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IBM Power Systems La nueva generación de sistemas diseñados para el dato y optimizados para Cloud Juan Manuel Alcudia jmalcudia@es.ibm.com.

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Presentation on theme: "IBM Power Systems La nueva generación de sistemas diseñados para el dato y optimizados para Cloud Juan Manuel Alcudia jmalcudia@es.ibm.com."— Presentation transcript:

1 IBM Power Systems La nueva generación de sistemas diseñados para el dato y optimizados para Cloud Juan Manuel Alcudia

2 Power Systems with POWER8 are built with open innovation to put data to work across the enterprise
Designed for big data First server processor generation optimized for big data & analytics with POWER8 innovative design Open innovation platform Delivering the world’s first open server ecosystem revolutionizing the way IT is developed & delivered Superior cloud economics Superior cloud price/performance advantages & security to move data-centric applications to the cloud Power Systems are enhanced with new capabilities so clients are better equipped for Cloud, Analytics & Mobile workloads as well as handling complex, mission critical applications with confidence. 2 2

3 Our Journey and Commitment to Power Systems
May September February April August October Watson Engagement Advisor 5 Power Systems Linux Centers around the world Power development cloud OpenPOWER Foundation open for business IBM Innovation Centers fuel Linux on Power Enterprise systems 2013 2014 August September April April August Key Message: Shifts in the marketplace resulted in a change to our strategy. We’ve been on a journey to reposition Power Systems and have been changing the perceptions of Power.  As part of that, we’ve been making investments during the last 12 months. • We’ve made a number of strategic investments and clients have responded favorably. We continue to be the ideal platform for IBM Watson; we’ve helped form the OpenPOWER Foundation and are helping to guide its rapid expansion; we announced a new set of scale-out Power Systems; and we are growing our presence in cloud in a big way – with a focus on hybrid. Clients have been waiting for an alternative to x86, and this is what we’re delivering with the new scale-out systems Scale-up Systems are coming soon. Inspur to develop system solutions using OpenPOWER innovations OpenPOWER Foundation announced $1 billion Linux on Power investment POWER8: 3+ years, $2.5 billion R&D investment with hundreds of patents Ubuntu supports IBM Power Systems for simpler Linux migration

4 Power Systems with POWER8 are built with open innovation to put data to work across the enterprise
Designed for big data New solutions for Hadoop, NoSQL and Elastic Storage Enhanced Scale-Out Systems with up to 2 TB / system New POWER8 Scalable enterprise systems Open innovation platform First solution from OpenPower – S824L with NVIDIA GPU Expanded Linux Support – IFLs and new Distributions Superior cloud economics Simplified Hybrid Cloud Management built on OpenStack Enhanced virtualization management for PowerVM and PowerKVM Power Enterprise Pools for private clouds and easier migration / integration with POWER8

5 Clients are rapidly expanding their data and analytics focus to enhance business opportunities
Map Reduce Implementations Relational Databases NoSQL Databases Instant insight from real-time operational data Simplified transactions and reporting Reduced tuning and indexing Analytics capability for multiple data types, often used in mobile and social workloads Scalability and flexibility for different data store models A scalable data architecture A parallel and distributed  programming model Open source community innovation (Apache Hadoop) Systems built with POWER8 deliver 2:1 Core Performance, Memory Bandwidth & Memory Capacity DB2 BLU Oracle in-memory SAP HANA Reduced complexity, space (>12x) and cost with CAPI attached Flash Redis, Cloudant, Mongo DB, Cassandra 4x Lower Storage requirements High performance, data centric design with GPFS & Compression NoSQL: Column or Distributed Data Store: Tuple of column name, value, timestamp Document: Designed for storing, retrieving and managing document-oriented information Key-value or Associative Array: Collection of (unique) key, value pairs Graph: Structure with nodes, edges and properties to represent and store data

6 IBM Data Engine for Analytics
IBM IOD 2011 10/13/2017 5:09 AM 10/13/2017 IBM Data Engine for Analytics A Customized Infrastructure Solution with Integrated Software Rapid Deployment Flexibility Efficiency Actionable Insights: preloaded Big Insights plus other analytic applications Grid infrastructure Services (Platform computing) POWER8 Systems: 2X Performance Optional Compression and Encryption High Performance, Scalable Networking IBM Elastic Storage Server 1 copy of data versus 3 Scalable file system Big Data & Analytics Software Infrastructure Services POWER8 Servers GZIP Compression Scalable Networking Scale Out Cluster File System Elastic Storage Server Elastic Storage Server 6

7 IBM IOD 2011 10/13/2017 10/13/2017 5:09 AM IBM Data Engine for NoSQL Reduce complexity and cost of NoSQL solutions Power CAPI-attached Flash model for NoSQL regains infrastructure control and reigns in the cost to deliver services. Today’s NoSQL in memory (x86) Differentiated NoSQL (POWER8 + CAPI Flash) WWW WWW 10Gb Uplink Load Balancer 10Gb Uplink POWER8 Server 500GB Cache Node 500GB Cache Node 500GB Cache Node Flash Array w/ up to 40TB 500GB Cache Node 500GB Cache Node “Today we are going to show you a revolutionary technology that we think is going to change the way services are consumed on the cloud.” “We all know the prevalence of NoSQLs and there seems to be flavors for every task at hand. For example, if you need large massive data storage there is hadoop. If you need lightning quick response time there is in memory redis. However, there deosn’t seem to be a way to combine the lightning quickness with massive capacity. Well, today we have a technology in out POWER 8 Systems that introduces a new tier of memory. This new tier lets our POWER 8 System perform like they are stacked with TBs of memory.” Infrastructure Attributes 192 threads in 4U Server drawer 40 TB of memory based Flash per 4U Drawer Shared Memory & Cache for dynamic tuning Elimination of I/O and Network Overhead Cluster solution in a box Infrastructure Requirements Large Distributed (Scale out) Large Memory per node Networking Bandwidth Needs Load Balancing Backup Nodes 7

8 4Q ANNOUNCE: CAPI “Developer Kit” for early adopters
An invitation to innovate Introducing the CAPI Developer Kit CAPI card and Support documentation will be made available for early adopters who wish to innovate custom logic / accelerator logic on an FPGA attached via CAPI This will be an offering from OpenPOWER member Nallatech FPGA IBM Supplied POWER Service Layer AFU Open space for Customization and innovation Can be plugged into an Existing Capi enabled Tuleta system

9 Scale-out Systems built with POWER8
Portfolio is complemented by a full commitment to support an open stack of software Ubuntu, SUSE, RedHat, PowerKVM, and Open Stack New Capabilities (4Q2014) 2 TB memory option in S824 Linux SUSE SLES12 (LE) enabling easier application portability S824L w/ NVidia GPU acceleration Mixed Endian VM support of a single PowerKVM host NEBS option for Telco S812L S822L S822 S814 S824L S824 1-socket, 2U Linux only 2-socket, 2U Up to 24 cores 1 TB memory 9 PCI Gen3 slot PowerVM & PowerKVM NEBs option Up to 20 cores 9 PCIe Gen 3 AIX & Linux PowerVM 1-socket, 4U Up to 8 cores 512 GB memory 7 PCIe Gen 3 AIX, IBM i, Linux 4 core/P05 for IBM i 2-socket, 4U Linux NVidia GPU Annc/GA in 4Q14 11 PCIe Gen 3 2 TB memory option

10 IBM and NVIDIA deliver new acceleration capabilities for analytics, big data, and Java
Runs pattern extraction analytic workloads 8x faster Provides new acceleration capability for analytics, big data, Java, and other technical computing workloads Delivers faster results and lower energy costs by accelerating processor intensive applications Power System S824L Up to 24 POWER8 cores Up to 1 TB of memory Up to 2 NVIDIA K40 GPU Accelerators Ubuntu Linux running bare metal

11 The OpenPOWER Foundation creates a pipeline of continued innovation and extends POWER8 capabilities
Opening the architecture and innovating across the full hardware & software stack Driving an expansion of enterprise-class hardware and software Building a complete sever ecosystem delivering maximum client flexibility Launched last year ... The OpenPOWER Foundation is an open development community collaborating together to leverage POWER's open architecture for broad industry innovation. There are currently 57 members with membership continuing to grow globally with latest additions from Australia, Europe, India, Brazil and a continued strong interest from China with 11 members.

12 Focus on ecosystem presence
RIVALRY Work with Universities Commercial Developers OpenPOWER & Open Source Initiatives Regional Ecosystem Expansion Growing POWER8 Ecosystem Double the number of Academic Initiative universities by 2015 (over 100 new schools in 2014) Drive University Challenge in fall semester 2014 OpenPOWER technology creates greater choice for customers Open and collaborative development model 60+ members & growing Over 800 Linux ISVs; ecosystem communities, 100K+ developers (i.e. Ubuntu, Zend, Opscode, etc) Partner with SWG to grow Linux capabilities for targeted workloads Build and promote ‘Virtual Appliance’ Reference configurations Create new GTM constructs for on-premise and cloud deployment -- Ecosystem has multiple elements: ISVs, middleware, universities, and there are key regional dynamics to consider -- OpenPOWER has created a rapidly expanding ecosystem, with partners at all levels in the stack -- Seeing strong growth in ecosystem around Power 12 © 2014 International Business Machines Corporation

13 New Enterprise POWER8-based Systems for the Most Demanding Data Environments
Tackle your largest workloads with massive performance and scalability (up to 192 cores and 1,024 threads; 16 TB; 1,000 VMs) Operate with more flexibility and efficiency Maximize availability and serviceability Instantly respond to the dynamic, changing needs of today’s business Deploy new workloads faster and at lower cost with Power IFLs and Usage / Utility based pricing for Elastic COD CLIENT VALUE Increased system scale Increased performance per-core Up to 20 VMs per-core Enterprise RAS Increased energy efficiency Elastic Capacity on Demand Share resources in Power Enterprise Pool * Initial GA supports 2 nodes, 64 cores, 8 TB with MES to 3 or 4 nodes in 2015

14 Designed for the most demand data workloads with the agility to handle today’s dynamic business environment Combining the architectural strengths of Power 795 with the modularity & efficiencies of Power 770/780 High performance compute nodes Fastest processor in the industry Up to 48-cores* and 4 TB per node Modular structure delivers efficiency and flexibility Flexible growth up to 4 compute nodes * Improved space and energy efficiency System design for High Availability and Serviceabilty Isolated, fully redundant System Control Unit Enhanced Serviceability Enhanced memory and system reliability Economic efficiency with Capacity on Demand flexibility and IFLs Elastic Capacity on Demand Mobile Capacity for Power Enterprise Pools Enhanced Serviceability: Slide rails and Blind Swap I/O adapters *All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. 14 14

15 POWER8 Enterprise Systems
192 cores* 1 – 4 node*, 4-16S* (12c) Up to 16 TB Memory Power E880 9119-MHE 128* 4.35 GHz 1 – 4 node*, 4-16S (8c) Up to 16 TB Memory GHz 1 – 2 node, 4 - 8S (10c) Up to 8TB* Memory Power E870 9119-MME 4 GHz 1 – 2 node, 8S (8c) Up to 8TB* Memory 1 E880 with 3 or 4 nodes, 96 or 128 cores, respectively, will GA in 2Q 2015. *Statement of Direction. All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

16 Accelerating Availability of POWER8 Enterprise Systems
192 cores* 1 – 4 node, 4-16S (12c)* Up to 16 TB Memory GA = 4Q14 Power E880 9119-MHE 128* 4.35 GHz 1 – 4 node*, 4-16S (8c) Up to 16 TB Memory 64-cores 8 TB GHz 1 – 2 node, 4 - 8S (10c) Up to 8TB* Memory Power E870 9119-MME 4 GHz 1 – 2 node, 4-8S (8c) Up to 8TB* Memory 1 E880 with 3 or 4 nodes, 96 or 128 cores, respectively, will GA in 2Q 2015. *Statement of Direction. All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

17 POWER8 Enterprise Systems
1H15 SOD : 192 cores* 1 – 4 node, 4-16S (12c)* Up to 16 TB Memory Power E880 9119-MHE GHz 1 – 4 node**, 4-16S (8c) Up to 16 TB** Memory 64-cores 8 TB Expand to 128 cores GHz 1 – 2 node, 4 - 8S (10c) Up to 8TB* Memory Power E870 9119-MME GHz 1 – 2 node, 4-8S (8c) Up to 8TB* Memory 1 E880 with 3 or 4 nodes, 96 or 128 cores, respectively, will GA in 2Q 2015. *Statement of Direction. All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

18 Power E870 & E880 servers Power E870 Power E880
Increased performance and scale Built-in PowerVM Enterprise Edition Enterprise RAS System Control Unit (2U) Built-in Active Memory Mirroring for Hypervisor More performance per-watt 8 PCIe adapter slots per node Up to 4 PCIe I/O drawers per Node* Share resources in Power Enterprise Pool Medium Software tier 24x7 Warranty 8 to GHz 8 to GHz 256 to 4TB Memory (8TB SOD*) 1 or 2 nodes (5U) per system 8 to GHz Up to 192 cores* in 2015 256 to 16TB Memory 1 to 4 nodes (5U) per system Built-in initial Elastic CoD days *Statement of Direction to support up to 8TB memory on E870 and up to 4 PCIe I/O Expansion Drawers per node on Power E870 & E880 in 2015. Initial GA in 4Q14 supports 4TB maximum on E870 and 0 or 2 PCIe I/O drawers per node on E870 & E880.

19 More Scalability than an other 8-socket systems
(best Intel Xeon and best Oracle SPARC) SAP SD Standard Application Benchmark Results, 2-Tier: SD Benchmark Users SAP enhancement package 5 for SAP ERP 6.0 Source: http// 1.6X more users than Ivybridge-EX v2 ~ 2X more users than Oracle T5-8 with 1/3 less cores! Fujitsu PQ 2800E Intel E v2, 120c/240t Oracle T5-8 T5 128c/1024t IBM x3950 X6 Intel E v2 IBM Power E870 POWER8 80c/640t 128c 120c 80c IBM Power System E870 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 80 cores / 640 threads, POWER8; 4.19GHz, 2048GB memory, 79,750 SD benchmark users, running AIX® 7.1 and DB2® 10.5, dialog response: 0.97 seconds, line items/hour:8,722,000, dialog steps/hour: 26,166,000 SAPS: 436,100 database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source: IBM System x3950 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and DB2® 10, dialog response: 0.85 seconds, line items/hour: 5,421,670, dialog steps/hour: 16,265,000 SAPS: 271,080; database response time (dialog/update): sec / sec, CPU utilization: 98%, Certification #:  Results valid as of 10/3/14.  Source: Fujitsu PRIMEQUEST 2800E on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and SQL Server 12, dialog response: 0.97 seconds, line items/hour: 5,193,670, dialog steps/hour: 15,581,000 SAPS: 259,680; database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source: (5) Oracle SPARC Server T5-8 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors/128 cores/1024 threads, SPARC T5; GHz, 2,048 GB memory; 40,000 SD benchmark users, running Solaris® 11 and Oracle 11g; Certification # Results valid as of 10/3/14. Source: SAP and all SAP logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries. All other product and service names mentioned are the trademarks of their respective IBM Power System E870 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 80 cores / 640 threads, POWER8; 4.19GHz, 2048GB memory, 79,750 SD benchmark users, running AIX® 7.1 and DB2® 10.5, dialog response: 0.97 seconds, line items/hour:8,722,000, dialog steps/hour: 26,166,000 SAPS: 436,100 database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source: IBM System x3950 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and DB2® 10, dialog response: 0.85 seconds, line items/hour: 5,421,670, dialog steps/hour: 16,265,000 SAPS: 271,080; database response time (dialog/update): sec / sec, CPU utilization: 98%, Certification #:  Results valid as of 10/3/14.  Source: Fujitsu PRIMEQUEST 2800E on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and SQL Server 12, dialog response: 0.97 seconds, line items/hour: 5,193,670, dialog steps/hour: 15,581,000 SAPS: 259,680; database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source: (5) Oracle SPARC Server T5-8 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors/128 cores/1024 threads, SPARC T5; GHz, 2,048 GB memory; 40,000 SD benchmark users, running Solaris® 11 and Oracle 11g; Certification # Results valid as of 10/3/14. Source: SAP and all SAP logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries. All other product and service names mentioned are the trademarks of their respective companies.

20 Superior cloud economics: simplified virtualization & cloud management

21 Superior Cloud economics: Simplified virtualization and hybrid cloud management
Cloud Manager with OpenStack Extended capability to enable customization & quicker deployment of OpenStack-based cloud solutions Management across heterogeneous systems, on premises and off premises Simplified virtual IO administration Risk reduction by using templates for repeatable deployment of workloads VM restart accelerates workload recovery Run any combination of Linux distros via Mixed Endian VM support on a single PowerKVM host Improve performance using PCI passthru for dedicated I/O Better availability through PCIe hot plug support Expanding device and OS support Import existing KVM VMs Simplified maintenance with one click system evacuation Increase scaling by 100% to 20 hosts; 2000 VMs *All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. 21

22 Clients are asking for:
IBM Delivers the most powerful foundation for private and public cloud infrastructure Clients are asking for: Extreme flexibility, instant response Higher Availability Economic Efficiency Investment Protection POWER7+ Designed to eliminate planned and unplanned downtime for the most demanding workloads Shift resources to support planned maintenance Active – Active for efficient HA / DR Seamless transition to new technology Easily manage the changing workload demands of today’s dynamic, real time business environment. Elastic Capacity on Demand Move virtual processor and memory resources to address new demands without physically reconfiguring the data center Leadership IT Efficiency Combining the economic efficiency of Elastic Cloud pricing with systems designed for 80-90% utilization Usage and utility based pricing Minimize excess capacity required to manage availability and contingency for dynamic business environments Ready for the Future Seamlessly integrate next generation technology in your Power Enterprise Pool Inactive resources are used for processor and memory sparing Inactive resources can be used for free trials of new applications Inactive resources can be used with temporary activations for emergency backup Power E880 Power 780 Power E880 22 22 22

23 Power Enterprise Pools: The most powerful foundation for a flexible, economically advantaged private and hybrid cloud IT infrastructure Extreme flexibility to instantly respond to changing business demands Simpler application workload balancing Easily manage periodic workload spikes and bursting High Availability Reduced planned downtime due to system maintenance Enhanced disaster recovery capabilities Economic Efficiency Operate at 80-90% utilization with flexible capacity Minimize excess capacity required to manage availability or contingency for workload uncertainties Usage and utility based pricing Investment Protection and simplified technology transition to POWER8 Upgrade / Share / Move POWER7+ resources & software to POWER8 Transition applications to POWER8 with increased business flexibility POWER7+ Mobile COD: move processor and memory resources amongst systems Elastic COD: for periodic spikes in workload demand OpenStack: for simplified Cloud and Virtualization Management Designed to eliminate planned and unplanned downtime for the most demanding workloads Shift resources to support planned maintenance Active – Active for efficient HA / DR Seamless transition to new technology Easily manage the changing workload demands of today’s dynamic, real time business environment. Elastic Capacity on Demand Move virtual processor and memory resources to address new demands without physically reconfiguring the data center Leadership IT Efficiency Combining the economic efficiency of Elastic Cloud pricing with systems designed for 80-90% utilization Usage and utility based pricing Minimize excess capacity required to manage availability and contingency for dynamic business environments Ready for the Future Seamlessly integrate next generation technology in your Power Enterprise Pool Inactive resources are used for processor and memory sparing Inactive resources can be used for free trials of new applications Inactive resources can be used with temporary activations for emergency backup *All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. 23 23 23

24 Deploy a Power Enterprise Pool today and your infrastructure is ready for the future
Today, Power Enterprise Pools provides Simpler application workload balancing Reduced planned downtime due to system maintenance Enhanced disaster recovery capabilities Flexible, efficient private cloud infrastructure POWER7+ and tomorrow with POWER8… Provides options for more granularity & flexibility when transitioning applications to POWER8 Tremendous asset/investment protection Future enhancements planned* to improve automation for high availability and disaster recovery environments with POWER8 *All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

25 Power Systems with POWER8 are built with open innovation to put data to work across the enterprise
Designed for big data New solutions for Hadoop and NoSQL databases and Elastic Storage to simplify operations and reduce cost New and enhanced Power Scale-Out Systems and solutions with up to 2 TB / system Scalable enterprise systems for the most demanding data environments with leadership performance and scale, up to 16 TB / system and over 80% utilization Open innovation platform First solution from the OpenPower Foundation – S824L with NVIDIA GPU for technical computing and high performance analytics Simplify operations and reduce costs by running new Linux workloads on POWER8- based IFLs New Linux distributions & turbo charge LAMP solution stacks Superior cloud economics Simplified Hybrid Cloud Management with Cloud Manager for OpenStack for a single point of control Enhanced virtualization management with expanded storage/networking and OS support and increased scalability Power Enterprise Pools enable enhanced business flexibility and availability with the ability to migrate POWER7 Mobile COD to POWER8 systems

26 Infrastructure Matters: Open Innovation with open innovation to put data to work across the enterprise Infrastructure Solutions & Expanding Ecosystem Infrastructure System Software Expanding choice, simplifying management, lowering costs Customized infrastructure solutions delivering new, unprecedented value IBM Data Engine for Analytics IBM Data Engine for NoSQL IBM S824L with Nvidia IBM BLU Acceleration for Power Systems Scale Out Systems Enterprise Systems & Pools Leadership performance and resiliency leveraging new, Open Innovation Designed for the most demanding data environments with agility and efficiency POWER7+ Power 780 Power E880 Midrange and Entry are one through four socket systems 26 26

27 Open innovation to put data to work
36 21 21 21

28 BIG DATA & ANALYTICS Because the speed of business is money
Héctor Colmenares, IBM SW Core Database Competitive Sales Leader, IM SPGI

29 Tendencias del mercado Demanda de respuestas en real time es una necesidad.
Vivimos en la generación del “NOW”. Los datos crecen constantemente, y los usuarios esperan respuestas más rápidas. Movilidad y el uso “democrático” de la información y la analítica hacen de la tecnologia in-memory y mensajería distribuida un requerimiento obligado. La velocidad cambia el negocio. Nuevas y modernas arquitecturas de datawarehouse dinámicas reemplazarán los modelos tradicionales de datos por la demanda de datos en real-time. La realidad es que vivimos en el mundo de la inmediates, el ahora ya es tarde, la movilidad, los sensores, adelantarnos, predecir es lo que marca la endencia pero en donod eencaja el bigdata? 29

30 Big Data y analítica del negocio La Revolución de los datos
2+ billion people on the Web by end 2011 30 billion RFID tags today (1.3B in 2005) 4.6 billion camera phones world wide 100s of millions of GPS enabled devices sold annually 76 million smart meters in 2009… 200M by 2014 De los datos mundiales NO ESTRUCTURADOS 80% 12+ TBs of tweet data every day IT Logs ? TBs of data every day Obviously, there are many other forms of data. Let’s start with the hottest topic associated with Big Data today: social networks. Twitter generates about 12 terabytes a day of tweet data – which is every single day. Now, keep in mind, these numbers are hard to keep accurate, so the point is that they’re big, right? So don’t fixate on the actual number because they change all the time and realize that even if these numbers are out of date by 2 years, it’s at a point where it’s too staggering to handle exclusively using traditional approaches. +CLICK+ Facebook over a year ago was generating 25 terabytes of log data every day (Facebook log data reference: ) and probably about 7 to 8 terabytes of data that goes up on the Internet. Google, who knows? Look at Google Plus, YouTube, Google Maps, and all that kind of stuff. So that’s the left hand of this chart – the social network layer. Now let’s get back to instrumentation: there are massive amounts of proliferated technologies that allow us to be more interconnected than in the history of the world – and it just isn’t P2P (people to people) interconnections, it’s M2M (machine to machine) as well. Again, with these numbers, who cares what the current number is, I try to keep them updated, but it’s the point that even if they are out of date, it’s almost unimaginable how large these numbers are. Over 4.6 billion camera phones that leverage built-in GPD to tag your location or your photos, purpose built GPS devices, smart metres. If you recall the bridge that collapsed in Minneapolis a number of years ago in the USA, it was rebuilt with smart sensors inside it that measure the contraction of the concrete based on weather conditions, ice build up, and so much more. So I didn’t realise how true it was when Sam P launched Smart Planet: I thought it was a marketing play. But truly the world is more instrumented, interconnected, and intelligent than it’s ever been before and this capability allows us to address new problems and gain new insight never before thought possible and that’s what the Big Data opportunity is going to be all about! 25+ TBs of log data every day 30

31 Big Data: todo son datos Paradigma para extraer valor
Transaccional & Datos Aplicativos Contenido Empresarial Dato Social Data Sensores Big data comes from many sources. Its much more than traditional data sources. And it order to capitalize on the breakthrough opportunities we’ve discussed, you definitely need to look beyond traditional data sources. But at the same time, don’t forget that big data comes from those traditional sources too. Transactional data and application data is growing an a significant rate. Although it’s structured, that data is large and it is contained in many different structures. Social data also needs to be incorporated. Most social data is really textual data. And the valuable insights remain locked within that text and its many possible meanings. And most of that data isn’t valuable, or has a very short expiry date during which it is valuable. That makes social data very challenging – extracting insight from largely textual content in very little time. And enterprise content must be amalgamated as well. And that data comes in many forms, and also in significant volume. Big data includes machine data – “the internet of things” – logs, web logs, instrumentation data, network data. Data generated by machines is multiplying quickly, and it contains valuable insights that need to be discovered. Volumen Estructurado Entrada / Salida Variedad No estructurado Veracidad Velocidad Ingestión

32 Big Data: todo son datos Gestión de los datos: No es única
Mobile Storefront Sales Analysis Real Time Fraud Detection Demand Analysis E-commerce These innovative solutions that we just talked about on the previous slide are comprised of different types of applications, each of which are best served by different types of data systems that are optimized specifically to each workload for speed, reliability and cost efficiency. At the top we have the types of innovative applications you are deploying or want to deploy and at the bottom is IBM’s DB with BLU Acceleration or Informix 12.1 capabilities that are optimized to handle them. JSON doc 2 Key 2 JSON doc 1 Key 1 Data series 2 Meter 2 Data series 1 Meter 1 Transactional Database JSON Database Analytics Data Warehouse Operational Data Warehouse Time Series Database Transaction Processing Mobile Data Serving Reporting and Analytics Operational Analytics Sensor Data Analysis

33 Analítica dá la clave para incrementar la competitividad
Compañías que realizan analíticas sofisticadas superan a su competencia 2.6x mas rendimiento que sus iguales del sector 1.6x Mas ingresos 260% estar entre los mejores del sector 2.5x Valorización del precio del stock From a survey of over 4,500 executives, managers and analysts, from more than 30 industries in 122 countries, some key statistics have been uncovered, relating to Big Data and Analytics. Businesses who use analytics, are 2.6 times more likely to outperform their competitors and achieve, on average, 1.6 times revenue growth, following implementation of an analytics solution. And become 206% more likely to be one of the top performers in their industry, leading to as much as 2.5 times stock price appreciation. Can any business afford to ignore these growth rates? In essence if they are not implementing best of breed analytics solutions, they are falling behind their competitors, and loosing relevance in their marketplace, as they likely react too slowly to changes in market trends. Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology Outperforming in a data-rich, hyper-connected world, IBM Center for Applied Insights study conducted in cooperation with the Economist Intelligence Unit and the IBM Institute of Business Value. 2012

34 Cuantificar valor de la analítica
Cierre Contable – Mejora del flujo de caja Speed equals 39% faster payment* Average closing of accounts Source: SAP value engineering study 2011 2012 2013 days to payment 59 36 reduced days to payment increased cash flow business growth So lets look at How an optimized analytics solution, makes a difference to the bottom line. And illustrate, how speed of business process, equals money. A study done by SAP, looked at how long companies take to complete their monthly financial close of their accounts Looking at the average of the worst performing customers, they take 22 days, to close their books. By contrast, the average of the best performing customers, they take just 7 days to close their books. <click> If we put that into business terms, here is an example of a report generated by XERO one of the fastest growing SaaS companies globally, specialising in Accounting software , they analysed 16 million invoices from thousands of businesses totalling £20 billion and reported that by increasing the speed of invoicing companies were seeing a 39% improvement in the number of days it was taking to get paid. Reducing the number of days to payment has increased their cashflow and has lead to business growth So here we truly see how speed of business process, is about money. Doing things better is important, understanding the business better is important, but doing those things faster, is delivering business growth by improving cash flow. *Based on analysis done by Xero, a SaaS company specialising in accounting software, Link to blog & infographic: HERE Speed of Business Process, Is Money

35 La lógica del Data Warehouse Contemplar componentes, propósitos, zonas
Vertical Industry Accelerators Advanced Application Capabilities Information Integration & Governance Data types Real-time processing & analytics Actionable insight Decision management Logical Data Warehouse Machine and sensor data Operational systems Exploration, landing and archive Deep analytics & modeling Image and video Predictive analytics and modeling Trusted data Enterprise content Reporting & interactive analysis Reporting, analysis, content analytics Transaction and application data Social data Discovery and exploration Third-party data

36 La lógica del Data Warehouse Ejemplo de la Solución de IBM
Vertical Industry Accelerators BigSQL and SQL based applications Advanced Application Capabilities Information Integration & Governance Data types Real-time processing & analytics Federation and In-memory federated cube Actionable insight Decision management Logical Data Warehouse Machine and sensor data Operational systems Exploration, landing and archive Deep analytics & modeling Image and video Predictive analytics and modeling Trusted data ORACLE Microsoft Teradata Enterprise content Reporting & interactive analysis Reporting, analysis, content analytics Transaction and application data Social data BigMatch Third-party data Discovery and exploration Streams

37 ¿Qué hace diferente BLU Acceleration
¿Qué hace diferente BLU Acceleration? Innovacionees de IBM Research & Developments Labs. Next Generation In-Memory In-memory columnar processing with dynamic movement of data from storage Analyze Compressed Data Patented compression technique that preserves order so data can be used without decompressing Encoded CPU Acceleration Multi-core and SIMD parallelism (Single Instruction Multiple Data) Data Skipping Skips unnecessary processing of irrelevant data Instructions Data Results BLU Acceleration is a game changing combination of innovations from IBM Research and Development Labs that dramatically simplifies and speeds the delivery of business insight from data. Easy to set up and self optimizing, BLU Acceleration eliminates the need for indexes, aggregates, or time consuming database tuning to achieve top performance and storage efficiency. With next generation In-memory capabilities, BLU Acceleration can deliver the performance of in-memory processing without the cost or limitations of in-memory only systems. BLU Acceleration does not require all data to fit in memory in order to achieve breakthrough performance. The system has the efficiency and intelligence of keeping the most relevant data in memory to maximize performance – optimizing both system memory and CPU memory (known as cache). This means, as data volumes grow, clients do not need to continuously buy expensive memory. Columnar organized BLU tables are well suited for compression because of their similar, common, and repeating data in each column – which is optimized by encoding frequent values with fewer bits. The patented encoding technology of BLU Acceleration’s Compression preserves the order of the data, enabling compressed data in BLU tables to be used without decompressing it. Furthermore, the encoded values are packed into bits matching the register width of the CPU – for reduced I/O, and better CPU and memory utilization. As a result of the very high levels of compression (clients report 10x compression) and elimination of indexes and aggregates, BLU Acceleration significantly reduces the need for storage. These storage savings result in cost saving on multiple fronts: e.g., hardware, power, and maintenance. BLU Acceleration is designed to take full advantage of the latest innovations in microprocessor advancements. With SIMD processing (Single Instruction Multiple Data), BLU Acceleration can apply a single instruction to many data elements simultaneously, for faster data processing. BLU Acceleration is as designed to take advantage of multiple cores for maximum core utilization. BLU Acceleration automatically detects large sections of data that don’t qualify for a query – and skips the unnecessary processing of this irrelevant data. E.g. skipping all the records prior to 2010 for a question about data from 2010 to the present. This is done with automatically maintained metadata that users do not have to worry about defining or maintaining. Data skipping can deliver vast savings across compute resources (CPU, RAM, and I/O).

38 + + + BLU Shadow Tables Single Server
Dedicated analytics and reporting Operational analytics Mixed workload analytics with OLTP OLTP Indexes Analytical Indexes + Traditional row-based tables, with indexes for, for tables dedicated to OLTP or Operational Analytics Simple BLU tables ( columnar ) for tables dedicated to analytics and reporting workloads OLTP Indexes Traditional row-based tables, with indexes and BLU Shadow Tables for tables with mixed workloads + + Power of BLU Faster analytics and reporting Faster OLTP Simpler environment Single Server All 3 scenarios in a single database

39 Oportunidad: Big Data y Analytics
2+ billion people on the Web by end 2011 30 billion RFID tags today (1.3B in 2005) 4.6 billion camera phones world wide 100s of millions of GPS enabled devices sold annually 76 million smart meters in 2009… 200M by 2014 PROBLEMAS DE RENDIMIENTO SAP BW CARGAS ANALÍTICAS COMPETENCIA: SAP con HANA ORACLE con EXADATA TERADATA MS-SQL PREMISA: AHORRO DE COSTES Of world’s data is unstructured 80% 12+ TBs of tweet data every day IT Logs ? TBs of data every day Obviously, there are many other forms of data. Let’s start with the hottest topic associated with Big Data today: social networks. Twitter generates about 12 terabytes a day of tweet data – which is every single day. Now, keep in mind, these numbers are hard to keep accurate, so the point is that they’re big, right? So don’t fixate on the actual number because they change all the time and realize that even if these numbers are out of date by 2 years, it’s at a point where it’s too staggering to handle exclusively using traditional approaches. +CLICK+ Facebook over a year ago was generating 25 terabytes of log data every day (Facebook log data reference: ) and probably about 7 to 8 terabytes of data that goes up on the Internet. Google, who knows? Look at Google Plus, YouTube, Google Maps, and all that kind of stuff. So that’s the left hand of this chart – the social network layer. Now let’s get back to instrumentation: there are massive amounts of proliferated technologies that allow us to be more interconnected than in the history of the world – and it just isn’t P2P (people to people) interconnections, it’s M2M (machine to machine) as well. Again, with these numbers, who cares what the current number is, I try to keep them updated, but it’s the point that even if they are out of date, it’s almost unimaginable how large these numbers are. Over 4.6 billion camera phones that leverage built-in GPD to tag your location or your photos, purpose built GPS devices, smart metres. If you recall the bridge that collapsed in Minneapolis a number of years ago in the USA, it was rebuilt with smart sensors inside it that measure the contraction of the concrete based on weather conditions, ice build up, and so much more. So I didn’t realise how true it was when Sam P launched Smart Planet: I thought it was a marketing play. But truly the world is more instrumented, interconnected, and intelligent than it’s ever been before and this capability allows us to address new problems and gain new insight never before thought possible and that’s what the Big Data opportunity is going to be all about! 25+ TBs of log data every day 39

40 DB2 with BLU vs Microsoft SQLServer Query Response Time: (In Seconds, Less is Better)
7X-8X Better Performance with equal cores

41 “56% better performance, with 25% of the cores ! Wow, that’s great !”
DB2 with BLU vs Microsoft SQLServer Query Response Time: (In Seconds, Less is Better) BestOffer Less Cores & Licenses but Much more Performance => Better SLA “56% better performance, with 25% of the cores ! Wow, that’s great !”

42 Estimated HW Infrastructure for Production – Year 1 and Year 5 assumption yearly 20% growth
Source Oracle database 8 TB on BW 7.0 (non-unicode) DB2 on 2-tier architecture (on one server all components) HANA on 3-tier rachitecture (database and application on different servers) Huge savings through DB2 Technology Often DB2 BLU needs 70-95% less HW

43  4 x POWER servers (160 cores)
COMPARATIVA ENTRE IBM POWER + DB2 contra ORACLE EXADATA NECESIDAD INICIAL: Sistema SAP (180 sistemas, 48 entornos de producción) CONTINUIDAD DEL NEGOCIO: Contingencia en 2 centros separados NOTA: El ejercicio de sizing se ha basado en la metodología SAP con entornos para Producción, Pre-Producción y Desarrollo/Q El nivel de rendimiento SAPS ha sido el mismo en ambos casos La infraestructura IBM es POWER8 + AIX + DB y la de Oracle es EXADATA (INTEL`+ Oracle Linux + Oracle DB) La opción de IBM permite virtualización El ejercicio es una estimación y está orientada a mostrar las diferencias de infraestructura entre ambas soluciones Customer runs DB2 on POWER - 180 systems, 48 production - 26 HA (LPM*) + 26 DR (PowerHA) 2 x data centers Possible Exadata implementation ** - 180 systems, 48 production - 26 HA + 26 DR clusters - 2 x BIGGER or more data centers 6 full racks for production + HA 6 full racks for DR 6 full racks for test/QA 6 full racks for dev 6 full racks for the rest 36 systems  4 x POWER servers (160 cores)  ~30 full racks (5760 cores) * LPM - AIX live partition mobility ** No virtualization + limited number of databases per rack (e.g. 8 database servers per full rack, max 24 processor per database)

44  4 x POWER servers (160 cores)
COMPARATIVA ENTRE IBM POWER + DB2 contra SAP HANA NECESIDAD INICIAL: Sistema SAP (180 sistemas, 48 entornos de producción) CONTINUIDAD DEL NEGOCIO: Contingencia en 2 centros separados NOTA: El ejercicio de sizing se ha basado en la metodología SAP con entornos para Producción, Pre-Producción y Desarrollo/Q El nivel de rendimiento SAPS ha sido el mismo en ambos casos La infraestructura IBM es POWER8 + AIX + DB y la de SAP HANA (INTEL+ Linux + HANA) La opción de IBM permite virtualización El ejercicio es una estimación y está orientada a mostrar las diferencias de infraestructura entre ambas soluciones 1 HANA UNIT = 64 Gb RAM = 13 K€ Customer runs DB2 on POWER - Customer runs DB2 on POWER - 180 systems, 48 production - 26 HA (LPM*) + 26 DR (PowerHA) 2 x data centers Possible HANA implementation ** - 180 systems, 48 production - 26 HA + 26 DR clusters - 2 x BIGGER or more data centers 48 appliance servers for production 52 appliance servers for HA+DR clusters up to 48 appliance servers for test/QA up to 48 appliance servers for dev up to 36 appliance servers for rest  4 x POWER servers (160 cores)  x HANA servers ( cores) * LPM - AIX live partition mobility ** No virtualization + limited number of databases per rack (e.g. 8 database servers per full rack, max 24 processor per database)

45 98 percent 30 percent 50 percent
Balluff GmbH – Game-changing boost to information delivery with IBM DB2 enables rapid insight 98 percent faster access to complex reports 30 percent typical report speed increase 50 percent faster SAP ERP response times Solution Components SAP® Business Warehouse, SAP ERP, SAP ERP HCM, SAP CRM, SAP NetWeaver® Enterprise Portal, SAP PI IBM® AIX®, DB2® for Linux, UNIX and Windows with BLU Acceleration, PowerHA® SystemMirror®, PowerVM®, System Storage SAN Volume Controller, Tivoli® Storage FlashCopy® Manager, IBM® Power® 750, FlashSystem™ 840, XIV®, IBM System and Technology Group Lab Services, IBM Software Group Services Business challenge: Balluff knew that slow access to finance and business reports threatened productivity and potential growth. How could executives gain fast insight into critical data to make better business decisions? The solution: The company moved its SAP Business Warehouse to IBM® DB2® with BLU Acceleration, running on IBM Power Systems™ with IBM AIX® and IBM PowerHA®. “IBM DB2 with BLU Acceleration is the ideal solution for us because we can gain new insights into business data more rapidly. Deploying IBM DB2 with BLU Acceleration was a low-risk project; implementation was quick and easy without affecting availability.” —Bernhard Herzog, Team Manager Information Technology SAP, Balluff Deep Blue IBM Solution SAP Stack IBM SAP Alliance © 2014 IBM Corporation 45

46 Business Analytics Accelerator
Big Data & Analytics Big Data & Analytics The Business Value, Why Speed is Money Dynamic Query Compatible Query Dynamic Cubes DB2 with BLU Business Analytics Accelerator Increase productivity & drive business growth Adding Value, not complexity Infrastructure That Matters 82X más rápido An important consideration for your selling approach, is understanding that 63% of all opportunity now come from outside of IT. Just think about that one. If you are only talking to, and selling to IT staff, you are only addressing, one third of IT based opportunities in your clients. If you have only been focused on IT, you could now triple your opportunity scope, if you SELL into the line of business in your clients. A perfect example of this recently, was a business who knew they had an issue with how long queries were taking to run on their database, and had attributed a cost to time wasted in waiting for a response. IBM and a Business Partner ran a proof of concept with a UK customer, but we focussed on presenting the POC to the Managing Director, The Finance Director and the Chief Operating officer, all of them board members in this company. The POC was such a big improvement, their query time so improved, that initially the client thought IBM had manipulated the system. The finance director then spent 30 minutes running some ad hoc queries of his own, including a very complex query that completed in 97 secs, the FD told us that this was a report that they were never able to complete in their existing environment. In fact he said they stopped this query on their system because after several hours it still had not completed. The client was so impressed, that they ended the POC by saying “We’ll take it”. The Client didn’t know what the solution was. They didn’t know what the hardware, software or services were. IBM and our partner had just fixed a business problem, and could do so at a cost that would pay back to the business in a few months. There was no discussion of how IBM’s hardware compared to a competitors. No going through a feeds and speeds check list, to see what solution was better on paper. Importantly, there wasn’t the same issue with price negotiation, as there was no competitive price to compare to. This is the difference selling to line of business makes, talking about and solving business issues <click> So what we want to talk through in this session, is a different way of talking to clients. We want to give them a “WOW”. And in this example, we can talk through what difference a big data and analytics project, can make to a business. Its understanding of its business. How it can help identify new market opportunities, to help growth. Importantly, selling a business vision with a “WOW” factor. Once we have the customer bought into the vision, excited at the prospect, we need to discuss, still from a business level perspective, “HOW” we can both enable AND deliver this difference to their business. Still with the focus on the business value, still not discussing features. And then importantly, for our sellers, our partners, and for IT Staff that may be engaged by the business, “WHAT” hardware & software we are actually providing for this solution. As the inverted triangle is alluding to, importantly, we must learn how to change the focus, so that the value to business becomes the most important aspect, not what the components of the solution are. The other great benefit is you will also be talking in a similar language to other sellers calling on the business. The objective here is not to make you an expert in Big Data and Analytics, but understand some of its benefits, and how linking with other sellers, can help you drive new and larger opportunities. It could be you help uncover a new opportunity for Big Data and Analytics, just through understanding the high level benefits to a business, at which point you can engage with your colleagues who are the experts in this field, and be part of the team that builds the end-to-end solution for the client. vs. Competitor Row Store Database on Ivy Bridge (x86)1 1) Based on IBM internal tests as of April 7, 2014 comparing IBM DB2 with BLU Acceleration on Power with a comparably tuned competitor row store database server on x86 executing a materially identical 2.6TB BI workload in a controlled laboratory environment. Test measured 60 concurrent user report throughput executing identical Cognos report workloads. Competitor configuration: HP DL380p, 24 cores, 256GB RAM, Competitor row-store database, SuSE Linux 11SP3 (Database) and HP DL380p, 16 cores, 384GB RAM, Cognos , SuSE Linux 11SP3 (Cognos). IBM configuration: IBM S824, 24 cores, 256GB RAM, DB2 10.5, AIX 7.1 TL2 (Database) and IBM S824, 16 of 20 cores activated, 384GB RAM, Cognos , SuSE Linux 11SP3 (Cognos). Results may not be typical and will vary based on actual workload, configuration, applications, queries and other variables in a production environment. 82x calculation based on geometric mean calculation giving equal weighting to the report per hour (RPH) improvements in the three categories of simple, intermediate, and complex reports. GEOMEAN(RPH_simple,RPH_intermediate,RPH_complex) = GEOMEAN(18.85,40.07,747.63)=82.66

47 POWER + BLU Acceleration pero y …. ¿Cómo avanzamos?

48 Elegir una opción de las dos configuraciones
Small Configuration Large Configuration Existing Data Warehouse Supports up to 5 TB uncompressed active data (1 TB compressed data) Hardware Configuration Power S814: 8 cores, 3.72 GHz Memory: 256 GB DRAM Storage: 146 GB (RAID 1) (OS/PGM VG) 2.4 TB HDD (RAID 5) (Data VG) AIX Standard Edition PowerVM Enterprise Edition Software Configuration DB2 Advanced Workgroup Edition Existing Data Warehouse Supports up to 10 TB uncompressed active data (3 TB compressed data) Hardware Configuration Power S824: 24 cores, 3.52 GHz Memory: 1 TB DRAM Storage: 2.4 TB HDD (RAID 5) (Data VG) 1.55 TB SSD (DB2 overflow cache) 146 GB (RAID 1) (OS/PGM VG) AIX Standard Edition PowerVM Enterprise Edition Software Configuration DB2 Advanced Workgroup Edition PRECIO MUY INTERESANTE ** PREGUNTE A SU VENDEDOR DE IBM ** 48

49 Configuración Try&Buy, incluye HW & SW
New BLU POC Program Stack: Power 8, DB with BLU Acceleration and Cognos BI 10.2 with Dynamic Cubes Target Use Cases: “Business Intelligence Workload Accelerator” Provides acceleration for BI workloads in competitive or back-level environments Can work in any environment Commodity hardware accounts Microstrategy, Business Objects SQLServer, Oracle Is an accelerator to your existing environment Configurations 5 pre-defined Power 8, DB2 BLU and Cognos BI configurations to support various workload sizes Announcement Highlights Announced: June, 2014 Leverages established Power POC processes Define the free trial period Try with your own data Owners for Additional Information

50 GRACIAS


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