Dino Quintero's Redbooks Blog

Si usted esta leyendo este blog, usted sabe algo de los IBM Redbooks y que son.  Asumimos ademáas que es también familiar con el formato de este blog que describe los cinco puntos más importantes de un tópico técnico y distribuye el conocimiento con nuestra audiencia.  Pero creemos que no todos ustedes están familiarizados con los Redbooks y queremos continuar introduciendo y promoviendo nuestro materiales a la nueva generación y comunidad de técnologos.

IBM Redbooks provee una perspectiva única a muchas preguntas técnicas desde el punto de vista de SMEs (subject matter experts) los cuales se reúnen por un corto tiempo a crear una publicación para resolver un reto técnico.  Algunas veces estos retos provienen de requisitos de clientes, experiencias en el campo, o de ideas que los residentes traen o desarrollan durante el transcurso de la creación de la  publicación.

Asi que decidimos crear 5 Cosas Que Debes Saber Acerca de IBM Redbooks para introducirnos a la nueva audiencia y quizás nuestros leales lectores aprendan algo nuevo:

1. ¿Qué son IBM Redbooks?

IBM Redbooks son documentos técnicos, blogs y videos que ayudan a aprender, adoptar e instalar soluciones creadas por SMEs y además complementan los manuales de los productos de IBM.  Por más de 40 años, IBM Redbooks han incluido contenido técnico el cual no está en manuales.  Por ejemplo:  conceptos técnicos, tendencias y direcciones de la industria, profundos escenarios técnicos, escenarios de integración con productos de terceros y contenido técnico describiendo como incorporar productos de IBM a soluciones con óptimos resultados.  Las publicaciones son descargadas y leídas millones de veces cada año y son conocidas como el estandar de oro de la comunidad técnica.  La mejor parte es que todo el material teécnico es gratuito.

2. ¿Son IBM Redbooks manuales?

IBM Redbooks no reemplazan los manuales de los productos y soluciones de IBM.  Los Redbooks complementan los manuales con prácticos escenarios técnicos, pero siempre apuntando y enlazando los manuales de IBM o al IBM Knowledge Center.

3. ¿Cómo son hechos los IBM Redbooks?

IBM Redbooks nacen del proceso de residencias de IBM Digital Business Group que reúne a un equipo de profesionales técnicos como business partners, clientes y personal de IBM.   Por medio de nominaciones el equipo de residentes es selecionado para participar en una localidad de IBM, participan remoto, y de dos a ocho semanas.  Los residentes son presentados con un escenario y crean sus soluciones en borrador las cuales se prestan al nacimiento de una publicación de IBM Redbooks.  El proceso también le da a los residentes la oportunidad de ser autores de la publicación.

4. IBM Redbooks en el mundo digital

Hace unos años, IBM Redbooks paso por una tranformación.  Previamente, Redbooks eran solamente  conocidas como largas y voluminosas guías técnicas.  En este mundo ágil, hay diferentes formatos de entrega diseñados para cortos documentos técnicos hasta más largas y comprensivas publicaciones.  Esta transformación se presto para crear nuevos formatos (Redpapers, Redguides, Product Guides, Solutions Guides, blogs, and videos) todos variando en tamaño, para incorporarlos al mundo digital.  Hoy, IBM Redbooks puede crear contenido técnico en el formato que se necesite.

IBM Redbooks son distribuidos por medio de nuestro sitio web en formatos PDF o EPUB, por medio de Apple iBooks, Google Play, y también por medio de la aplicación oficial móvil de IBM Redbooks.  Hay además impresión a demanda disponible para los lectores que quieran copias de la publicación.

5. IBM Redbooks y Open Source

IBM Redbooks también cubren tópicos relacionados a integraciones y escenarios de software y hardware de terceros incluyendo OpenStack con productos y soluciones de IBM.  Estás publicaciones tienen información de como integrar productos y soluciones no pertenecientes a IBM en los centros de cómputos.

Asegúrese de visitarnos por medio de los siguientes canales para estar al día de las últimas publicaciones:

IBM Redbooks continua creando  contenido y haciendolo disponible por medio de varios canales.  Comuniquenos si les gustaría ver los IBM Redbooks en un lugar nuevo.

Dino E. Quintero

IBM Redbooks Enterprise Solutions Enablement

SAP HANA is the SAP database platform for multiple SAP solutions. In changing direction to former classic SAP solutions, HANA is the processing core of it all. Operations that have formerly performed at application layers have moved into the database layer and are now performed by the HANA engines.  SAP HANA works by loading all the data into memory, which is why it is called an in-memory database. This is the most key factor that allows SAP HANA to run analytical reports in seconds as opposed to minutes, or in minutes as opposed to hours, allowing real-time analysis of analytical data.

Here are 5 things to know about SAP HANA on IBM Power Systems:

1.  SAP allows flexibility in a TDI implementation of HANA on IBM Power Systems.

The SAP HANA TDI architecture helps you to build an environment using your existing hardware such as servers, storage, SAN and network switches. There is a set of configuration and settings that work best for a HANA on a Power Systems implementation. This configuration and these settings are seen by many customers as the ones that bring the most performance and stability, less management and maintenance effort, and better understanding of the environment.  By supporting TDI in the deployment of SAP HANA, Power Systems give organizations choice over the technology they use, compared to the rigidly defined hardware appliances used in many competing SAP HANA infrastructures.

2.  IBM Power Systems PowerVM virtualization for SAP HANA.

IBM PowerVM virtualization is fully supported by SAP, allowing customers to deploy SAP HANA in a virtual environment that supports both dedicated and shared processor resources, running both production and non-production workloads in a single server.  IBM Power Systems provides flexibility to meet the individual needs of organizations deploying SAP HANA. One aspect of this flexibility is that a robust virtualization is supported, ready for use, and helps consolidating multiple SAP HANA virtual machines on a single Power Systems server.  Virtualization with PowerVM also provides ability to handle the varying utilization patterns that are typical in SAP HANA workloads. Dynamic capacity sizing allows for fast, granular reallocation of compute resources among SAP HANA virtual machines. This approach to load balancing and tailoring capacity to the workload enhances agility compared to competing processor architectures that require capacity to be allocated in larger chunks.

3. High availability (HA) and disaster recovery (DR) for SAP HANA.

The costs of downtime have increased over time, so companies are paying more attention to high availability (HA) today than in the past. Also, the costs for HA solutions have decreased considerably in a way that makes much more sense to invest in protecting business continuity than to undertake the downtime costs.  From a business continuity perspective, you can protect your systems by creating a local HA plan to ensure the minimum Recovery Time Objective (RTO) possible, and protect your business from a complete site failure (DR).  There are options available for high availability and disaster recovery:  SAP HANA Host Auto-Failover (Scale-Out with Standby), SAP HANA System Replication + SuseHA, SAP HANA Storage Replication, and SAP HANA System Replication.

4.  SAP HANA Systems Replication (HSR).

SAP HANA Systems Replication is a contingency solution that is used to duplicate your HANA database. This means that it uses a completely different system (that is, another operating system instance), a distinct set of disks, and a different database instance than the primary ones. In summary, it is based on having two totally independent HANA environments host the same data. The data is created on the primary system and replicated to the secondary system over the network through TCP/IP. If a failure of the primary system occurs, you can choose to have the secondary one take-over.

5.  IBM service and productivity tools for Linux on POWER.

IBM Power Systems is known for its prominent level of reliability, availability, and serviceability (RAS). The difference between an ordinary Linux for x86 image and a Linux on IBM Power image is that the latter has a layer of additional added value software to enable Linux to take advantage of Power System hardware and virtualization features, such as dynamic logical partition (DLPAR) operations, resource monitoring and control (RMC) communication with the Hardware Management Console (HMC), and other functions. 

SAP notes change constantly. Validate all notes before you start implementing your HANA environment because SAP guidelines and statements change frequently. For SAP notes, refer to the following website (SAP ONE Support Launchpad): http://launchpad.support.sap.com/

For more information about SAP HANA on IBM Power Systems, refer to the following:

IBM Power Systems for SAP HANA 
https://www-03.ibm.com/systems/power/solutions/bigdata-analytics/sap-hana/

IBM Power Systems Home Page 

http://www-03.ibm.com/systems/power/

SUSE Linux Enterprise High Availability Extension 12 SP2 Documentation
https://www.suse.com/documentation/sle-ha-12/

Automate your SAP HANA System Replication Failover
https://www-03.ibm.com/systems/power/solutions/bigdata-analytics/sap-hana/

Implementing High Availability and Disaster Recovery Solutions with SAP HANA on IBM Power Systems Redbooks publication

http://www.redbooks.ibm.com/abstracts/redp5443.html?Open

Luis Bolinches

Rodrigo Ceron Ferreira de Castro

John Wright

Fabio Martins

Dino Quintero

Data, in all forms, is expanding as a resource to be utilized. Yet in many industries and professions, the data explosion is outstripping the human capacity to understand the meaning hidden within that data. Patterns for Cognitive Computing Systems can unlock the potential in all data, internal, external, structured, unstructured, voice, and visual, and make it work together.

Cognitive Computing is perhaps most unique in that it alters the established IT doctrine that a technology’s value diminishes over time; because Cognitive Systems improve as they learn, they become more valuable. This quality among others makes cognitive technology highly desirable for business, and many early adopters are leveraging the competitive advantage it affords.

Think of a Pattern as a use case on a specific scenario such as Event based Real Time Marketing for Real Time Analytics, Anti-Money Laundering, address Data Oceans by reducing cost of Hadoop, and so on. Those are just a few of the Cognitive Patterns now available. Patterns identify and address pain points for cognitive infrastructures. These entry points then help you understand where you are on the cognitive journey and enables IBM to demonstrate the set of solutions capabilities for each lifecycle stage.

Here are 5 things to know about IBM Patterns for Cognitive Computing Systems:

1.  What are Patterns for Cognitive Computing Systems?

Patterns for Cognitive Computing Systems are solutions addressing a combination of customers’ challenges and pain points utilizing IBM Power Systems Solutions portfolio to deliver a viable recommendation to help solve the problem. Patterns for Cognitive Computing Systems helps to classify (prediction) with accuracy and can determine appropriate products to be recommended to customers. For example, utilize history for different customers, ratings on products and Machine and Deep Learning techniques to make targeted recommendations that ensure better product purchase rates, click rates, customer retention rates, better customer experiences, and others.

2. Patterns for Cognitive Computing Systems helps to eliminates data infrastructure silos and manages information lifecycle.

In the fast-paced environment customers are faced with, information storage often gets optimized to a single application or departmental requirement. This leads to information silos in an organization and creates significant difficulties in synchronizing and sharing this information across the enterprise. These silos can be spread across many different storage and file system technologies, further complicating this unifying process. Utilizing Spectrum scale and IBM Elastic Storage Server, for example, a customer can logically or physically combine these silos into a unified, more manageable and sharable storage environment.

3. Patterns for Cognitive Computing Systems helps to backup, restore and archive big data.

With the massive amounts of data that comes with big data implementations, it is often very difficult to back up business critical sets of data. Utilizing IBM Spectrum family of products (Spectrum Scale, Spectrum Archive, Spectrum Protect) and low cost and high capacity storage capabilities (Cloud Object Storage, Elastic Storage Server, Tape) customers can establish economic and performing backup, restore and archive capabilities for their big data environments.

4.  Patterns for Cognitive Computing Systems helps to meet performance requirements for technical workloads.

As requirements for instantaneous analysis of information grows with high-performance computing (HPC), high-performance data analysis (HPDA) and cognitive workloads, the high-performance access of data becomes critical. Utilizing Elastic Storage Server with Spectrum Scale Native RAID provides high data reliability, high data integrity, consistent performance.

5.  Patterns for Cognitive Computing Systems helps to augment data warehouses with Hadoop.

This cognitive pattern leverages Hadoop to help customers optimize and improve cost effectiveness of their data warehouses. Traditional, proprietary data warehouse systems are very expensive to purchase, upgrade and maintain, making them a highly desirable area for cost reduction. These systems also have difficulty in supporting unstructured data. However, they tend to be very integrated into customer business operations making them difficult to eliminate. Customers often enrich the structured data in a data warehouse with unstructured data in a Hadoop environment to provide a complete data environment.

The idea is to start the conversation with customers, listen to their challenges and pain points, and bring answers to the challenges discussed during these conversations incorporating IBM Power Systems Solutions portfolio.  For more information and examples of some of the solutions already available across industries, refer to the following documentation.

IBM Cognitive Systems PowerAI makes deep learning, machine learning, and AI more accessible and more performant.  Refer to the following webpage for more details:

https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=POD03135USEN

For IBM Watson: AI and Cognitive computing solutions with IBM Power Systems, and for a cognitive computing system designed for complex analytics -- integrating massively parallel POWER processors and DeepQA technology can be read at the following website:  https://www.ibm.com/power/solutions/cognitive-computing

For Enterprise AI, refer to the following website:  https://www.ibm.com/it-infrastructure/us-en/resources/power/enterprise-ai/

For IBM Power Systems solutions information, refer to the following website:  https://ibm.co/2DOzPoS

Cesar Maciel
Marcos Quezada
Dino Quintero

PowerAI is an IBM Cognitive Systems offering for the rapidly growing and quickly evolving artificial intelligence (AI) category of deep learning.  PowerAI brings a suite of capabilities from the open source community and combines them into a single enterprise distribution of software that incorporates complete lifecycle management from installation and configuration; data ingest and preparation; building, optimizing, and training the model; to inference; testing; and moving the model into production.

Deep learning is the fastest growing subcategory of machine learning and uses software neural networks to help develop patterns of analysis within the system to generate predictive capability: deep learning is a platform that is capable of effectively learning how to learn, and it is immensely powerful for helping clients get the most out of their data.

IBM PowerAI V1.5 is a software solution designed to provide an end-to-end deep learning platform for data scientists. This solution simplifies the process of creating deep learning environments, from single systems to the largest clusters, and provides prominent levels of deep learning training performance by taking advantage of IBM’s unique accelerated systems architecture.

Here are 5 things to know about IBM PowerAI:

1.  Helps to make deep learning easier and faster for organizations.

The solution provides workflow support for the deep learning lifecycle on a distributed architecture from data ingest and preparation, through model training and optimization to inference, moving the model into production. PowerAI helps enable your clients' teams to iterate through the deep learning cycle faster, training on more data to continuously improve the model.

2. Designed to provide an end-to-end deep learning platform for data scientist.

PowerAI offers many optimizations that can ease installation and management, and can accelerate performance, for example:

• Ready-to-use deep learning frameworks (TensorFlow, IBM Caffe, and BVLC Caffe).
• Distributed as easy-to-install binaries.
• Includes all dependencies and libraries.
• Easy updates: Code updates arrive from a repository.
• Validated deep learning platform with each release.
• Dedicated support teams for deep learning.
• Designed for enterprise scale with multisystem cluster performance and large memory support

3. Designed for enterprise scale.

PowerAI is designed for enterprise scale, with software optimized for both single server and cluster deep learning training.  PowerAI takes advantage of a distributed architecture to help enable your teams to quickly iterate through the training cycle on more data to help continuously improve the model over time.  PowerAI enables clients to distribute the training of a model across many servers, with the potential for greatly improving performance. What used to take weeks on a single server can potentially now be completed in just hours. This distributed capability is also transparent to the application logic previously written for a single server implementation. It is the best of both worlds: potential performance improvements without having to change the application code.

4. Deep learning to unleash new analytic capabilities.

Deep learning or machine learning design enables computers to learn from experiences, like how humans learn. In addition, like how humans store past experiences in their brain, deep learning design enables computers to store past experiences as data. Organizations use deep learning to develop powerful new analytic capabilities that span multiple usage patterns, from computer vision and object detection, to improved human computer interaction through natural language processing, to very sophisticated anomaly detection capabilities. At the core of any use case associated with deep learning are very sophisticated pattern recognition and classification capabilities, which serve as the springboard for revolutionary applications and insights of the future.

5.  Training neural network models.

Training a model takes a long time. Training neural network models is often measured in days or even weeks. During this time, any interruption means starting over. In addition, if accuracies are not high, the result might have limited usage and is only known after the completion of the training cycle. With PowerAI, data scientists have visual tools for understanding accuracy while the model is running; If accuracy is not high, the model can be stopped without wasting additional time.

IBM intends to deliver IBM PowerAI Vision, an application development tool for computer vision workloads. IBM PowerAI Vision is intended to automatically train deep learning models for different image and video input data sets.

To learn more about IBM Power AI, refer to the following website:

https://www.ibm.com/us-en/marketplace/deep-learning-platform

Bing He

Bruno C. Faria

Alfonso Jara

Chris Parsons

Shota Tsukamoto

Richard Wale

Dino Quintero

PowerHA SystemMirror for Linux V7.2.2 is for keeping mission-critical Linux workloads on Power Systems servers available 24 x 365. The first release of PowerHA for Linux features a high-availability (HA) solution for SAP HANA, SLES, RHEL, and PowerHA UI/Dashboard. It also supports custom workload configurations.  PowerHA V7.2.2 was designed with our AIX and Linux customers in mind. Increasingly, we see IT shops with both AIX and Linux deployments and we wanted to ensure that IT operations can readily manage both with the same look and feel. The GUI/Dashboard enables you monitor and manage both from the same screen and the CLI is designed to be the same for both environments.

PowerHA SystemMirror for Linux provides an integrated HA management solution for SAP workloads, including support for:

• HA management for SAP HANA system replication
• A wizard to deploy HA policies that enable an integrated HA management environment
• Integrated HA management for the SAP NetWeaver environment, including smart assists for simplified deployment and management

Here are 5 things to know about PowerHA SystemMirror for Linux on IBM Power Systems:

1. Solution that helps provide high availability on Linux distributions.

IBM PowerHA SystemMirror for Linux V7.2.2.0 introduces support for the following:

• SAP HANA on SUSE Linux Enterprise Server
• SAP NetWeaver on SUSE
• PowerHA Cluster manager UI
• SUSE Linux Enterprise Server (SLES) 12 (LE mode)
• Supports Linux LPARs on PowerVM platform
• Red Hat Enterprise Linux (RHEL) Little-Endian (LE) 7.2 and 7.3

2.  IBM PowerHA SystemMirror prerequisites.

PowerHA SystemMirror V7.2.2 integrates clustering technology into the kernel and the operating system, enabling our customers to be more productive while delivering high quality IT services with robust and easy-to- manage solutions.  PowerHA SystemMirror for Linux V7.2.2 supports:

• IBM POWER8 and later technology-based servers
• SUSE Linux Enterprise Server (SLES) 12 (LE mode)
• Linux LPARs on PowerVM platform
• Red Hat Enterprise Linux (RHEL) Little-Endian (LE) 7.2 and 7.3

3.  Smart assists streamline implementation and configuration.

PowerHA V7.2.2 provides smart assists for easier, out-of-the-box high availability setup and application management for SAP HANA scale-up and SAP NetWeaver. The smart assists are high-availability agents for application deployment and management.  Smart assists are used to define high-availability policies by discovering software that is deployed within the cluster. Discovery-based information helps define the high availability policy and provides periodic health monitoring, enabling middleware and resource dependencies to be restarted via the specified policy.

4.  The UI/Dashboard enables you to monitor and manage both your AIX and Linux clusters from a single screen.

The PowerHA V7.2.2 UI/Dashboard enables you to monitor and manage both your PowerHA on AIX and your PowerHA on Linux clusters from the same screen. You will be able to set up cluster zones for multitenant hosting and establish user role-based access authorization. The PowerHA UI/Dashboard will enable you to conduct routine cluster management such as move RSG, start/stop cluster, and cluster verification.

5.  PowerHA SystemMirror V7.2.2 for Linux disaster recovery.

The PowerHA SystemMirror V7.2.2 for Linux does not offer an Enterprise Edition. Our recommended solution for disaster recovery is Geographically Dispersed Resiliency (GDR). With GDR clients can replicate their traditional data center cluster VMs a remote location for disaster recovery. GDR makes disaster recovery testing relatively simple while putting the operator in charge of managing failover policy and procedures.

High availability solutions from IBM provide clients with the confidence that comes from integrated design and testing. This reduces the risk of failures resulting from combining disparate components from multiple vendors and can be a critical factor for business environments. IBM high availability solutions provide the advantage of IBM Power Systems, the AIX or IBM i operating systems, IBM Storage offerings and PowerHA SystemMirror software.  For more information on the IBM PowerHA SystemMirror, refer to the following:

Power Systems solutions for high availability Resiliency for AIX, Linux and IBM i

https://www-03.ibm.com/systems/power/software/availability/

IBM Knowledge Center – PowerHA SystemMirror for Linux V7.2.2
https://ibm.co/2DaEFzq

IBM Power Systems Home Page
http://www-03.ibm.com/systems/power/

Dino E. Quintero

5 things to know about IBM Spectrum Scale:

• Spectrum Scale was introduced in 1998, formerly known as IBM GPFS, and also formerly known as code name IBM Elastic Storage.
• Spectrum Scale was designed from the beginning to support high performance parallel workloads, and has since proven effectiveness for a variety of applications.
• Spectrum Scale is designed to help organizations tackle emerging file storage challenges.
• A Spectrum Scale file system is built from a collection of storage devices that contain the file system data and metadata.
• Spectrum Scale helps simplify data management with integrated tools designed to help manage petabytes of data and billions of files

For more information, refer to the following website:

http://www-03.ibm.com/systems/storage/spectrum/scale/index.html

5 Things to Know About Open Platform for Database-as-a-Service (DBaaS) on IBM Power Systems

Traditional enterprise computing, with its reliance on conventional databases designed for structured data, is unable to cope with this deluge. That’s why organizations everywhere are modernizing their data platforms, using all available technology, to derive patterns and insights from both structured and unstructured data. Next-generation applications based on open source technology, and especially open source databases, are critical for this modernization.

Open Platform for Database-as-a-Service (DBaaS) on IBM Power Systems provides a turnkey solution that enables application developers to provision their choice of the most popular open source databases in minutes. The solution integrates OpenPOWER servers, storage, and open source software and services components that are required to automate the deployment of popular open source databases on demand.

Here are 5 things to know about Open Platform for DBaaS on IBM Power Systems:

1.  Faster time to value and improved productivity.

Open Platform for DBaaS on IBM Power Systems has unique advantages over traditional database deployment models. One, it improves speed and agility with on-demand and agile provisioning of databases, a requirement for today’s cloud workloads. Two, it significantly reduces licensing and infrastructure costs. Three, it eliminates database sprawl generated by the hundreds or thousands of underutilized or unutilized databases that have accumulated over the years in organizations.

2. Superior performance and price-performance.

IBM Power Systems solutions deliver remarkable price-performance advantage over x86-based solutions for the leading open source databases, including MongoDB and EDB Postgres. This advantage not only reduces server and database sprawl, but also frees up precious resources that can be allocated to higher value projects critical to drive innovation for your business.

3. Fully open with no vendor lock-in.

Open Platform for DBaaS on IBM Power Systems is an open-source-based platform that integrates servers, storage, operating systems, middleware and databases, disrupting conventional x86-based solutions with substantial ease-of-use and administration benefits, and price-performance advantages.  The solution combines three elements: open source and ISV databases; OpenStack and Ubuntu Linux distribution and support; IBM OpenPOWER System LC servers, networking, storage, services and support.

4. Flexible with choice of most popular open source databases, on demand.

The solution supports a self-service portal for end users who can deploy in minutes their choice of the most popular open source community-based databases, including MongoDB, PostgreSQL, MySQL, MariaDB, and Redis. In addition, clients who want to build and deploy their own custom databases to the database image library can take advantage of the database image building tool. An open source, cloud-oriented operations manager will provide dashboards and tools to visualize, control, monitor, and analyze the physical and virtual resources comprising the Open Platform for DBaaS on IBM Power Systems.

5.  Enterprise-grade foundation for compliance.

The IBM OpenPOWER System LC server portfolio was codeveloped by IBM and OpenPOWER Foundation members to help deliver better data-centric innovation around IBM Power architecture. OpenPOWER System LC servers integrate virtually seamlessly into data centers and clouds to scale data-intensive workflows with maximum performance and minimum cost and server footprint. This integration frees up organizations to focus on solving critical business challenges and accelerating innovation.

The exponential growth of data demands not only the fastest throughput but also smarter networks. Mellanox intelligent interconnect solutions incorporate advanced acceleration engines that perform sophisticated processing algorithms on the data as it moves through the network. Intelligent network solutions greatly improve the performance and total infrastructure efficiency of data-intensive applications.

As part of the Open Platform for DBaaS on IBM Power Systems, IBM delivers Ansible scripts to support OpenStack Trove-based DBaaS installation and configuration on Power Systems servers, storage and networking.  Pre-tested reference architectures are provided in four configurations that are designed for varying levels of client needs: starter, entry, enterprise and performance configurations.  Each configuration includes appropriately sized compute, storage and networking hardware, and IBM Lab services and tooling, for a complete solution deployment. IBM also provides multiple options and configurations to extend the open source DBaaS platform across private or public clouds.

To learn more about Open Platform for DBaaS on IBM Power Systems, refer to the following website:

https://www.ibm.com/power/solutions/modern-data-platform#DBaaS

Eduardo Cerdas

Rafael Folco

Fabio Martins

Dino Quintero

5 Things to Know about the IBM Elastic Storage Server (ESS):

• The Elastic Storage Server (ESS) is built on IBM Spectrum Scale (formerly IBM GPFS) for Linux.
• The Elastic Storage Server solution combines the CPU and I/O capability of the IBM POWER8 architecture.
• The Elast Storage Server deploys the latest solid state (SSD), SAS and Nearline SAS drives.
• The Elastic Storage Server is equipped to manage the complete data lifecycle.
• The Elastic Storage Server solution is designed for a variety of workloads.

For more information, refer to the following website:

http://www-03.ibm.com/systems/storage/spectrum/ess/

5 Things to Know About the IBM Reference Architecture for High Performance Analytics in HealthCare and Life Science

Facing the challenges of data tsunami and parallel discovery, IBM has been working to evolve high performance computing (HPC) into High Performance Data Analytics (HPDA) to harness the power of big data, cloud and deep learning.

Advancements in high-throughput molecular profiling techniques and high-performance computing systems have introduced in a new area of personalized healthcare where the treatment and prevention of a disease can be tailored to the unique molecular profiles, behavioral characteristics, and environmental exposures of individual patients. 

Healthcare and life science organizations must manage, access, store, share and analyze big data within the constraints of their IT budgets.  For many biomedical research and clinical organizations, large-scale initiatives in personalized healthcare are technical daunting.  IBM’s reference architecture for healthcare and life sciences defines a platform for delivering the highest level of performance for big data workloads, while also lowering the total cost of IT ownership.

Here are 5 things to know about the IBM Reference Architecture for High Performance Analytics in HealthCare and Life Science:

1.  Diverse computing architecture built on a common infrastructure.

IBM Spectrum Computing cloud solutions for high performance cloud transform static computing resources into flexible private, hybrid and public clouds that can be shared, remotely managed and easily provisioned to support the demands of technical computing, analytics, Hadoop and other compute- and data-intensive workloads.

2. Building blocks:  Spectrum Computing, Spectrum Symphony, and OpenPOWER with IBM Power Systems.

IBM Spectrum Computing provides a comprehensive set of workload management capabilities; all designed to work together to address your needs.  IBM Spectrum Symphony employs optimization techniques that allow sub-millisecond response and fast provisioning for a variety of workloads. Thus, short-running jobs spend a smaller percentage of time in the provisioning and deprovisioning steps, giving a higher useful work-to-overhead ratio. IBM Spectrum Symphony has a high job throughput rate that allows more than 17,000 tasks to be submitted per second.  OpenPOWER systems are being designed to support compute- and data-intensive workloads, such as machine learning and deep neural networks.

3. Key platform capabilities.

IBM Spectrum Computing offers a comprehensive set of cloud capabilities designed to work together to address your high-performance cloud needs to help you deliver application-ready clusters in the cloud.  IBM Spectrum Computing assists organizations with consolidating data center infrastructure and sharing resources across on premise, cloud or hybrid environments. IBM Spectrum Computing includes three new software solutions: IBM Spectrum Conductor, IBM Spectrum LSF and IBM Spectrum Symphony.

4.  Hybrid architecture built on IBM Spectrum Computing and IBM Spectrum Scale.

IBM Spectrum Computing helps remove the complexity out of the cluster management.  It simplifies the entire cluster management process from the initial deployment to final production, thus significantly improve the time for cluster readiness. The automated provisioning, maintenance, and monitoring capabilities bring productivity to the IT administrators and help improve overall system performance while optimizing the resource utilization.

5.  Ecosystem of business partners in the healthcare and life sciences industry.

Healthcare and life science industry subject matter experts, both within and outside of IBM, contribute to the enablement of computational algorithms, user applications, and data repositories that clinicians and research scientists might choose to run on IBM Systems infrastructure.  To meet full system requirements for customers pursuing personalized healthcare initiatives, IBM Systems has already formed business and development partnerships with healthcare and life science industry leaders

IBM is also developing ground-breaking technologies for hybrid cloud, converged platform, and metadata/provenance systems to enable the architecture.  For more information, visit the  website:  https://www.ibm.com/storage/healthcare-industry

The expanded software-defined computing portfolio complements the IBM Spectrum Storage software-defined storage family. The IBM Spectrum portfolio provides clients with a unique set of software-defined infrastructure capabilities.  For more information, visit the website:  https://www.ibm.com/spectrum-computing

For detailed information about the IBM Reference Architecture for High Performance Analytics in HealthCare and Life Science, refer to the following website: 

https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=TSW03536USEN

For IBM Redbooks publications, refer to IBM Reference Architecture for Genomics: Speed, Scale, Smarts at the following website: http://www.redbooks.ibm.com/abstracts/redp5210.html?Open

Frank Lee

Dino Quintero

• New generation of data management innovation for cost effective analytics
• Next generation database for data intensive analytics and reporting
• New technology in DB2 for analytic queries taking advantages of the optimization with the IBM POWER platform
• Industry solution delivering storage savings, performance, and time to value
• This solution combines the experience and expertise of IBM to deliver technology leadership

5 Things You Should Know about IBM Data Engine for Genomics - Power Systems Edition

• The architecture is designed to address the grand challenge of analyzing increasingly large genome-related datasets.
• The high-throughput architecture and reference design enables fast turnaround for a wide variety of workflows including genomic medicine, agrigenomics, biofuels, forensics and drug development. 
• This solution is based on multi-year collaborations with leaders in the Life Sciences industry.
• This dynamic platform integrates high performance compute, storage, workflow orchestration and portal access, and can also be easily adapted to support large scale and cloud based deployments. 
• The most recent solution version further exploits the capabilities of IBM POWER8 and introduces the IBM Elastic Storage Server (ESS), defining a complete solution containing all of the hardware and software elements required to accomplish genomics processing for data analysis.

For more information about IBM Data Engine for Genomics – Power Systems Edition Architecture and Reference Design Version 3.0, refer to the following website:

http://ibm.co/1i1NPzi

For more information about IBM Health Care and Life Sciences solutions, refer to the following website:
http://www-03.ibm.com/systems/power/solutions/industry/healthcare.html

• 5 things you should know about IBM High performance computing (HPC) and technical computing solutions:
• IBM Power Systems high performance computing and technical computing solutions deliver faster time to value with intuitive and powerful solutions. 
• Configurable into highly scalable Linux clusters, Power Systems offer extreme performance for demanding workloads such as genomics, finance, computational chemistry, oil and gas exploration, and high performance data analytics.
• Hardware, solutions and ecosystem:
  • IBM Power LC server line for clusters and clouds
  • Scale-out servers for Linux
  • Elastic Storage Server (ESS)
  • OpenPOWER Foundation
• Software, solutions, and ecosystem:
  • IBM Platform Computing software
  • IBM Spectrum Scale Storage Software (formerly GPFS)
  • Extreme Cloud Administraton Toolkit (xCAT)
  • Parallel Environment (PE)
  • Engineering and Scientific Subroutine Library (ESSL) and Parallel ESSL
• About the OpenPOWER Foundation:  The OpenPOWER Foundation is a collaboration encouraging the adoption of an open server architecture for data centers. It has grown to more than 150 members across 22 countries. IBM’s POWER architecture is the cornerstone of innovation for OpenPOWER, creating a computing platform available to all.  For more information about the OpenPOWER Foundation, refer to the following website: http://openpowerfoundation.org/

For more information on IBM High Performance Computing (HPC) and Technical Computing Solutions, refer to the following website:

http://www-03.ibm.com/systems/power/solutions/high-performance-computing/index.html