Storage Tutorial: The Future of Big Data

Welcome to 2015 and the exciting world of storage and Big Data! Want to know what the new year holds for Big Data?

Check out this storage tutorial with Red Hat’s Brian Chang chatting with Greg Kleiman, (Director, Big Data, Red Hat) and Irshad Raihan (Big Data Product Marketing, also at Red Hat) who give their storage predictions for 2015.

In the video the group discusses the importance of enterprise data scientists and their role in helping enterprises succeed both in their current business model while also opening new business opportunities. They talk about how to capture, cultivate, and manage Big Data, especially the new challenge of doing so in real time. They look at monetizing data not only in data-based businesses but spreading into more traditional industries such as the car industry. And, last but not least, they discuss how to translate Big Data into a viable and easily accessible revenue stream.

For more predictions for 2015 from even more people at Red Hat, check out this great big roundup post from a few weeks back. And to learn more about Big Data at Red Hat, be sure to check out our solutions page.

Storage Tutorial: 2015 IT Predictions with Ceph

Back in April 2014, Red Hat acquired Ceph provider Inktank. Now that the team is a part of Red Hat, we get to pick their brains for thoughts on 2015! To that end, Storage Tutorial Mastermind (and brand manager) Brian Chang sat down with Ross Turk, product marketing manager for Red Hat Storage, Danielle Womboldt, director of marketing for Ceph, and Patrick “Scuttlemonkey” McGarry, community manager for Ceph for their predictions. We’re summarizing it a bit here, but for the entire conversation check out the video below!

Goals for 2015

Ross:

Last year, halfway through, Ceph 1.2 was released. It had new features such as cached tiering and erasure coding. This year the focus is going to be solidly on stability, reliability, packaging, quality assurance. And also spending a lot of time thinking about what it means to be part of a portfolio that includes a product such as Gluster.

Danielle:

From a marketing perspective, we’re trying to keep the coolness and uniqueness that Inktank brought to Ceph. And also looking to keep a separate user community.

Patrick:

From the community, we can declare this the year of CephFS.

We had a lot of community/partner participation that has gone a long way for tuning and performance. We’re expecting amazing advancements in tuning and performance across the entire Ceph platform, not just CephFS — hardware integrations such as with Ethernet drives, flash storage stuff and networking hardware. Lot’s of partners are working to ensure their products work with Ceph.

A prediction

Patrick:

We’ll see an industry evolution as people think about things like Ceph — OpenStack, CloudStack’s. We’ll start to see a paradigm shift in how developers treat their infrastructure.

And watching OpenStack blossom will be fun in 2015.

Segue: Ceph and OpenStack

Brian:

2015 will be a defining year for OpenStack — why is Ceph the de facto storage backend for it?

Ross:

It’s interesting to watch over the years how the Ceph and OpenStack community have worked in parallel. The last OpenStack user survey showed that Ceph was the leading distributed storage platform for OpenStack. But an interesting thing happened, in the most recent survey is that Ceph is more popular than the default — Directly Attached Storage.

The way you manage Ceph and OpenStack are similar — they are both software. It isn’t like a cloud architect deploying OpenStack and calling an IT department to get a proprietary client set up for storage for virtual machines…it can be used with the same hardware profile that can be used for OpenStack.

What’s coming for the Ceph community in 2015?

Danielle:

Ceph days! The global Ceph day program will be exciting. Six Ceph Days were run in 2014. Highlights include over 100 attendees in each city, over 100 presentations to the community. These bring together experts, partners, and the community. We’re planning to have even more in 2015 and will be rolled out across the globe, and one each month this year.

On to the video

To learn what cities Ceph Days may be coming to, and to hear about plans for the next Google Summer of Code, get that video below going now!

GlusterFS 4.0: bold new release

gluster

Questions about the GlusterFS 4.0 release? Then this is the video for you. Brian Chang, of Red Hat, interviews Jeff Darcy, Red Hat Principle Software Engineer and GlusterFS Architect to get the inside take on the newest GlusterFS.

Focusing on long-term features, this release, which Darcy calls “very adventurous, very bold,” introduces a host of new features. For example, the enhanced scalability features — which provide a strong focus on management features — delivers an increased robustness. Hand-in-hand with scalability features are multiple features that focus on small file and large directory performance. In addition, driven by a very inclusive, very open planning process, GlusterFS 4.0 also addresses multiple types of tiering, For more information on these, and additional, GlusterFS 4.0 features, click here.

Fantasy Football proves Big Data is for Everyone

The Fantasy Sports Trade Association, an organization formed around enabling the white collar set to fulfill their dream of becoming the general manager of an imaginary sports franchise, estimates that there are 41.5 million people playing fantasy sports in North America.

If you don’t know much about fantasy sports, fear not – we’ll break it down for you. But, more importantly, we’re going to talk about how fantasy sports are an analogy for why big data impacts us all…and why.

touchdown

Photo credit: M P R

Fantasy sportsball

In fantasy sports, groups of people agree amongst themselves to create fictional teams of players – consisting of real people from a sport such as football or baseball – and then keep track of the performance of each player in order to score points. For example, points are scored depending on how many touchdowns a football player achieves, or how many yards they’ve run. The persons in a league who score the most points end up winning prizes or taking the lion’s share of a pool of money.

No player can exist on two teams at once so, at the beginning of the “season,” players hold a draft to select who will be on their team. And this is where the big data plays a significant role. In order to select players sure to score points for them, fantasy sports participants look at the statistics of each athlete. How many touchdowns or home runs have they achieved? How accident-prone are they? How likely to pass a ball or puck to someone are they? Do they perform better in a stadium with or without a dome?

Selection is generally achieved by looking at the online equivalent of a sports trading card. This page at NFL.com is an excellent example…just start clicking names and try to ingest those numbers. Then read articles about the athletes, get opinions from pundits and co-workers. This process would no doubt have obsessive compulsives in an absolute froth!

And then there’s the recent revelation from Intel, which showed there can be up to 20,000 points of data collected and available for a single game.

Pass the ball to big data

Compared to the information out there that could aid in decision making, what fantasy spots enthusiasts have access to now is essentially the top two or three micrometers of an iceberg.

Imagine if everyone had access to a system that trawled athletes social media profiles to learn where they’ve checked in, when, and with whom. That system would then look at what they ordered at a restaurant, if they shared such information, and what their companions ordered. Look at the cleanliness score of the restaurant to determine how likely a player is to get sick. Determine how often an athlete is to get drunk depending on the comments – or the quality of comments – left by companions after long nights on the town.

This level of knowledge would absolutely affect decision making in fantasy sports. And it can affect everyday life, too.

Big data day to day: A scenario

Imagine if a butcher was selecting haunches of meat for the day and could see a history of where the animal has been, how its health fared during its lifetime, and how other haunches of meat from the animal have been reviewed by customers.

But even this example is just scratching the surface.

Imagine if the butcher had a system that could analyze the weather in the region the animal came from, the quality of the feed, and what kinds of chemicals (if any) the animal had been provided. This holistic view of the animal’s life can help make a much more informed decision than, for example, simply examining the marbling of flesh. Grocery stores would use the same data, of course, but could also layer in information about customer reviews of the butcher, or their latest health score. Customers could access this information to help them hone in on the cut of meat perfect for their upcoming meal. Or to make decisions that align with their ethical choices.

Big data is the future

We talk a lot about corporations becoming more efficient, driving more revenue, or even making happier customers thanks to big data. But we don’t often talk about the personal impact of the technology. We’ll all be seeing – and feeling – more of that in the years to come. We’ll keep an eye out in 2015 for both types of stories – we hope you’ll keep coming back to enjoy them with us.

Whiteboarded: How Red Hat delivers on Big Data

In the below explainer video, Red Hat’s Irshad Raihan explains how Red Hat can connect businesses to big data and help drive results. Check it out below but, if you want a taste of what to expect, read on!

Trends and buckets

Irshad points out three key trends he’s seeing in enterprise IT: Big data, cloud, and open source. These trends are technologies that Red Hat offers leading tools for.

Irshad goes on to explain that big data comes in two buckets; infrastructure, which must be reliable, secure, and scalable to support big data workloads; and a data & analytics layer, which is where data is ingested, enriched, and processed.

Needs

There are two types of users who will be involved on the front-lines in the implementation of enterprise IT projects. Red Hat has them covered.

Developers want to rapidly develop apps. To help them, Red Hat offers tools such as JBoss, Datagrid, BRMS (business rules management system) and Openshift, a platform as a service platform.

Data center managers already know Red Hat Enterprise Linux by now, but Red Hat also offers Red Hat Storage, a software defined storage tool, and Openstack, an infrastructure as a service platform.

These are all tools that span physical, virtual, and cloud deployments.

The bottom line

For CIOs, these tools from Red Hat can mean lower costs, reduced lock-in, and eliminated silos. You can learn about all this and more by checking out the video, below!

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