Industry’s first reference architecture for Hadoop with advanced access control and encryption with IDH, first flash-enhanced reference architecture for Hadoop demonstrated using YCSB with MapR, industry’s first validated and certified solution for real-time Big Data analytics with SAP HANA, and Unleashing IT big data special edition
Built up on our vision of shared infrastructure and unified management for enterprise applications, the Cisco UCS Common Platform Architecture (CPA) for Big Data has become a popular choice for enterprise Big Data deployments. It has been widely adopted in finance, healthcare, service provider, entertainment, insurance, and public sectors. The new Cisco UCS CPA V2 improves both performance and capacity featuring Intel Xeon E5-2600 v2 family of processors, industry leading storage density, and industry’s first transparent cache acceleration for Big Data.
The Cisco UCS CPA v2 offers a choice of infrastructure options, including “Performance Optimized”, “Balanced”, “Capacity Optimized”, and “Capacity Optimized with Flash” to support a range of workload needs.
Up to 160 servers (3200 cores, 7.6PB storage) are supported in single switching/UCS domain. Scaling beyond 160 servers can be implemented by interconnecting multiple UCS domains using Nexus 6000/7000 Series switches, scalable to thousands of servers and to hundreds of petabytes storage, and managed from a single pane using UCS Central in a data center or distributed globally.
The Cisco UCS CPA v2 solutions are available through Cisco UCS Solution Accelerator Paks program designed for rapid deployments, tested and validated for performance, and optimized for cost of ownership: Performance Optimized half-rack (UCS-SL-CPA2-P) ideal for MPP databases and scale-out data analytics, Performance and Capacity Balanced rack (UCS-SL-CPA2-PC) ideal for high performance Hadooop and NoSQL deployments, Capacity Optimized rack (UCS-SL-CPA2-C) when capacity matters, and Capacity Optimized with Flash rack (UCS-SL-CPA2-CF) offers industry’s first transparent caching option for Hadoop and NoSQL. Start with any configuration and scale as your workload demands.
Cisco supports leading Hadoop and NoSQL distributions, including Cloudera, HortonWorks, Intel, MapR, Oracle, Pivotal and others. For more information visit Cisco Big Data Portal, and Big Data Design Zone that offers Cisco Validated Designs (CVD) -- pretested and validated architectures that accelerate the time to value for customers while reducing risks and deployment challenges.
Cisco UCS Common Platform Architecture Version 2 for Big Data
Cisco Launches the First Flash-Enhanced Solution for Hadoop
Simplifying the Deployment of Real-time Big Data Analytics — UCS + SAP HANA
Also see Maximizing Big Data Benefits with MapR and Informatica on Cisco UCS
Tags: Cisco UCS CPA, Cisco UCS Solution Accelerator Paks, Cloudera, Hortonworks, Intel Hadoop, MapR, Pivotal HD, SAP. HANA
Extending our vision of shared infrastructure and unified management for enterprise applications, we are announcing industry’s first validated and certified solution for real-time Big Data analytics with SAP HANA. Based on our joint work with Intel and SAP at the SAP Co-innovation Lab (COIL), the solution integrates SAP HANA with Intel Distribution for Apache Hadoop running on Cisco UCS Common Platform Architecture (CPA) for Big Data, enabling real-time analysis of Big Data, while radically simplifying the infrastructure and management.
Solution Brief: Simplifying the Deployment of Real-time Big Data Analytics -- UCS + SAP HANA
Blog: Building on Success: Cisco and Intel Expand Partnership to Big Data
White Paper: Cisco UCS with the Intel Distribution for Apache Hadoop Software
Tags: Cisco UCS CPA, HANA, intel-distribution-for-apache-hadoop
While there is not yet an industry standard benchmark for measuring the performance of Hadoop systems (yes, there is work in progress -- WBDB, BigDataTop100 etc), workloads like TeraSort have become a popular choice to benchmark and stress test Hadoop clusters.
TeraSort is very simple, consists of three map/reduce programs (i) TeraGen -- generates the dataset (ii) TeraSort -- samples and sort the dataset (iii) TeraValidate -- validates the output. With multiple vendors now publishing TeraSort results, organizations can make reasonable performance comparisons while evaluating Hadoop clusters.
We conducted a series of TeraSort tests on our popular Cisco UCS Common Platform Architecture (CPA) for Big Data rack with 16 Cisco UCS C240 M3 Rack Servers equipped with two Intel Xeon E5-2665 processors, running Apache Hadoop distribution, see figure below, demonstrating industry leading performance and scalability over a range of data set sizes from 100GB to 50TB. For example, out of the box, our 10TB result is 40 percent faster than HP’s published result on 18 HP ProLiant DL380 Servers equipped with two Intel Xeon E5-2667 processors.
While Hadoop offers many advantages for organizations, the Cisco story isn’t complete without including collaborations with our ecosystem partners that enables us to offer complete solution stacks. We support leading Hadoop distributions including Cloudera, HortonWorks, Intel, MapR, and Pivotal on our Cisco UCS Common Platform Architecture (CPA) for Big Data. We just announced our Big Data Design Zone that offers Cisco Validated Designs (CVD) -- pretested and validated architectures that accelerate the time to value for customers while reducing risks and deployment challenges.
Cisco Big Data Design Zone
Cisco UCS Demonstrates Leading TeraSort Benchmark Performance
Cisco UCS Common Platform Architecture (CPA) for Big Data
Tags: Big Data, Big Data Benchmarks, Cisco UCS C240 M3 Rack Server, Cisco UCS CPA, CPA, Hadoop, TeraSort, YCSB
Cisco UCS Common Platform Architecture (CPA) for Big Data offers a comprehensive stack for enterprise Hadoop deployments. Today we announce the availability of Cisco Validated Design (CVD) for Cloudera (CDH) that describes the architecture and deployment procedures, jointly tested and certified by Cisco and Cloudera to accelerate deployments while reducing the risks, complexity, and total cost of ownership.
Together, Cisco and Cloudera are well positioned to help organizations exploit the valuable business insights found in all their data, regardless of whether it’s structured, semi structured or unstructured. The solution offers industry-leading performance, scalability and advanced management capabilities to address the business needs of our customers.
The rack level configuration detailed in the document can be extended to multiple rack scale. Up to 160 servers (10 racks) can be supported with no additional switching in a single UCS domain. Scaling beyond 10 racks can be implemented by interconnecting multiple UCS domains using Nexus 6000/7000 Series switches, scalable to thousands of servers and to hundreds of petabytes storage, and managed from a single pane using UCS Central.
We would like to invite you to our upcoming Journey to Big Data Roadshow in a city near you, designed to help you identify where you are on your Big Data journey, and how to keep that journey going in a low-risk, productive way.
1. Cisco UCS CPA for Big Data with Cloudera
2. Flexpod Select for Hadoop with Cloudera
3. Cloudera Enterprise with Cisco Unified Computing System (solution brief)
Tags: Cisco UCS CPA, Cloudera, CPA, Hadoop, Journey to Big Data
Cisco and NetApp have been partners for over a decade, and in January we announced the planned expansion of our partnership. We are always looking to work with our partners in new ways to offer customers greater choice, and Cisco and NetApp are working toward delivering a complete platform for enterprises in data-intensive industries with business-critical SLAs. The solution will offer pre-sized storage, networking, and compute in a highly reliable, ready-to-deploy Hadoop stack, and it is planned to be generally available summer 2013. But, who can wait until summer?! I know we can’t, so we’re going to offer a demo of the joint reference architecture at Cisco Live! Melbourne March 5-8, and we hope you’ll stop by to check it out!
To give you more information on the solution — it will be pre-validated for enterprise Hadoop deployments built using 6296 Fabric Interconnects (connectivity and management), a pair of Nexus 2232s, C220 M3 Servers (compute) and NetApp E5400 and FAS 2240 series storage arrays. Following the -- highly successful -- FlexPod model of pre-sized rack level configurations, this solution will be made available through the well-established FlexPod sales engagement and channel. Field sales and partners from both companies will resell the solution upon general availability.
Tags: Big Data, Cisco UCS CPA, CPA, Hadoop, netapp