Cisco Unified Computing System™ is unique among vendors with its comprehensive set of solutions for SAP and SAP HANA workloads—solutions that include servers with two to eight processors. Cisco Cisco UCS® C220 M4 Rack Server delivered 16,025 users and a SAPS score of 87,680: the best two-processor, two-tier result running Microsoft Windows 2012 Datacenter Edition.
Some of the key highlights of this result are:
- Best Two-Socket Server SAP SD Benchmark Result: The Cisco UCS C240 M4 running Microsoft Windows Server 2012 delivered the best two-tier SAP SD Benchmark result with SAP Enhancement Package 5 for SAP ERP 6.0 and Microsoft SQL Server 2012. The solution supported 16,025 SAP SD Benchmark users while maintaining a consistent application response time of less than one second
- Scale to meet demand: Cisco UCS C240 M4 Rack Server configured with the Intel Xeon processor E5-2600 v3 family can support up to 16,025 concurrent SAP SD Benchmark users in a Microsoft Windows Server 2012 and Microsoft SQL Server 2012 environment.
- Optimize application throughput: High-performance rack servers, blade servers, and network fabrics enable Cisco UCS to handle many SAP application tasks, with results showing that the system can process 1,753,670 order line items per hour or 5,261,000 dialog steps per hour.
- Cisco Consistently Improves Two-Processor, Two- Tier SAP SD Benchmark Performance: As illustrated in the graph below, these results show almost a 60 percent improvement over performance delivered by the last generation of Intel Xeon processor E5 product family CPUs.
The SAP SD Benchmark is designed to stress the computing infrastructure and determine whether a consistent response can be delivered as more users consume system resources. Cisco tested a Cisco UCS C240 M4 server equipped with two 2.30-GHz, 18-core Intel Xeon processor E5-2699 v3 CPUs, 256 GB of main memory, and a Cisco UCS Virtual Interface Card (VIC) 1225. The server ran both the SAP software and the 64-bit Microsoft SQL Server 2012 Enterprise Edition in a bare-metal configuration. Check out the Performance Brief and the detailed official benchmark disclosure report for additional information on the benchmark configuration.
Let’s see, what does this latest result mean for our customers?
- This result proves that Cisco UCS servers make an excellent foundation for any standards-based infrastructure solution.
- Cisco UCS dramatically reduces the number of physical components needed to support demanding SAP landscape applications, enabling IT departments to make effective use of limited space, power, and cooling resources.
- By deploying SAP on Cisco UCS, IT departments can support more users and accelerate response times. Many users can be supported—up to 16,025 in the benchmark configuration—with little hardware
- IT departments can choose from a broad range of Cisco UCS blade and rack server models to scale deployments further by using larger servers or by adding servers to create scale-out deployments with small footprints.
It is interesting to note that although all vendors have access to same Intel processors, only Cisco UCS unleashes their power to deliver high performance to applications through the power of unification. The unique, fabric-centric architecture of Cisco UCS integrates the Intel Xeon processors into a system with a better balance of resources that brings processor power to life. For additional information on Cisco UCS and Cisco UCS Integrated Infrastructure solutions please visit Cisco Unified Computing & Servers web page.
The statement of comparison is based on highest-performing system using two Intel Xeon processors and running SAP Enhancement Package 5 for SAP ERP 6.0 on Microsoft Windows Server 2012 Datacenter Edition in a two-tier configuration. Results referenced are available from the SAP website at: http://global.sap.com/solutions/benchmark/sd2tier.epx and are current as of December 1, 2014.
Tags: application performance, Application Scalability, Application throughput Optimization, Cisco UCS, Cisco UCS Performance, Cisco UCS Performance Leadership, SAP SD Benchmark, SAP. HANA
Want to get the most out of your big data? Build an enterprise data hub (EDH).
Big data is rapidly getting bigger. That in itself isn’t a problem. The issue is what Gartner analyst Doug Laney describes as the three Vs of Big Data: volume, velocity, and variety.
Volume refers to the ever-growing amount of data being collected. Velocity is the speed at which the data is being produced and moved through the enterprise information systems. Variety refers to the fact that we’re gathering information from multiple data sources such as sensors, enterprise resource planning (ERP) systems, e-commerce transactions, log files, supply chain info, social media feeds, and the list goes on.
Data warehouses weren’t made to handle this fast-flowing stream of wildly dissimilar data. Using them for this purpose has led to resource-draining, sluggish response times as workers attempt to perform numerous extract, load, and transform (ELT) functions to make stored data accessible and usable for the task at hand.
Constructing Your Hub
An EDH addresses this problem. It serves as a central platform that enables organizations to collect structured, unstructured, and semi-structured data from slews of sources, process it quickly, and make it available throughout the enterprise.
Building an EDH begins with selecting the right technology in three key areas: infrastructure, a foundational system to drive EDH applications, and the data integration platform. Obviously, you want to choose solutions that fit your needs today and allow for future growth. You’ll also want to ensure they are tested and validated to work well together and with your existing technology ecosystem. In this post, we’ll focus on selecting the right hardware.
The Infrastructure Component
Big data deployments must be able to handle continued growth, from both a data and user load perspective. Therefore, the underlying hardware must be architected to run efficiently as a scalable cluster. Important features such as the integration of compute and network, unified management, and fast provisioning all contribute to an elastic, cloud-like infrastructure that’s required for big data workloads. No longer is it satisfactory to stand up independent new applications that result in new silos. Instead, you should plan for a common and consistent architecture to meet all of your workload requirements.
Big data workloads represent a relatively new model for most data centers, but that doesn’t mean best practices must change. Handling a big data workload should be viewed from the same lens as deployments of traditional enterprise applications. As always, you want to standardize on reference architectures, optimize your spending, provision new servers quickly and consistently, and meet the performance requirements of your end users.
Cisco Unified Computing System to Run Your EDH
The Cisco Unified Computing System™ (Cisco UCS®) Integrated Infrastructure for Big Data delivers a highly scalable platform that is proven for enterprise applications like Oracle, SAP, and Microsoft. It also provides the same required enterprise-class capabilities--performance, advanced monitoring, simplification of management, QoS guarantees--to big data workloads. With lower switch and cabling infrastructure costs, lower power consumption, and lower cooling requirements, you can realize a 30 percent reduction in total cost of ownership. In addition, with its service profiles, you get fast and consistent time-to-value by leveraging provisioning templates to instantly set up a new cluster or add many new nodes to an existing cluster.
And when deploying an EDH, the MapR Distribution including Apache™ Hadoop® is especially well-suited to take advantage of the compute and I/O bandwidth of Cisco UCS. Cisco and MapR have been working together for the past 2 years and have developed Cisco-validated design guides to provide customers the most value for their IT expenditures.
Cisco UCS for Big Data comes in optimized power/performance-based configurations, all of which are tested with the leading big data software distributions. You can customize these configurations further, or use the system as is. Utilizing one of Cisco UCS for Big Data’s pre-configured options goes a long way to ensuring a stress-free deployment. All Cisco UCS solutions also provide a single point of control for managing all computing, networking, and storage resources, for any fine tuning you may do before deployment or as your hub evolves in the future.
I encourage you to check out the latest Gartner video to hear Satinder Sethi, our VP of Data Center Solutions Engineering and UCS Product Management, share his perspective on how powering your infrastructure is an important component of building an enterprise data hub.
In addition, you can read the MapR Blog, Building an Enterprise Data Hub, Choosing the Foundational Software.
Let me know if you have any comments or questions, or via twitter at @CicconeScott.
Tags: Big Data, blade server, blades servers, C240 M3 Rack Server, Cisco UCS, Cisco Unified Computing System, Cisco Unified Data Center, Cisco Unified Fabric, Enterprise Data Hub, Gartner, Hadoop, MapR, rack server, UCS Central, UCS service profiles
Have a bit of free time this Wednesday morning? If so please feel free to sit in on a Cisco keynote delivered by Mark Balch, Director of Cisco UCS Product Management, as he outlines the challenges faced and the discoveries made with the UCS family and how it has driven revolutionary change and business benefits for today’s modern datacenter.
The Cisco keynote starts WindowsITPro’s “virtual trade show” on Optimizing Your Virtual Infrastructure”. The event brings top industry Microsoft experts together in an online forum affording attendees the opportunity to learn about key datacenter optimization topics and trends.
Our UCS family has been a leader in Data Center optimization since it’s initial release to market five years ago. Having been designed for virtualization from the beginning, UCS is an integrated system that is configured through unified, model-based management to simplify deployment of enterprise-class applications and services running in bare-metal, virtualized, and cloud-computing environments.
Download the UCS Family poster
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Tags: ACI, Cisco, Cisco Data Center, Cisco UCS, datacenter, Hardware Optimization, Microsoft, network optimization, nexus
My final observation from my days at the London Gartner Data Center Conference is related to SDN and ease of network management – or otherwise. Hopefully this discussion will give you some ideas for good questions to ask at the Las Vegas conference, which is running as I write this.
Cisco UCS on show at the Gartner Data Center Conference
Before I start, if you are at the conference in Las Vegas, please do take time out to visit the Cisco stand #305 to find out more onCisco solutions including Unified Computing and ACI. Also take some time to say hello to our with new, exciting team members from our Metacloud acquisition – it’s fantastic to have such OpenStack and DevOps expertise in particular part of the Cisco team.
To catch up on my earlier questions, see my part 1 and part 2 blogs – questions you can ask at any SDN conference or of any vendor, since this blog series is not just about the Gartner conference. Now on to more SDN questions to ask ….
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Tags: ACI, API, Cisco UCS, cisco_services, network_management, nms, SDN
The Internet of Everything continues to gain momentum and every new connection is creating new data. Cisco UCS Integrated Infrastructure for Big Data is helping customers convert that data into powerful intelligence, and we’re working with a number of new partners to bring exciting new solutions to our customers.
Today, I want to spotlight Elasticsearch, Inc. and welcome them to the Cisco Solution Partner Program.
Elasticsearch excels at providing real-time insight into data – whether structured or unstructured, human- or machine-generated; by bringing a search-based architecture to data analytics. By combining the ELK stack with Cisco UCS, organizations benefit from a turnkey underlying infrastructure solution that provides them with real-time search and analytics for a variety of applications, from log analysis, to structured, semi-structured, or unstructured searches, as well as a web-backend for custom applications that use search-based analytics as a core functionality.
Mozilla is just one of the companies who are already benefiting from the joint solution with real-time search and analysis of data powering its defense platform, MozDef. The ELK stack leverages Cisco UCS’ fast connectivity for query, indexing and replication of data traffic. And Elasticsearch handles the full scale of event storage, archiving, indexing and searching of the data logs. The ELK stack and Cisco UCS also protect Mozilla’s network, services, systems, and audit data from hackers.
Partners like Elasticsearch are just one reason that Cisco UCS Integrated Infrastructure can help your company capitalize on the IoE data avalanche and deliver powerful and cost-effective analytics solutions throughout your enterprise.
Find out more at www.cisco.com/go/bigdata, or register for a webinar entitled, “Learn How Mozilla Tackles their Security Logs with Elasticsearch and Cisco”.
Thursday, November 13th
9:00 AM PST / 12:00 PM EST / 5:00 PM GMT
Are you interested in learning how to build enterprise applications on top of Elasticsearch and Cisco’s Unified Computing System (UCS) infrastructure? We’re holding a webinar to delve more deeply into how to optimize ELK on Cisco UCS infrastructure.
Cisco UCS unites compute, network, and storage access into a single cohesive system. By combining the ELK stack with Cisco UCS, businesses benefit by having a turnkey hardware-software solution for their search and analytics applications. In this webinar you’ll learn about the various UCS hardware profiles you should consider when deploying ELK and how Mozilla built MozDef, their custom SIEM application, using ELK on Cisco UCS.
- Introduction – Jobi George, Elasticsearch (5 minutes)
- Overview of UCS + ELK reference architectures – Raghunath Nambiar, Distinguished Engineer, Data Center Business Group, Cisco (10 minutes)
- How Mozilla Built MozDef on ELK and Cisco UCS – Jeff Bryner, Security Assurance, Mozilla (25 minutes)
- Q&A – Jobi George, Elasticsearch (~20 minutes)
Tags: analytics, Big Data, Cisco, Cisco UCS, Cisco Unified Computing System, elasticsearch, UCS