Cisco Blogs


Cisco Blog > Data Center and Cloud

What it Takes to Build a Platform Robust Enough for Your Big Data with UCS CPA.

Everybody has been talking about big data over the past years . Your data continues to grow, both in mass and importance. And you know that your company is in need of better analytics to use the influx of data as a point of improvement for business. As the Internet expands and connects all things previously unconnected (a concept referred to as the Internet of Everything, or IoE), consumers have access to more personalized information that keeps them engaged and delivers efficient services. This means data is pouring in from—well, everywhere. To sort and utilize it for better user experiences, it’s first necessary to ensure your data center is capable of gathering and housing all this data. And that starts at the foundation.

raghunathnambiarOur distinguished engineer and Chief Architect of Big Data Solutions at Cisco, Raghunath Nambiar, talks about “A Unified Platform for Big Data” in our last edition of Unleashing IT . Recently elected by the Transaction Processing Performance Council (TPC) to lead the development of the industry’s first big data benchmark standard, Nambiar states  “To get the most out of big data, companies need an infrastructure that is tuned for big data workloads, with better performance and scalability than traditional environments.” Read more here .

In fact, the Intel® Xeon® processor-based Cisco® Unified Computing System™ (Cisco UCS®) Common Platform Architecture (CPA) for Big Data is a robust platform built on a unified fabric, and based on Cisco Nexus® switches for exceptional availability and scalability. Built specifically with Big Data in mind, this certified and validated architecture has been utilized by businesses in a variety of industries.

Read More »

Tags: , , , , , ,

Announcing Cisco Solution for Cloudera Enterprise 5

Built upon our vision of shared infrastructure and unified management, the Cisco UCS Common Platform Architecture (CPA) for Big Data has become a leading platform for Big Data deployments. Today we are announcing support for Cloudera Enterprise 5 – an industry leading data management platform that combines Apache Hadoop with a number of other open source projects all integrated in to a single enterprise ready platform. The joint solution is tested and certified by Cisco and Cloudera to accelerate enterprise Hadoop deployments while significantly reducing the risks, complexity, and total cost of ownership.

With Hadoop at its core, Cloudera Enterprise enables an enterprise data hub by making it economically viable and technically feasible for enterprises to keep all their data in a single, centralized platform, from which they can store, process and analyze data in full fidelity, for a variety of enterprise workloads. Cloudera Enterprise 5 delivers tight integration with existing enterprise data management systems including key attributes to deliver robust security, governance, and data protection and management that enterprises require.

The Cisco and Cloudera joint solution is available in two reference architectures, Performance-Capacity Balanced and Capacity Capacity Optimized, both support up to 10 racks at 16 servers each without additional switches. The Performance-Capacity Balanced configuration provides an excellent balance of computing power and storage capacity supporting 32GBps of I/O bandwidth and 384TB storage per rack. The Capacity Optimized configuration provides a high storage density for storage-intensive deployments supporting 16GBps of I/O bandwidth and 768TB storage per rack for a total of 7.68PB when scaled to a 10 rack configuration.

Scaling beyond 10 racks (160 servers) can be implemented by interconnecting multiple UCS domains using Nexus 7000/9000 Series switches, scalable to thousands of servers and to hundreds of petabytes storage, and managed from a single pane using UCS Central in a datacenter or distributed globally.

The base rack configuration is available through Cisco UCS Solution Accelerator Paks for Big Data program, designed for: ease of ordering, rapid deployments, tested and validated for performance, and optimized for cost of ownership. Performance and Capacity Balanced rack SKU: UCS-SL-CPA2-PC and Capacity Optimized rack SKU: UCS-SL-CPA2-C.

Additional Information
Big Data Design Zone
Cisco Validated Design: Cisco UCS CPA for Big Data with Cloudera

Tags: , , , ,

Summary: One Second in Baseball Brought to You By The Cloud

The world of sports is being transformed by the acceleration of big data, cloud and Internet of Everything technologies. One sport where this transformation is evident is in Major League Baseball.

MLB fans are voracious consumers of baseball data, making it important for MLB to be alive and available 24/7, 365 days a year – not just on opening day.

As discussed in Rick Smolan’s The Human Face of Big Data, the amount of data being captured during one moment of a game today is greater than that from the entire season only a few years ago.

While the game has continued to evolve on the field thanks to the work of MLB Advanced Media (MLBAM) and technologies such as PITCH/fx, it has rapidly been changing off the field as well. For example, Cisco Connected Sports solutions are transforming the fan experience, whether they are watching the game live from the stands or on their mobile devices.

As the Internet of Everything (IoE) continues to connect more people, process, data, and things, the future of baseball is sure to generate more networked connections to reveal valuable insights. Imagine what the world of sports will be like when connected baseballs can report back whether a ball was fair or out!

By adding network intelligence, convergence, orchestration, and analytics with a secure connection between devices – and connected athletes – the Internet of Everything promises to deliver powerful insights about athlete performance. An essential part of delivering these insights is through the cloud.

For a closer look at how big data, cloud and the Internet of Everything will enhance America’s favorite game, read the full blog: One Second in Baseball Brought to You By the Cloud.     

One Second in Baseball Brought to You By The Cloud

Tags: , , , , , , , , , , , , , ,

One Second in Baseball Brought To You By The Cloud

Major League Baseball fans are voracious consumers of baseball data. It’s important for MLB to be live and available 24/7, 365 days a year – not just on opening day.

And because fans have been obsessed with statistics for as long as the sport has existed, it’s no surprise that the intersection of Big Data, mobility and cloud has begun to transform every aspect of the sport.

As discussed in Rick Smolan’s The Human Face of Big Data, the amount of data being captured during one moment of a game today is greater than that from the entire season only a few years ago.

Thanks to the work of MLB Advanced Media (MLBAM) and technologies such as PITCH/fx, gigabytes of data that capture each moment of every game in stadiums around the country are being shared with broadcasters, stadium operators and viewers at home, all in real-time through the cloud. While the game has continued to evolve on the field, it has rapidly been changing off the field. Ballparks around the country have been installing Cisco Connected Sports solutions , which impact everything from safety and security to live video on mobile devices. Beyond baseball, Cisco has been transforming the fan experience in more than 200 venues in more than 30 countries.

One Second in Baseball Brought To You By The Cloud

As the Internet of Everything (IoE) connects more people, process, data, and things, the future of baseball is sure to generate more networked connections to reveal valuable insights. The possibilities for connections are limitless:  connected fields, baseballs, bats, player uniforms, and more will not only generate more data but also provide more possibilities for analysis. Imagine what the world of sports will be like when connected baseballs can report back whether a ball was fair or foul!

Here’s a closer look at how Big Data, cloud and the Internet of Everything will enhance America’s favorite game.

Read More »

Tags: , , , , , , , , , , , , , ,

Maximizing Big Data Performance and Scalability with MapR and Cisco UCS

Huge amounts of information are flooding companies every second, which has led to an increased focus on big data and the ability to capture and analyze this sea of information. Enterprises are turning to big data and Apache Hadoop in order to improve business performance and provide a competitive advantage. But to unlock business value from data quickly, easily and cost-effectively, organizations need to find and deploy a truly reliable Hadoop infrastructure that can perform, scale, and be used safely for mission-critical applications.

As more and more Hadoop projects are being deployed to provide actionable results in real-time or near real-time, low latency has become a key factor that influences a company’s Hadoop distribution choice. Thus, performance and scalability should be evaluated closely before choosing a particular Hadoop solution.

Performance

The raw performance of a Hadoop platform is critical; it refers to how quickly the platform can ingest, process and analyze information. The MapR Distribution for Hadoop in particular provides world-record performance for MapReduce operations on Hadoop. Its advanced architecture harnesses distributed metadata with an optimized shuffle process, delivering consistent high performance.

The graph below compares the MapR M7 Edition with another Hadoop distribution, and it vividly illustrates the vast difference in latency and performance between these Hadoop distributions.

High Performance with Low Latency

 

One particular solution that is optimized for performance is Cisco UCS with MapR. MapR on the Cisco Unified Computing System™ (Cisco UCS®) is a powerful, production-ready Hadoop solution that increases business and IT agility, supports mission-critical workloads, reduces total cost of ownership (TCO), and delivers exceptional return on investment (ROI) at scale.

Read More »

Tags: , , , , , , , , , , , ,