architects who perform lab validation, tuning, and interoperability development for composable storage services with target workloads on optimized server and network configurations. We seek simplicity on the other side of complexity.

At the end of this blog entry is a full library of our current publications and test drives.

In our modern era, a top company asset is pivotability. Pivotability based on external market changes. Pivotability after unknowns become known. Pivotability after golden ideas become dark alleys. For most enterprises, pivotability requires a composable technology infrastructure for shifting resources to meet changing needs. Composable storage services, such as those provided by Ceph and Gluster, are part of many companies’ composable infrastructures.

Composable technology infrastructures are most frequently described by the following attributes:

  • Open source v. closed development.
  • On-demand architectures v. fixed architectures.
  • Commodity hardware v. proprietary appliances.
  • Cross-industry collaboration v. isolated single-vendor silos.

As noted in the following figure, a few companies with large staffs of in-house experts can create composable infrastructures from raw technologies. Their large investments in in-house expertise allows them to convert raw technologies into solutions with limited pre-integration by technology suppliers. AWS, Google, and Azure are all examples of DIY businesses. A larger number of other companies, also needing composable infrastructures, rely on technology suppliers and the community for solution pre-integration and guidance to reduce their in-house expertise costs. We’ll label them “Assisted DIY.” Finally, the majority of global enterprises lack the in-house expertise for deploying these composable infrastructures. They rely on public cloud providers and pre-packaged solutions for their infrastructure needs. We’ll call them “Pre-packaged.”

Brent_Slide

The reference architectures, performance and sizing guides, and test drives produced by our team are primarily focused on the “Assisted DIY” segment of companies. Additionally, we strive to make Gluster and Ceph composable storage services available to the “Pre-packaged” segment of companies by using what we learn to produce pre-packaged combinations of Red Hat software with partner hardware targeting specific workload use cases.

We enjoy our roles at Red Hat because of the many of you with whom we collaborate to produce value.  We hope you find these guides useful.

Team-produced with partner collaboration:

Partner-produced with team collaboration:

Pre-packaged solutions:

Hands-on test drives:

Storage and Big Data Tutorial live at Strata+Hadoop World with Red Hat, Cloudera and Intel

 

Red Hat’s Greg Kleiman, director of storage and big data, meets up at Strata+Hadoop World 2015 with Brandon Draeger, director of marketing and strategy, big data solutions at Intel, and David Tishgart, director of marketing at Cloudera to discuss what interesting new trends they are seeing at the show. One revelation in particular will be most surprising…see the video

Continue reading “Storage and Big Data Tutorial live at Strata+Hadoop World with Red Hat, Cloudera and Intel”

You Won’t Believe Where You’d Find Big Data at the Soccer World Cup

The vast range of possibilities and outcomes in sport makes it fertile ground for number crunchers. Analysts use sophisticated algorithms to factor in everything from temperature and humidity to the materials used in the manufacturing of tournament equipment in order to predict results.

Many of these factors are prone to volatility over the course of a sporting event, making real time analysis even more challenging. A case in point is the Goldman Sachs model built on regression analysis of all team results leading up to the tournament that had to be updated mid-tournament. They predict a 2-1 victory for Brazil over the Dutch in the finals (which of course we now know is impossible after Brazil’s stunning defeat against Germany in the semi-finals).

Continue reading “You Won’t Believe Where You’d Find Big Data at the Soccer World Cup”

Summit Spotlight: Don’t Miss These Storage Tracks and Sessions

Summit Spotlight: Don’t Miss These Storage Tracks and Sessions

Red Hat Summit kicks off this year from April 14-17th in San Francisco, CA. We’ve organized more than 150 breakout sessions, each with a unique solution-focus, but attendees of all experience levels will see a variety of products, demos, customer success stories, and more.

Continue reading “Summit Spotlight: Don’t Miss These Storage Tracks and Sessions”

Manageability Becoming A Key Component of Open, Software Defined Storage (Red Hat Storage Console Now Available!)

By Steve Bohac, Red Hat Storage Product and Solution Marketing

Open software-defined storage is transforming the way organizations tackle their data management challenges. We are seeing that more and more customers are realizing that an open software-based approach can create opportunities to significantly reduce costs and efficiently contend with their exploding data landscape. Additionally, open software-defined storage solutions can help discover new roles and value for enterprise storage.

Continue reading “Manageability Becoming A Key Component of Open, Software Defined Storage (Red Hat Storage Console Now Available!)”

Red Hat’s Approach with Open, Software-Defined Storage (A Four Part Series)

Today’s Post: Red Hat Storage Server In Action

By Steve Bohac, Red Hat Storage Product Marketing

Several weeks ago, we posted the blog “Open Software Defined Storage – Don’t Get Fooled By The False ‘Open’ and Get Locked-In Again”. Today’s entry is the conclusion of this four part mini-series.

We understand how difficult it is to optimize your storage for innovation and growth, and our goal is to help enterprises on their journey to convert their data centers from cost centers into revenue-generators. Red Hat Storage Server has helped businesses of all varieties achieve their objectives. Here’s how open, software-defined storage has helped a few organizations get to the next level:

Continue reading “Red Hat’s Approach with Open, Software-Defined Storage (A Four Part Series)”

The beauty of little boxes, and their role in the future of storage

If you’re into 1960’s songs about middle class conformity, you may not have a positive association with lots of interchangeable “little boxes.” In storage, however, those little boxes are not only beautiful but the wave of the future. Insider (free registration required)

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Asteroids, nuclear war and data center outages: Surviving big disasters by being small

Imagine that it’s the height of the Cold War, and you are trying to design an approach to command, control, and communications that can survive a full-scale nuclear attack.

One approach is to build a small number of communications nodes that are highly resilient. For example, you can build communications bunkers a mile deep under mountains, or keep a pair of specially-outfitted jets continuously in the air above Nebraska. Let’s call this the Big Box approach.

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Storage is a hard problem with a soft(ware) solution

My wife and I are both dog people, but we have mixed views regarding another contentious issue: hardware versus software.

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Big data SMAQ-down

The term "big data," is getting thrown around a lot these days, and in certain circles it is threatening to overtake "cloud" as the most overused and misused term in IT.

Interestingly, some of the large, traditional storage vendors are embracing the term big data, using it as an umbrella term for all large collections of data and hence an umbrella term for all of their offerings. A more nuanced understanding of big data actually shows it to be antithesis of both the technology and the business models of the traditional storage vendors.

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Update on GlusterFS 3.3 Beta – Unified File and Object Storage

On July 20th we announced and delivered the first beta of  GlusterFS 3.3, which featured unified file and object storage. I am excited to give you an update on how things are going with the beta and how we see our customers deploying this innovative file and object storage technology.

At a glance – use cases for GlusterFS 3.3:

  • Can eliminate the need for gateway devices bridging the data center to the cloud.
  • Back up email for Exchange environments
  • Global storage for photo processing and archiving
  • Easier onramp to cloud storage
  • On-premise, S3-like object storage for private cloud

Both our public beta testing and testing at select enterprise customer sites continues on schedule, and unique deployments of this innovative technology are being crafted which leverage the unified file and object storage capability. There is still space available in the private beta and if you are interested in participating then email us at glusterfs3.3beta@gluster.com.

Email Backups On-premise and in the Cloud

I want to share with you some of the ways in which our unified file and object storage can be used. One way is for email back-up and archive. Exchange environments can back up to a GlusterFS NAS target and then move the backup files out as objects to S3 – in many cases this is eliminating the need for gateway devices bridging the data center to the cloud.

Data Processing and Archiving – Photos

Another example is digital photo processing, editing and archiving where photos are stored in files as well as objects simultaneously within GlusterFS. The uniqueness of GlusterFS is that the object can be accessed from any application that accesses objects for other business purposes, from any cloud. In some cases this includes other photo processing applications (editing items such as photo attributes and color corrections). This is an example where Gluster provides file and object storage as well as an object archive.

Easier Onramp to Public Cloud Storage

Also, we see customers who have deployed our NAS in the cloud via Amazon Web Services, or GoGrid, developing creative solutions that export objects from the data center to the cloud via HTTP (lower protocol overhead as compared to NFS and CIFS) and directly into GlusterFS unified file and object in the cloud. By moving information quickly, and having it immediately available for processing, customers save both time and money and will improve their overall operational efficiency. For some customers this means faster time to-market for their products and for others it means faster report generation and speedier, more well informed business decisions. We’re pleased to be able to further accelerate our customers’ ability to move to the cloud.

On-premise S3-like Object Storage

Additionally, for those customers who have been looking for an on-premise, cost effective, object storage system, they now have the best of both worlds – highly available, high performance, unified file and object storage deployable in a cost effective manner. On-premise customers can now deploy an S3-like private cloud storage capability on commodity hardware.

Contact us to learn more about leveraging unified file and object storage in your environment.

All the best,

Tom Trainer

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