Posts Tagged ‘Cloud’

IBM Puts Open DBaaS on IBM OpenPOWER LC Servers

June 15, 2017

Sometimes IBM seems to be thrashing around looking for anything hot that’s selling, and the various NoSQL databases definitely are hot. The interest is driven by DevOps, cloud, and demand for apps fast.

A month or so ago the company took its Power LC server platform to the OpenPOWER Developer Conference in San Francisco where they pitched Database-as-a-Service (DBaaS) and a price-performance guarantee: OpenPOWER LC servers designed specifically for Big Data to deliver a 2.0x price-performance advantage over x86 for MongoDB and 1.8x for EDB PostgreSQL 9.5 guaranteed. With organizations seeking any performance advantage, these gains matter.

There are enough caveats that IBM will almost never be called to deliver on the guarantee. So, don’t expect to cash in on this very quickly. As IBM says in the miles of fine print: the company will provide additional performance optimization and tuning services consistent with IBM Best Practices, at no charge.  But the guarantee sounds intriguing. If you try it, please let DancingDinosaur know how it works out.

IBM Power System S822LC for Big Data

BTW, IBM published the price for the S822LC for big data as starting at $6,399.00 USD. Price includes shipping. Linux OS, however, comes for an additional charge.

Surprisingly, IBM is not aiming this primarily to the IBM Cloud. Rather, the company is targeting the private cloud, the on-premises local version. Its Open DBaaS toolkit, according to IBM, provides enterprise clients with a turnkey private cloud solution that pre-integrates an Open Source DB image library, OpenStack-based private cloud, and DBaaS software packages with hardware (servers/storage/network switches/rack) and a single source of support to enable a DBaaS self-service portal for enterprise developers and LOB users to provision MongoDB, Postgres, and others in minutes. But since it is built on OpenStack, it also supports hybrid cloud integration with IBM Cloud offerings via OpenStack APIs.

In terms of cost it seems remarkably reasonable. It comes in four reference configurations. The Starter configuration is ~$80k (US list price) and includes 3 Power 822LC servers, pair of network switches, rack, DBaaS Toolkit software, and IBM Lab Services. Other configurations include Entry, Cloud Scale, and Performance configurations that have been specified for additional compute, storage, and OpenStack control plane nodes along with high-capacity JBOD storage drawers. To make this even easier, each configuration can be customized to meet user requirements. Organizations also can provide their own racks and/or network switches.

Furthermore, the Power 822LC and Power 821LC form the key building blocks for the compute, storage and OpenStack control plane nodes. As a bonus, however, IBM includes the new 11-core Power 822LC, which provides an additional 10-15% performance boost over the 10-core Power 822LC for the same price.

This is a package deal, at least if you want the best price and to deploy it fast. “As the need for new applications to be delivered faster than ever increases in a digital world, developers are turning to modern software development models including DevOps, as-a-Service, and self-service to increase the volume, velocity and variety of business applications,” said Terri Virnig, VP, Power Ecosystem and Strategy at IBM. Open Platform for DBaaS on IBM in the announcement. Power Systems DBaaS package  includes:

  • A self-service portal for end users to deploy their choice of the most popular open source community databases including MongoDB, PostgreSQL, MySQL, MariaDB, Redis, Neo4j and Apache Cassandra deployable in minutes
  • An elastic cloud infrastructure for a highly scalable, automated, economical, and reliable open platform for on-premises, private cloud delivery of DBaaS
  • A disk image builder tool for organizations that want to build and deploy their own custom databases to the database image library

An open source, cloud-oriented operations manager with dashboards and tools will help you visualize, control, monitor, and analyze the physical and virtual resources. A turnkey, engineered solution comprised of compute, block and archive storage servers, JBOD disk drawers, OpenStack control plane nodes, and network switches pre-integrated with the open source DBaaS toolkit is available through GitHub here.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

Syncsort Drives zSystem and Distributed Data Integration

June 8, 2017

IBM appears to be so busy pursuing its strategic imperatives—security, blockchain, quantum computing, and cognitive computing—that it seems to have forgotten the daily activities that make up the bread-and-butter of mainframe data centers. Stepping up to fill the gap have been mainframe ISVs like Compuware, Syncsort, Data Kinetics, and a few others.

IBM’s Project DataWorks taps into unstructured data often missed

IBM hasn’t completely ignored this need. For instance, Project DataWorks uses Watson Analytics and natural language processing to analyze and create complex visualizations. Syncsort, on the other hand, latched onto open Apache technologies, starting in the fall of 2015. Back then it introduced a set of tools to facilitate data integration through Apache Kafka and Apache Spark, two of the most active Big Data open source projects for handling real-time, large-scale data processing, feeds, and analytics.

Syncsort’s primary integration vehicle then revolved around the Intelligent Execution capabilities of its DMX data integration product suite with Apache Spark. Intelligent Execution allows users to visually design data transformations once and then run them anywhere – across Hadoop, MapReduce, Spark, Linux, Windows, or Unix, both on premise or in the cloud.

Since then Syncsort, in March, announced another big data integration solution. This time its DMX-h, is now integrated with Cloudera Director, enabling organizations to easily deploy DMX-h along with Cloudera Enterprise on Amazon Web Services, Microsoft Azure, or Google Cloud. By deploying DMX-h with CDH, Syncsort explained, organizations can quickly pull data into new, ready-to-work clusters in the cloud. This accelerates how quickly they can take advantage of big data cloud benefits, including cost savings and Data-as-a-Service (DaaS) delivery.

A month before that, this past February, Syncsort introduced new enhancements in its Big Data integration solution by again deploying DMX-h to deliver integrated workflow capabilities and Spark 2.0 integration, which simplifies Hadoop and Spark application development, effectively enabling mainframe data centers to extract maximum value from their data assets.

In addition, Syncsort brought new integrated workflow capabilities and Spark 2.0 integration to simplify Hadoop and Spark application development. It lets data centers tap value from their enterprise data assets regardless of where it resides, whether on the mainframe, in distributed systems, or in the cloud.

Syncsort’s new integrated workflow capability also gives organizations a simpler, more flexible way to create and manage their data pipelines. This is done through the company’s design-once, deploy-anywhere architecture with support for Apache Spark 2.0, which makes it easy for organizations to take advantage of the benefits of Spark 2.0 and integrated workflow without spending time and resources redeveloping their jobs.

Assembling such an end-to-end data pipeline can be time-consuming and complicated, with various workloads executed on multiple platforms, all of which need to be orchestrated and kept up to date. Delays in such complicated development, however, can prevent organizations from getting the timely insights they need for effective decision-making.

Enter Syncsort’s Integrated Workflow, which helps organizations manage various workloads, such as batch ETL on large repositories of historical data. This can be done by referencing business rules during data ingest in a single workflow, in effect simplifying and speeding development of the entire data pipeline, from accessing critical enterprise data, to transforming that data, and ultimately analyzing it for business insights.

Finally, in October 2016 Syncsort announced new capabilities in its Ironstream software that allows organizations to access and integrate mainframe log data in real-time to Splunk IT Service Intelligence (ITSI). Further, the integration of Ironstream and Compuware’s Application Audit software deliver the audit data to Splunk Enterprise Security (ES) for Security Information and Event Management (SIEM). This integration improves an organization’s ability to detect threats against critical mainframe data, correlate them with related information and events, and satisfy compliance requirements.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

IBM Introduces Hitachi-Specific z13

May 30, 2017

Remember when rumors were flying that Hitachi planned to buy the mainframe z Systems business from IBM?  DancingDinosaur didn’t believe it at that time, and now we have an official announcement that IBM is working with Hitachi to deliver mainframe z System hardware for use with Hitachi customers.

Inside the IBM z13

DancingDinosaur couldn’t see Hitachi buying the z. The overhead would be too great. IBM has been sinking hundreds of millions of dollars into the z, adding new capabilities ranging from Hadoop and Spark natively on z to whatever comes out of the Open Mainframe Project.

The new Hitachi deal takes the z in a completely different direction. The plans calls for using Hitachi’s operating system, VOS3, running on the latest IBM z13 hardware to provide Hitachi users with better performance while sustaining their previous investments in business-critical Hitachi data and software, as IBM noted. VOS3 started as a fork of MVS and has been repeatedly modified since.

According to IBM, Hitachi will exclusively adopt the IBM z Systems high-performance mainframe hardware technology as the only hardware for the next generation of Hitachi’s AP series. These systems primarily serve major organizations in Japan. This work expands Hitachi’s cooperation with IBM to make mainframe development more efficient through IBM’s global capabilities in developing and manufacturing mainframe systems. The Open Mainframe Project, BTW, is a Linux initiative.

The collaboration, noted IBM, reinforces its commitment to delivering new innovations in mainframe technology and fostering an open ecosystem for the mainframe to support a broad range of software and applications. IBM recently launched offerings for IBM z Systems that use the platform’s capabilities for speed, scale and security to deliver cloud-based blockchain services for building new transaction systems and machine learning for analyzing large amounts of data.

If you count VOS3, the mainframe now runs a variety of operating systems, including z/OS, z/TPF and z/VM operating systems as well as the Linux. Reportedly, Hitachi plans to integrate its new mainframe with its Lumada Internet of Things (IoT) offerings. With z scalability, security, massive I/O, and performance the z makes an ideal IoT platform, and IoT is a market IBM targets today. Now IBM is seeding a competitor with the z running whatever appealing capabilities Hitachi’s Lumada offers. Hope whatever revenue or royalties IBM gets is worth it.

IBM and Hitachi, as explained in the announcement, have a long history of cooperation and collaboration in enterprise computing technologies. Hitachi decided to expand this cooperation at this time to utilize IBM’s most advanced mainframe technologies. Hitachi will continue to provide its customers with a highly reliable, high-performance mainframe environment built around the Hitachi VOS3 operating system. Hitachi also continues to strengthen mainframe functionality and services which contributes to lower TCO, improved ease of system introduction and operation, and better serviceability.

Of course, the mainframe story is far from over. IBM has been hinting at a new mainframe coming later this year for months.  Since IBM stopped just automatically cranking up core processor speed to boost price/performance it will employ an array of assist processors and software optimizations to boost performance wherever it can, but particularly in the area of its current critical imperatives—security, cognitive computing, blockchain, and cloud. One thing DancingDinosaur doesn’t expect to see in the new z, however, will be cubits embedded, but who knows?

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

IBM Insists Storage is Generating Positive Revenue

May 19, 2017

At a recent quarterly briefing on the company’s storage business, IBM managers crowed over its success: 2,000 new Spectrum Storage customers, 1,300 new DS8880 systems shipped, 1500 PB of capacity shipped, 7% revenue gain Q1’17. This appeared to contradict yet another consecutive losing quarter in which only IBM’s Cognitive Solutions (includes Solutions Software and Transaction Processing Software) posted positive revenue.

However, Martin Schroeter, Senior Vice President and Chief Financial Officer (1Q’17 financials here), sounded upbeat about IBM storage in the quarterly statement: Storage hardware was up seven percent this quarter, led by double-digit growth in our all-flash array offerings. Flash contributed to our Storage revenue growth in both midrange and high-end. In storage, we continue to see the shift in value towards software-defined environments, where we continue to lead the market. We again had double-digit revenue growth in Software-Defined Storage, which is not reported in our Systems segment. Storage software now represents more than 40 percent of our total storage revenue.

IBM Flash System A9000

Highly parallel all-flash storage for hyperscale and cloud data centers

Schroeter continued: Storage gross margins are down, as hardware continues to be impacted by price pressure. To summarize Systems, our revenue and gross profit performance were driven by expected cycle declines in z Systems and Power, mitigated by Storage revenue growth. We continue to expand our footprint and add new capabilities, which address changing workloads. While we are facing some shifting market dynamics and ongoing product transitions, our portfolio remains uniquely optimized for cognitive and cloud computing.

DancingDinosaur hopes he is right.  IBM has been signaling a new z System coming for months, along with enhancements to Power storage. Just two weeks ago IBM reported achievements with Power and Nvidia, as DancingDinosaur covered at that time.

If there was any doubt, all-flash storage is the way IBM and most other storage providers are heading for the performance and competitive economics. In January IBM announced three all flash DS888* all flash products, which DancingDinosaur covered at the time here. Specifically:

  • DS8884 F (the F designates all flash)—described by IBM as performance delivered within a flexible and space-saving package
  • DS8886 F—combines performance, capacity, and cost to support a variety of workloads and applications
  • DS8888 F—promises performance and capacity designed to address the most demanding business workload requirements

The three products are intended to provide the speed and reliability needed for workloads ranging from enterprise resource planning (ERP) and financial transactions to cognitive applications like machine learning and natural language processing. Doubt that a lot of mainframe data centers are doing much with cognitive systems yet, but that will be coming.

Spectrum Storage also appears to be looming large in IBM’s storage plans. Spectrum Storage is IBM’s software defined storage (SDS) family of products. DancingDinosaur covered the latest refresh of the suite of products this past February.

The highlights of the recent announcement included the addition of Cloud Object Storage and a version of Spectrum Virtualize as software only.  Spectrum Control got a slew of enhancements, including new cloud-based storage analytics for Dell EMC VNX, VNXe, and VMAX; extended capacity planning views for external storage, and transparent cloud tiering for IBM Spectrum Scale.  The on-premises editions added consolidated chargeback/showback and support for Dell EMC VNXe file storage. This should make it clear that Spectrum Storage is not only for underlying IBM storage products.

Along the same lines, Spectrum Storage added VMware 6 support and the certified vSphere Web client. In the area of cloud object storage, IBM added native NFS access, enhance STaaS multi-tenancy, IPV6 support, and preconfigured bundles.

IBM also previewed enhancements coming in 2Q’17.   Of specific interest to DancingDinosaur readers will likely be  the likely updates to the FlashSystem and VeraStack portfolio.

The company is counting on these enhancements and more to help pull IBM out of its tailspin. As Schroeter wrote in the 1Q’17 report: New systems product introductions later in the year will drive improved second half performance as compared to the first. Hope so; already big investors are cashing out. Clients, however, appear to be staying for now.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

IBM Gets Serious About Open Data Science (ODS) with Anaconda

April 21, 2017

As IBM rapidly ramps up cognitive systems in various forms, its two remaining platforms, z System and POWER, get more and more interesting. This week IBM announced it was bringing the Anaconda Open Data Science (ODS) platform to its Cognitive Systems and PowerAI.

Anaconda, Courtesy Pinterest

Specifically, Anaconda will integrate with the PowerAI software distribution for machine learning (ML) and deep learning (DL). The goal: make it simple and fast to take advantage of Power performance and GPU optimization for data-intensive cognitive workloads.

“Anaconda on IBM Cognitive Systems empowers developers and data scientists to build and deploy deep learning applications that are ready to scale,” said Bob Picciano, senior vice president of IBM Cognitive Systems. Added Travis Oliphant, co-founder and chief data scientist, Continuum Analytics, which introduced the Anaconda platform: “By optimizing Anaconda on Power, developers will also gain access to the libraries in the PowerAI Platform for exploration and deployment in Anaconda Enterprise.”

With more than 16 million downloads to date, Anaconda has emerged as the Open Data Science platform leader. It is empowering leading businesses across industries worldwide with tools to identify patterns in data, uncover key insights, and transform basic data into the intelligence required to solve the world’s most challenging problems.

As one of the fastest growing fields of AI, DL makes it possible to process enormous datasets with millions or even billions of elements and extract useful predictive models. DL is transforming the businesses of leading consumer Web and mobile application companies, and it is catching on with more traditional business.

IBM developed PowerAI to accelerate enterprise adoption of open-source ML and DL frameworks used to build cognitive applications. PowerAI promises to reduce the complexity and risk of deploying these open source frameworks for enterprises on the Power architecture and is tuned for high performance, according to IBM. With PowerAI, organizations also can realize the benefit of enterprise support on IBM Cognitive Systems HPC platforms used in the most demanding commercial, academic, and hyperscale environments

For POWER shops getting into Anaconda, which is based on Python, is straightforward. You need a Power8 with IBM GPU hardware or a Power8 combined with a Nvidia GPU, in effect a Minsky machine. It’s essentially a developer’s tool although ODS proponents see it more broadly, bridging the gap between traditional IT and lines of business, shifting traditional roles, and creating new roles. In short, they envision scientists, mathematicians, engineers, business people, and more getting involved in ODS.

The technology is designed to run on the user’s desktop but is packaged and priced as a cloud subscription with a base package of 20 users. User licenses range from $500 per year to $30,000 per year depending on which bells and whistles you include. The number of options is pretty extensive.

According to IBM, this started with PowerAI to accelerate enterprise adoption of open-source ML/DL learning frameworks used to build cognitive applications. Overall, the open Anaconda platform brings capabilities for large-scale data processing, predictive analytics, and scientific computing to simplify package management and deployment. Developers using open source ML/DL components can use Power as the deployment platform and take advantage of Power optimization and GPU differentiation for NVIDIA.

Not to be left out, IBM noted growing support for the OpenPOWER Foundation, which recently announced the OpenPOWER Machine Learning Work Group (OPMLWG). The new OPMLWG includes members like Google, NVIDIA and Mellanox to provide a forum for collaboration that will help define frameworks for the productive development and deployment of ML solutions using OpenPOWER ecosystem technology. The foundation has also surpassed 300-members, with new participants such as Kinetica, Red Hat, and Toshiba. For traditional enterprise data centers, the future increasingly is pointing toward cognitive in one form or another.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

IBM Changes the Economics of Cloud Storage

March 31, 2017

Storage tiering used to be simple: active data went to your best high performance storage, inactive data went to low cost archival storage, and cloud storage filled in for one or whatever else was needed. Unfortunately, today’s emphasis on continuous data analytics, near real-time predictive analytics, and now cognitive has complicated this picture and the corresponding economics of storage.

In response, last week IBM unveiled new additions to the IBM Cloud Object Storage family. The company is offering clients new choices for archival data and a new pricing model to more easily apply intelligence to unpredictable data patterns using analytics and cognitive tools.

Analytics drive new IBM cloud storage pricing

By now, line of business (LOB) managers, having been exhorted to leverage big data and analytics for years, are listening. More recently, the analytics drumbeat has expanded to include not just big data but sexy IoT, predictive analytics, machine learning, and finally cognitive science. The idea of keeping data around for a few months and parking it in a long term archive to never be looked at again until it is finally deleted permanently just isn’t happening as it was supposed to (if it ever did). The failure to permanently remove expired data can become costly from a storage standpoint as well as risky from an e-discovery standpoint.

IBM puts it this way: Businesses typically have to manage across three types of data workloads: “hot” for data that’s frequently accessed and used; “cool” for data that’s infrequently accessed and used; and “cold” for archival data. Cold storage is often defined as cheaper but slower. For example, if a business uses cold storage, it typically has to wait to retrieve and access that data, limiting the ability to rapidly derive analytical or cognitive insights. As a result, there is a tendency to store data in more expensive hot storage.

IBM’s new cloud storage offering, IBM Cloud Object Storage Flex (Flex), uses a “pay as you use” model of storage tiers potentially lowering the price by 53 percent compared to AWS S3 IA1 and 75 percent compared to Azure GRS Cool Tier.2 (See footnotes at the bottom of the IBM press release linked to above. However IBM is not publishing the actual Flex storage prices.) Flex, IBM’s new cloud storage service, promises simplified pricing for clients whose data usage patterns are difficult to predict. Flex promises organizations will benefit from the cost savings of cold storage for rarely accessed data, while maintaining high accessibility to all data.

Of course, you could just lower the cost of storage by permanently removing unneeded data.  Simply insist that the data owners specify an expiration date when you set up the storage initially. When the date arrives in 5, 10, 15 years automatically delete the data. At least that’s how I was taught eons ago. Of course storage costs orders of magnitude less now although storage volumes are orders of magnitude greater and near real-time analytics weren’t in the picture.

Without the actual rates for the different storage tiers you cannot determine how much Storage Flex may save you.  What it will do, however, is make it more convenient to perform analytics on archived data you might otherwise not bother with.  Expect this issue to come up increasingly as IoT ramps up and you are handling more data that doesn’t need hot storage beyond the first few minutes of its arrival.

Finally, the IBM Cloud Object Storage Cold Vault (Cold Vault) service gives clients access to cold storage data on the IBM Cloud and is intended to lead the category for cold data recovery times among its major competitors. Cold Vault joins its existing Standard and Vault tiers to complete a range of IBM cloud storage tiers that are available with expanded expertise and methods via Bluemix and through the IBM Bluemix Garages.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

IBM Spotlights Blockchain and Hyperledger Fabric at IBM InterCONNECT

March 23, 2017

IBM announced earlier this week Hyperledger Fabric v 1.0 beta, with security for regulated industries, governance tools, and over 1,000 transactions per second possible.  This is represents the first enterprise-ready blockchain service based on the Linux Foundation’s open source Hyperledger Fabric version 1.0. The service enables developers to quickly build and host security-rich production blockchain networks on the IBM Cloud and underpinned by IBM LinuxONE.

Maersk and IBM transform global trade with blockchain

LinuxONE, a dedicated z-based Linux system with as much security as any commercial platform is likely to have, should play a central role in blockchain networks. The machine also delivers all the itys the z is renowned for: scalability, availability, flexibility, manageability, and more.

The Linux Foundation’s open source Hyperledger Fabric v1.0 is being developed by members of the Hyperledger consortium alongside other open source blockchain technologies. The Hyperledger consortium’s Technical Steering Committee recently promoted Fabric from incubator to active state, and it is expected to be available in the coming weeks. It is designed to provide a framework for enterprise-grade blockchain networks that can transact at over 1,000 transactions per second.

Safety and security is everything with blockchain, which means blockchain networks are only as safe as the infrastructures on which they reside, hence the underpinning on LinuxONE. In addition, IBM’s High Security Business Network brings an extremely secure Linux infrastructure that, according to IBM, integrates security from the hardware up through the software stack, specifically designed for enterprise blockchains by providing:

  • Protection from insider attacks – helps safeguard entry points on the network and fight insider threats from anyone with system administrator credentials
  • The industry’s highest certified level of isolation for a commercial system- Evaluation Assurance Level certification of EAL5+ is critical in highly regulated industries such as government, financial services and healthcare, to prevent the leakage of information from one party’s environment to another
  • Secure Service Containers – to help protect code throughout the blockchain application and effectively encapsulating the blockchain into a virtual appliance, denying access even to privileged users
  • Tamper-responsive hardware security modules –to protect encrypted data for storage of cryptographic keys. These modules are certified to FIPS 140-2 Level 4, the highest level of security certification available for cryptographic modules
  • A highly auditable operating environment – comprehensive , immutable log data supports forensics, audit, and compliance

IBM also announced today the first commercially available blockchain governance tools, and new open-source developer tools that automate the steps it takes to build with the Hyperledger Fabric, reportedly speeding the process from weeks to days.

The new blockchain governance tools also make it easy to set up a blockchain network and assign roles and levels of visibility from a single dashboard. They help network members set rules, manage membership, and enforce network compliance once the network is up and running.

This seems straightforward enough. Once setup is initiated, members can determine the rules of the blockchain and share consent when new members request to join the network. In addition, the deployment tool assigns each network a Network Trust Rating of 1 to 100. New network members can view this before joining and determine whether or not they can trust the network enough to participate. Organizations can also take steps to improve their Trust Ratings before moving into production.

To make it easier for developers to translate business needs from concept to actual code, IBM Blockchain includes a new open-source developer tools for the Hyperledger Fabric called Fabric Composer. Fabric Composer promises to help users model business networks, create APIs that integrate with the blockchain network and existing systems of record, and quickly build a user interface. Fabric Composer also automates tasks that traditionally could take weeks, allowing developers to complete them in minutes instead.

IBM Blockchain for Hyperledger Fabric v1.0 is now available through a beta program on IBM Bluemix. Hyperledger Fabric also is available on Docker Hub as an IBM-certified image available for download at no cost.

At this point, IBM has over 25 publicly named Blockchain projects underway. They address everything from carbon asset management to consumer digital ID, post trade derivatives processing, last mile shipping, supply chain food safety, provenance, securities lending, and more seemingly are being added nearly weekly.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

Open POWER-Open Compute-POWER9 at Open Compute Summit

March 16, 2017

Bryan Talik, President, OpenPOWER Foundation provides a detailed rundown on the action at the Open Compute  Summit held last week in Santa Clara. After weeks of writing about Cognitive, Machine Learning, Blockchain, and even quantum computing, it is a nice shift to conventional computing platforms that should still be viewed as strategic initiatives.

The OpenPOWER, Open Compute gospel was filling the air in Santa Clara.  As reported, Andy Walsh, Xilinx Director of Strategic Market Development and OpenPOWER Foundation Board member explained, “We very much support open standards and the broad innovation they foster. Open Compute and OpenPOWER are catalysts in enabling new data center capabilities in computing, storage, and networking.”

Added Adam Smith, CEO of Alpha Data:  “Open standards and communities lead to rapid innovation…We are proud to support the latest advances of OpenPOWER accelerator technology featuring Xilinx FPGAs.”

John Zannos, Canonical OpenPOWER Board Chair chimed in: For 2017, the OpenPOWER Board approved four areas of focus that include machine learning/AI, database and analytics, cloud applications and containers. The strategy for 2017 also includes plans to extend OpenPOWER’s reach worldwide and promote technical innovations at various academic labs and in industry. Finally, the group plans to open additional application-oriented workgroups to further technical solutions that benefits specific application areas.

Not surprisingly, some members even see collaboration as the key to satisfying the performance demands that the computing market craves. “The computing industry is at an inflection point between conventional processing and specialized processing,” according to Aaron Sullivan, distinguished engineer at Rackspace. “

To satisfy this shift, Rackspace and Google announced an OCP-OpenPOWER server platform last year, codenamed Zaius and Barreleye G2.  It is based on POWER9. At the OCP Summit, both companies put on a public display of the two products.

This server platform promises to improve the performance, bandwidth, and power consumption demands for emerging applications that leverage machine learning, cognitive systems, real-time analytics and big data platforms. The OCP players plan to continue their work alongside Google, OpenPOWER, OpenCAPI, and other Zaius project members.

Andy Walsh, Xilinx Director of Strategic Market Development and OpenPOWER Foundation Board member explains: “We very much support open standards and the broad innovation they foster. Open Compute and OpenPOWER are catalysts in enabling new data center capabilities in computing, storage, and networking.”

This Zaius and Barreleye G@ server platforms promise to advance the performance, bandwidth and power consumption demands for emerging applications that leverage the latest advanced technologies. These latest technologies are none other than the strategic imperatives–cognitive, machine learning, real-time analytics–IBM has been repeating like a mantra for months.

Open Compute Projects also were displayed at the Summit. Specifically, as reported: Google and Rackspace, published the Zaius specification to Open Compute in October 2016, and had engineers to explain the specification process and to give attendees a starting point for their own server design.

Other Open Compute members, reportedly, also were there. Inventec showed a POWER9 OpenPOWER server based on the Zaius server specification. Mellanox showcased ConnectX-5, its next generation networking adaptor that features 100Gb/s Infiniband and Ethernet. This adaptor supports PCIe Gen4 and CAPI2.0, providing a higher performance and a coherent connection to the POWER9 processor vs. PCIe Gen3.

Others, reported by Talik, included Wistron and E4 Computing, which showcased their newly announced OCP-form factor POWER8 server. Featuring two POWER8 processors, four NVIDIA Tesla P100 GPUs with the NVLink interconnect, and liquid cooling, the new platform represents an ideal OCP-compliant HPC system.

Talik also reported IBM, Xilinx, and Alpha Data showed their line ups of several FPGA adaptors designed for both POWER8 and POWER9. Featuring PCIe Gen3, CAPI1.0 for POWER8 and PCIe Gen4, CAPI2.0 and 25G/s CAPI3.0 for POWER9 these new FPGAs bring acceleration to a whole new level. OpenPOWER member engineers were on-hand to provide information regarding the CAPI SNAP developer and programming framework as well as OpenCAPI.

Not to be left out, Talik reported that IBM showcased products it previously tested and demonstrated: POWER8-based OCP and OpenPOWER Barreleye servers running IBM’s Spectrum Scale software, a full-featured global parallel file system with roots in HPC and now widely adopted in commercial enterprises across all industries for data management at petabyte scale.  Guess compute platform isn’t quite the dirty phrase IBM has been implying for months.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

 

IBM Introduces First Universal Commercial Quantum Computers

March 9, 2017

A few years ago DancingDinosaur first encountered the possibility of quantum computing. It was presented as a real but distant possibility. This is not something I need to consider I thought at the time.  By the time it is available commercially I will be long retired and probably six feet under. Well, I was wrong.

This week IBM unveiled its IBM Q quantum systems. IBM Q will be leading Watson and blockchain to deliver the most advanced set of services on the IBM Cloud platform. There are organizations using it now, and DancingDinosaur continues to be living and working still.

IBM Quantum Computing scientists Hanhee Paik (left) and Sarah Sheldon (right) examine the hardware inside an open dilution fridge at the IBM Q Lab

As IBM explains: While technologies that currently run on classical (or conventional) computers, such as Watson, can help find patterns and insights buried in vast amounts of existing data, quantum computers will deliver solutions to multi-faceted problems where patterns cannot be seen because the data doesn’t exist and the possibilities that you need to explore are too enormous to ever be processed by conventional computers.

Just don’t retire your z or Power system in favor on an IBM Q yet. As IBM explained at a recent briefing on the quantum computing the IBM Q universal quantum computers will be able to do any type of problem that conventional computers do today. However, many of today’s workloads, like on-line transaction processing, data storage, and web serving will continue to run more efficiently on conventional systems. The most powerful quantum systems of the next decade will be a hybrid of quantum computers with conventional computers to control logic and operations on large amounts of data.

The most immediate use cases will involve molecular dynamics, drug design, and materials. The new quantum machine, for example, will allow the healthcare industry to design more effective drugs faster and at less cost and the chemical industry to develop new and improved materials.

Another familiar use case revolves around optimization in finance and manufacturing. The problem here comes down to computers struggling with optimization involving an exponential number of possibilities. Quantum systems, noted IBM, hold the promise of more accurately finding the most profitable investment portfolio in the financial industry, the most efficient use of resources in manufacturing, and optimal routes for logistics in the transportation and retail industries.

To refresh the basics of quantum computing.  The challenges invariably entail exponential scale. You start with 2 basic ideas; 1) the uncertainty principle, which states that attempting to observe a state in general disturbs it while obtaining only partial information about the state. Or 2) where two systems can exist in an entangled state, causing them to behave in ways that cannot be explained by supposing that each has some state of its own. No more zero or 1 only.

The basic unit of quantum computing is the qubit. Today IBM is making available a 5 qubit system, which is pretty small in the overall scheme of things. Large enough, however, to experiment and test some hypotheses; things start getting interesting at 20 qubits. An inflexion point, IBM researchers noted, occurs around 50 qubits. At 50-100 qubits people can begin to do some serious work.

This past week IBM announced three quantum computing advances: the release of a new API for the IBM Quantum Experience that enables developers and programmers to begin building interfaces between IBM’s existing 5 qubit cloud-based quantum computer and conventional computers, without needing a deep background in quantum physics. You can try the 5 qubit quantum system via IBM’s Quantum Experience on Bluemix here.

IBM also released an upgraded simulator on the IBM Quantum Experience that can model circuits with up to 20 qubits. In the first half of 2017, IBM plans to release a full SDK on the IBM Quantum Experience for users to build simple quantum applications and software programs. Only the publically available 5 qubit quantum system with a web-based graphical user interface now; soon to be upgraded to more qubits.

 IBM Research Frontiers Institute allows participants to explore applications for quantum computing in a consortium dedicated to making IBM’s most ambitious research available to its members.

Finally, the IBM Q Early Access Systems allows the purchase of access to a dedicated quantum system hosted and managed by IBM. Initial system is 15+ qubits, with a fast roadmap promised to 50+ qubits.

“IBM has invested over decades to growing the field of quantum computing and we are committed to expanding access to quantum systems and their powerful capabilities for the science and business communities,” said Arvind Krishna, senior vice president of Hybrid Cloud and director for IBM Research. “We believe that quantum computing promises to be the next major technology that has the potential to drive a new era of innovation across industries.”

Are you ready for quantum computing? Try it today on IBM’s Quantum Experience through Bluemix. Let me know how it works for you.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.


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