Ibm Cloud Pak For Data On Ibm Z


Ibm Cloud Pak For Data On Ibm Z
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Ibm Cloud Pak For Data On Ibm Z


Ibm Cloud Pak For Data On Ibm Z
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Author : Jasmeet Bhatia
language : en
Publisher: IBM Redbooks
Release Date : 2023-07-11

Ibm Cloud Pak For Data On Ibm Z written by Jasmeet Bhatia and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-11 with Computers categories.


Most industries are susceptible to fraud, which poses a risk to both businesses and consumers. According to The National Health Care Anti-Fraud Association, health care fraud alone causes the nation around $68 billion annually. This statistic does not include the numerous other industries where fraudulent activities occur daily. In addition, the growing amount of data that enterprises own makes it difficult for them to detect fraud. Businesses can benefit by using an analytical platform to fully integrate their data with artificial intelligence (AI) technology. With IBM Cloud Pak® for Data on IBM Z, enterprises can modernize their data infrastructure, develop, and deploy machine learning (ML) and AI models, and instantiate highly efficient analytics deployment on IBM LinuxONE. Enterprises can create cutting-edge, intelligent, and interactive applications with embedded AI, colocate data with commercial applications, and use AI to make inferences. This IBM Redguide publication presents a high-level overview of IBM Z. It describes IBM Cloud Pak for Data (CP4D) on IBM Z and IBM LinuxONE, the different features that are supported on the platform, and how the associated features can help enterprise customers in building AI and ML models by using core transactional data, which results in decreased latency and increased throughput. This publication highlights real-time CP4D on IBM Z use cases. Real-time Clearing and Settlement Transactions, Trustworthy AI and its Role in Day-To-Day Monitoring, and the Prevention of Retail Crimes are use cases that are described in this publication. Using CP4D on IBM Z and LinuxONE, this publication shows how businesses can implement a highly efficient analytics deployment that minimizes latency, cost inefficiencies, and potential security exposures that are connected with data transportation.



Building A Red Hat Openshift Environment On Ibm Z


Building A Red Hat Openshift Environment On Ibm Z
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Author : Lydia Parziale
language : en
Publisher: IBM Redbooks
Release Date : 2022-08-10

Building A Red Hat Openshift Environment On Ibm Z written by Lydia Parziale and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-10 with Computers categories.


Cybersecurity is the most important arm of defense against cyberattacks. With the recent increase in cyberattacks, corporations must focus on how they are combating these new high-tech threats. When establishing best practices, a corporation must focus on employees' access to specific workspaces and information. IBM Z® focuses on allowing high processing virtual environments while maintaining a high level of security in each workspace. Organizations not only need to adjust their approach to security, but also their approach to IT environments. To meet new customer needs and expectations, organizations must take a more agile approach to their business. IBM® Z allows companies to work with hybrid and multi-cloud environments that allows more ease of use for the user and efficiency overall. Working with IBM Z, organizations can also work with many databases that are included in IBM Cloud Pak® for Data. IBM Cloud Pak for Data allows organizations to make more informed decisions with improved data usage. Along with the improved data usage, organizations can see the effects from working in a Red Hat OpenShift environment. Red Hat OpenShift is compatible across many hardware services and allows the user to run applications in the most efficient manner. The purpose of this IBM Redbooks® publication is to: Introduce IBM Z and LinuxONE platforms and how they work with the Red Hat OpenShift environment and IBMCloud Pak for Data Provide examples and the uses of IBM Z with Cloud Paks for Data that show data gravity, consistent development experience, and consolidation and business resiliency The target audience for this book is IBM Z Technical Specialists, IT Architects, and System Administrators.



Ibm Cloud Pak For Data


Ibm Cloud Pak For Data
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Author : Hemanth Manda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-11-24

Ibm Cloud Pak For Data written by Hemanth Manda and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Computers categories.


Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook Description Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is for This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.



Optimized Inferencing And Integration With Ai On Ibm Zsystems Introduction Methodology And Use Cases


Optimized Inferencing And Integration With Ai On Ibm Zsystems Introduction Methodology And Use Cases
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Author : Makenzie Manna
language : en
Publisher: IBM Redbooks
Release Date : 2022-11-30

Optimized Inferencing And Integration With Ai On Ibm Zsystems Introduction Methodology And Use Cases written by Makenzie Manna and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Computers categories.


In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, and demonstrates how to leverage certain capabilities and components to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16TM. This publication describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS. The benefits that are derived from the solutions also are described in detail, including how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and enables easy integration to deploy on IBM zSystems for optimal inferencing. Thus, allowing enterprises to uncover insights at the transaction-level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM CICS, Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).



Ibm Cloud Pak For Data With Ibm Spectrum Scale Container Native


Ibm Cloud Pak For Data With Ibm Spectrum Scale Container Native
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Author : Gero Schmidt
language : en
Publisher: IBM Redbooks
Release Date : 2021-12-17

Ibm Cloud Pak For Data With Ibm Spectrum Scale Container Native written by Gero Schmidt and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-17 with Computers categories.


This IBM® Redpaper® publication describes configuration guidelines and best practices when IBM Spectrum® Scale Container Native Storage Access is used as a storage provider for IBM Cloud® Pak for Data on Red Hat OpenShift Container Platform. It also provides the steps to install IBM Db2® and several assemblies within IBM Cloud Pak® for Data, including Watson Knowledge Catalog, Watson Studio, IBM DataStage®, Db2 Warehouse, Watson Machine Learning, Watson OpenScale, Data Virtualization, Data Management Console, and Apache Spark. This IBM Redpaper publication was written for IT architects, IT specialists, developers, and others who are interested in installing IBM Cloud Pak for Data with IBM Spectrum Scale Container Native.



Ibm Z Integration Guide For Hybrid Cloud


Ibm Z Integration Guide For Hybrid Cloud
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Author : Nigel Williams
language : en
Publisher: IBM Redbooks
Release Date : 2020-04-11

Ibm Z Integration Guide For Hybrid Cloud written by Nigel Williams and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-11 with Computers categories.


Today, organizations are responding to market demands and regulatory requirements faster than ever by extending their applications and data to new digital applications. This drive to deliver new functions at speed has paved the way for a huge growth in cloud-native applications, hosted in both public and private cloud infrastructures. Leading organizations are now exploiting the best of both worlds by combining their traditional enterprise IT with cloud. This hybrid cloud approach places new requirements on the integration architectures needed to bring these two worlds together. One of the largest providers of application logic and data services in enterprises today is IBM Z, making it a critical service provider in a hybrid cloud architecture. The primary goal of this IBM Redpaper publication is to help IT architects choose between the different application integration architectures that can be used for hybrid integration with IBM Z, including REST APIs, messaging, and event streams.



Ibm Integrated Synchronization Incremental Updates Unleashed


Ibm Integrated Synchronization Incremental Updates Unleashed
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Author : Christian Michel
language : en
Publisher: IBM Redbooks
Release Date : 2021-01-27

Ibm Integrated Synchronization Incremental Updates Unleashed written by Christian Michel and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-27 with Computers categories.


The IBM® Db2® Analytics Accelerator (Accelerator) is a logical extension of Db2 for IBM z/OS® that provides a high-speed query engine that efficiently and cost-effectively runs analytics workloads. The Accelerator is an integrated back-end component of Db2 for z/OS. Together, they provide a hybrid workload-optimized database management system that seamlessly manages queries that are found in transactional workloads to Db2 for z/OS and queries that are found in analytics applications to Accelerator. Each query runs in its optimal environment for maximum speed and cost efficiency. The incremental update function of Db2 Analytics Accelerator for z/OS updates Accelerator-shadow tables continually. Changes to the data in original Db2 for z/OS tables are propagated to the corresponding target tables with a high frequency and a brief delay. Query results from Accelerator are always extracted from recent, close-to-real-time data. An incremental update capability that is called IBM InfoSphere® Change Data Capture (InfoSphere CDC) is provided by IBM InfoSphere Data Replication for z/OS up to Db2 Analytics Accelerator V7.5. Since then, an extra new replication protocol between Db2 for z/OS and Accelerator that is called IBM Integrated Synchronization was introduced. With Db2 Analytics Accelerator V7.5, customers can choose which one to use. IBM Integrated Synchronization is a built-in product feature that you use to set up incremental updates. It does not require InfoSphere CDC, which is bundled with IBM Db2 Analytics Accelerator. In addition, IBM Integrated Synchronization has more advantages: Simplified administration, packaging, upgrades, and support. These items are managed as part of the Db2 for z/OS maintenance stream. Updates are processed quickly. Reduced CPU consumption on the mainframe due to a streamlined, optimized design where most of the processing is done on the Accelerator. This situation provides reduced latency. Uses IBM Z® Integrated Information Processor (zIIP) on Db2 for z/OS, which leads to reduced CPU costs on IBM Z and better overall performance data, such as throughput and synchronized rows per second. On z/OS, the workload to capture the table changes was reduced, and the remainder can be handled by zIIPs. With the introduction of an enterprise-grade Hybrid Transactional Analytics Processing (HTAP) enabler that is also known as the Wait for Data protocol, the integrated low latency protocol is now enabled to support more analytical queries running against the latest committed data. IBM Db2 for z/OS Data Gate simplifies delivering data from IBM Db2 for z/OS to IBM Cloud® Pak® for Data for direct access by new applications. It uses the special-purpose integrated synchronization protocol to maintain data currency with low latency between Db2 for z/OS and dedicated target databases on IBM Cloud Pak for Data.



Singlestore Database On High Performance Ibm Spectrum Scale Filesystem With Red Hat Openshift And Ibm Cloud Pak For Data


Singlestore Database On High Performance Ibm Spectrum Scale Filesystem With Red Hat Openshift And Ibm Cloud Pak For Data
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Author : Nilesh Suryawanshi
language : en
Publisher: IBM Redbooks
Release Date : 2022-09-15

Singlestore Database On High Performance Ibm Spectrum Scale Filesystem With Red Hat Openshift And Ibm Cloud Pak For Data written by Nilesh Suryawanshi and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-15 with Computers categories.


This IBM® blueprint describes the SingleStoreDB that is running on Red Hat OpenShift in a containerized environment. The SingleStoreDB deployment uses the IBM Spectrum® Scale container native access storage class to create persistent volumes (PVs) for the SingleStoreDB pods deployment. This document also describes the process that is used to expand a SingleStoreDB volume on IBM Spectrum Scale and an IBM Spectrum Scale PV on a Red Hat OpenShift cluster for IBM Spectrum Scale to verify that the SingleStoreDB remained intact after the volume is expanded. The procedure to create a sample database that is named stockDB, and the data analytical stats for reading and writing the data also are included. The sample data was captured for comparison statistics for SingleStoreDB that is deployed on the IBM Spectrum Scale Cluster File System and local storage. These comparison statistics emphasize the notable difference between the sample data sets. Finally, this document also explains the procedure that is used to create the same sample database with the unlimited storage feature in SingleStore by using IBM Cloud® Object Storage.



Enabling Ibm Cloud Pak For Multicloud Management To Connect Kubernetes Clusters Using Ibm Secure Gateway


Enabling Ibm Cloud Pak For Multicloud Management To Connect Kubernetes Clusters Using Ibm Secure Gateway
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Author : Michael Bubel
language : en
Publisher: IBM Redbooks
Release Date : 2020-11-20

Enabling Ibm Cloud Pak For Multicloud Management To Connect Kubernetes Clusters Using Ibm Secure Gateway written by Michael Bubel and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-20 with Computers categories.


In today's dynamically changing IT landscape, it is highly likely that a company's cloud strategy spans multiple cloud providers. Such a span is known as the hydrid multi-cloud landscape. The challenges that quickly surface in an IT department's list of responsibilities now encompass managing environments that are running on multiple cloud providers. The traditional IT administrators find themselves using individual dashboards for each of the cloud providers to monitor and manage those environments. In turn, each of the cloud provider's dashboards have their own unique features that require a learning curve to become productive. The traditional IT administrator must now become a specialized hybrid cloud engineer with different hats for each of the cloud providers. This dynamic led to the quick realization of the need for a tool that provides a common dashboard for managing a company's hybrid cloud landscape. IBM® is one such company that quickly recognized this need and used their experience in years of systems management tools created the IBM Cloud® Pak for Multicloud Management. This paper describes the steps that are required to connect a Kubernetes management dashboard that is provided with the IBM Cloud Pak® for Multicloud Management running on an on-premises private cloud to Kubernetes clusters that are running on public clouds. An IBM Cloud service that is called IBM Secure Gateway is at the core of this connection. The procedure to set up the Kubernetes clusters to use the IBM Secure Gateway service also is described this paper.



Deploying A Database Instance In An Ibm Cloud Private Cluster On Ibm Z


Deploying A Database Instance In An Ibm Cloud Private Cluster On Ibm Z
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Author : Christian May
language : en
Publisher: IBM Redbooks
Release Date : 2019-07-29

Deploying A Database Instance In An Ibm Cloud Private Cluster On Ibm Z written by Christian May and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-29 with Computers categories.


This IBM® RedpaperTM publication shows you how to deploy a database instance within a container using an IBM CloudTM Private cluster on IBM Z®. A preinstalled IBM SpectrumTM Scale 5.0.3 cluster file system provides back-end storage for the persistent volumes bound to the database. A container is a standard unit of software that packages code and all its dependencies, so the application runs quickly and reliably from one computing environment to another. By default, containers are ephemeral. However, stateful applications, such as databases, require some type of persistent storage that can survive service restarts or container crashes. IBM provides several products helping organizations build an environment on an IBM Z infrastructure to develop and manage containerized applications, including dynamic provisioning of persistent volumes. As an example for a stateful application, this paper describes how to deploy the relational database MariaDB using a Helm chart. The IBM Spectrum Scale V5.0.3 cluster file system is providing back-end storage for the persistent volumes. This document provides step-by-step guidance regarding how to install and configure the following components: IBM Cloud Private 3.1.2 (including Kubernetes) Docker 18.03.1-ce IBM Storage Enabler for Containers 2.0.0 and 2.1.0 This Redpaper demonstrates how we set up the example for a stateful application in our lab. The paper gives you insights about planning for your implementation. IBM Z server hardware, the IBM Z hypervisor z/VM®, and the IBM Spectrum Scale cluster file system are prerequisites to set up the example environment. The Redpaper is written with the assumption that you have familiarity with and basic knowledge of the software products used in setting up the environment. The intended audience includes the following roles: Storage administrators IT/Cloud administrators Technologists IT specialists