Ibm Reference Architecture For High Performance Data And Ai In Healthcare And Life Sciences

Author : Dino Quintero,Frank N. Lee,IBM Redbooks
Publisher : IBM Redbooks
Page : 88 pages
File Size : 47,6 Mb
Release : 2019-09-08
Category : Computers
ISBN : 9780738456904

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IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences by Dino Quintero,Frank N. Lee,IBM Redbooks Pdf

This IBM® Redpaper publication provides an update to the original description of IBM Reference Architecture for Genomics. This paper expands the reference architecture to cover all of the major vertical areas of healthcare and life sciences industries, such as genomics, imaging, and clinical and translational research. The architecture was renamed IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences to reflect the fact that it incorporates key building blocks for high-performance computing (HPC) and software-defined storage, and that it supports an expanding infrastructure of leading industry partners, platforms, and frameworks. The reference architecture defines a highly flexible, scalable, and cost-effective platform for accessing, managing, storing, sharing, integrating, and analyzing big data, which can be deployed on-premises, in the cloud, or as a hybrid of the two. IT organizations can use the reference architecture as a high-level guide for overcoming data management challenges and processing bottlenecks that are frequently encountered in personalized healthcare initiatives, and in compute-intensive and data-intensive biomedical workloads. This reference architecture also provides a framework and context for modern healthcare and life sciences institutions to adopt cutting-edge technologies, such as cognitive life sciences solutions, machine learning and deep learning, Spark for analytics, and cloud computing. To illustrate these points, this paper includes case studies describing how clients and IBM Business Partners alike used the reference architecture in the deployments of demanding infrastructures for precision medicine. This publication targets technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing life sciences solutions and support.

Author : Dino Quintero,Frank N. Lee
Publisher : Unknown
Page : 128 pages
File Size : 40,6 Mb
Release : 2019
Category : Artificial intelligence
ISBN : OCLC:1123174446

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IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences by Dino Quintero,Frank N. Lee Pdf

Author : Elgar Fleisch,Christoph Franz,Andreas Herrmann
Publisher : Emerald Group Publishing
Page : 224 pages
File Size : 48,9 Mb
Release : 2021-03-22
Category : Business & Economics
ISBN : 9781787566750

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The Digital Pill by Elgar Fleisch,Christoph Franz,Andreas Herrmann Pdf

The Digital Pill reflects on apps and digital projects launched by pharmaceutical companies in recent years, as well as the first accreditations for digital pills already issued by recognised regulators. The Digital Pill is essential reading for anyone working in, engaged with or interested in understanding the e-health community.

Author : Joseph Dain,Abeer Selim,Anil Patil,Christopher Vollmar,Flavio de Rezende,Frank Greco,Frank N. Lee,Isom Crawford Jr.,Ivaylo B. Bozhinov,Joanna Wong,Joshua Blumert,Larry Coyne,IBM Redbooks
Publisher : IBM Redbooks
Page : 108 pages
File Size : 46,6 Mb
Release : 2020-08-11
Category : Computers
ISBN : 9780738459028

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Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover by Joseph Dain,Abeer Selim,Anil Patil,Christopher Vollmar,Flavio de Rezende,Frank Greco,Frank N. Lee,Isom Crawford Jr.,Ivaylo B. Bozhinov,Joanna Wong,Joshua Blumert,Larry Coyne,IBM Redbooks Pdf

This IBM® Redpaper publication explains how IBM Spectrum® Discover integrates with the IBM Watson® Knowledge Catalog (WKC) component of IBM Cloud® Pak for Data (IBM CP4D) to make the enriched catalog content in IBM Spectrum Discover along with the associated data available in WKC and IBM CP4D. From an end-to-end IBM solution point of view, IBM CP4D and WKC provide state-of-the-art data governance, collaboration, and artificial intelligence (AI) and analytics tools, and IBM Spectrum Discover complements these features by adding support for unstructured data on large-scale file and object storage systems on premises and in the cloud. Many organizations face challenges to manage unstructured data. Some challenges that companies face include: Pinpointing and activating relevant data for large-scale analytics, machine learning (ML) and deep learning (DL) workloads. Lacking the fine-grained visibility that is needed to map data to business priorities. Removing redundant, obsolete, and trivial (ROT) data and identifying data that can be moved to a lower-cost storage tier. Identifying and classifying sensitive data as it relates to various compliance mandates, such as the General Data Privacy Regulation (GDPR), Payment Card Industry Data Security Standards (PCI-DSS), and the Health Information Portability and Accountability Act (HIPAA). This paper describes how IBM Spectrum Discover provides seamless integration of data in IBM Storage with IBM Watson Knowledge Catalog (WKC). Features include: Event-based cataloging and tagging of unstructured data across the enterprise. Automatically inspecting and classifying over 1000 unstructured data types, including genomics and imaging specific file formats. Automatically registering assets with WKC based on IBM Spectrum Discover search and filter criteria, and by using assets in IBM CP4D. Enforcing data governance policies in WKC in IBM CP4D based on insights from IBM Spectrum Discover, and using assets in IBM CP4D. Several in-depth use cases are used that show examples of healthcare, life sciences, and financial services. IBM Spectrum Discover integration with WKC enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of data. The integration improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 54,9 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Author : Joseph Dain,Norman Bogard,Isom Crawford Jr.,Mathias Defiebre,Larry Coyne,IBM Redbooks
Publisher : IBM Redbooks
Page : 152 pages
File Size : 53,9 Mb
Release : 2019-10-01
Category : Computers
ISBN : 9780738457864

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IBM Spectrum Discover: Metadata Management for Deep Insight of Unstructured Storage by Joseph Dain,Norman Bogard,Isom Crawford Jr.,Mathias Defiebre,Larry Coyne,IBM Redbooks Pdf

This IBM® Redpaper publication provides a comprehensive overview of the IBM Spectrum® Discover metadata management software platform. We give a detailed explanation of how the product creates, collects, and analyzes metadata. Several in-depth use cases are used that show examples of analytics, governance, and optimization. We also provide step-by-step information to install and set up the IBM Spectrum Discover trial environment. More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data such as: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.

Author : Dino Quintero,Luis Carlos Cruz,Ricardo Machado Picone,Dusan Smolej,Daniel de Souza Casali,Gheorghe Tudor,Joanna Wong,IBM Redbooks
Publisher : IBM Redbooks
Page : 202 pages
File Size : 53,5 Mb
Release : 2014-09-30
Category : Computers
ISBN : 9780738439471

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IBM Platform Computing Solutions Reference Architectures and Best Practices by Dino Quintero,Luis Carlos Cruz,Ricardo Machado Picone,Dusan Smolej,Daniel de Souza Casali,Gheorghe Tudor,Joanna Wong,IBM Redbooks Pdf

This IBM® Redbooks® publication demonstrates and documents that the combination of IBM System x®, IBM GPFSTM, IBM GPFS-FPO, IBM Platform Symphony®, IBM Platform HPC, IBM Platform LSF®, IBM Platform Cluster Manager Standard Edition, and IBM Platform Cluster Manager Advanced Edition deliver significant value to clients in need of cost-effective, highly scalable, and robust solutions. IBM depth of solutions can help the clients plan a foundation to face challenges in how to manage, maintain, enhance, and provision computing environments to, for example, analyze the growing volumes of data within their organizations. This IBM Redbooks publication addresses topics to educate, reiterate, confirm, and strengthen the widely held opinion of IBM Platform Computing as the systems software platform of choice within an IBM System x environment for deploying and managing environments that help clients solve challenging technical and business problems. This IBM Redbooks publication addresses topics to that help answer customer's complex challenge requirements to manage, maintain, and analyze the growing volumes of data within their organizations and provide expert-level documentation to transfer the how-to-skills to the worldwide support teams. This IBM Redbooks publication is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for delivering cost-effective computing solutions that help optimize business results, product development, and scientific discoveries.

Author : Scott Vetter,Ivaylo B. Bozhinov,Anto A John,Rafael Freitas de Lima,Ahmed.(Mash) Mashhour,James Van Oosten,Fernando Vermelho,Allison White,IBM Redbooks
Publisher : IBM Redbooks
Page : 162 pages
File Size : 43,8 Mb
Release : 2019-04-10
Category : Computers
ISBN : 9780738457512

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AI and Big Data on IBM Power Systems Servers by Scott Vetter,Ivaylo B. Bozhinov,Anto A John,Rafael Freitas de Lima,Ahmed.(Mash) Mashhour,James Van Oosten,Fernando Vermelho,Allison White,IBM Redbooks Pdf

As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.

Author : Hemanth Manda,Sriram Srinivasan,Deepak Rangarao
Publisher : Packt Publishing
Page : 336 pages
File Size : 53,5 Mb
Release : 2021-10-08
Category : Electronic
ISBN : 1800562128

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IBM Cloud Pak for Data by Hemanth Manda,Sriram Srinivasan,Deepak Rangarao Pdf

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 Features: Explore data virtualization by accessing data in real time without moving it Unify the data and AI experience with the integrated end-to-end platform Explore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scale Book 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 Learn: Understand the importance of digital transformations and the role of data and AI platforms Get to grips with data architecture and its relevance in driving AI adoption using IBM's AI Ladder Understand Cloud Pak for Data, its value proposition, capabilities, and unique differentiators Delve into the pricing, packaging, key use cases, and competitors of Cloud Pak for Data Use the Cloud Pak for Data ecosystem with premium IBM and third-party services Discover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVs Who 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.

Author : Dr. Alfio Gliozzo,Chris Ackerson,Rajib Bhattacharya,Addison Goering,Albert Jumba,Seung Yeon Kim,Laksh Krishnamurthy,Thanh Lam,Angelo Littera,Iain McIntosh,Srini Murthy,Marcel Ribas,IBM Redbooks
Publisher : IBM Redbooks
Page : 132 pages
File Size : 43,9 Mb
Release : 2017-06-23
Category : Computers
ISBN : 9780738442648

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Building Cognitive Applications with IBM Watson Services: Volume 1 Getting Started by Dr. Alfio Gliozzo,Chris Ackerson,Rajib Bhattacharya,Addison Goering,Albert Jumba,Seung Yeon Kim,Laksh Krishnamurthy,Thanh Lam,Angelo Littera,Iain McIntosh,Srini Murthy,Marcel Ribas,IBM Redbooks Pdf

The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 1, introduces cognitive computing, its motivating factors, history, and basic concepts. This volume describes the industry landscape for cognitive computing and introduces Watson, the cognitive computing offering from IBM. It also describes the nature of the question-answering (QA) challenge that is represented by the Jeopardy! quiz game and it provides a high-level overview of the QA system architecture (DeepQA), developed for Watson to play the game. This volume charts the evolution of the Watson Developer Cloud, from the initial DeepQA implementation. This book also introduces the concept of domain adaptation and the processes that must be followed to adapt the various Watson services to specific domains.

Author : Vasfi Gucer,Chris de Almeida,Joe Dorio,Israel Feygelman,Max Huber,Michael Knieriemen,Lars Lauber,Jussi Lehtinen,Jaswinder Singh Saini,IBM Redbooks
Publisher : IBM Redbooks
Page : 214 pages
File Size : 43,6 Mb
Release : 2023-06-14
Category : Computers
ISBN : 9780738460130

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IBM Cloud Object Storage System Product Guide by Vasfi Gucer,Chris de Almeida,Joe Dorio,Israel Feygelman,Max Huber,Michael Knieriemen,Lars Lauber,Jussi Lehtinen,Jaswinder Singh Saini,IBM Redbooks Pdf

Object storage is the primary storage solution that is used in the cloud and on-premises solutions as a central storage platform for unstructured data. IBM Cloud Object Storage is a software-defined storage (SDS) platform that breaks down barriers for storing massive amounts of data by optimizing the placement of data on commodity x86 servers across the enterprise. This IBM Redbooks® publication describes the major features, use case scenarios, deployment options, configuration details, initial customization, performance, and scalability considerations of IBM Cloud Object Storage on-premises offering. For more information about the IBM Cloud Object Storage architecture and technology that is behind the product, see IBM Cloud Object Storage Concepts and Architecture , REDP-5537. The target audience for this publication is IBM Cloud Object Storage IT specialists and storage administrators.

Author : Dino Quintero,Bing He,Bruno C. Faria,Alfonso Jara,Chris Parsons,Shota Tsukamoto,Richard Wale,IBM Redbooks
Publisher : IBM Redbooks
Page : 278 pages
File Size : 54,7 Mb
Release : 2019-06-05
Category : Computers
ISBN : 9780738442945

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IBM PowerAI: Deep Learning Unleashed on IBM Power Systems Servers by Dino Quintero,Bing He,Bruno C. Faria,Alfonso Jara,Chris Parsons,Shota Tsukamoto,Richard Wale,IBM Redbooks Pdf

This IBM® Redbooks® publication is a guide about the IBM PowerAI Deep Learning solution. This book provides an introduction to artificial intelligence (AI) and deep learning (DL), IBM PowerAI, and components of IBM PowerAI, deploying IBM PowerAI, guidelines for working with data and creating models, an introduction to IBM SpectrumTM Conductor Deep Learning Impact (DLI), and case scenarios. IBM PowerAI started as a package of software distributions of many of the major DL software frameworks for model training, such as TensorFlow, Caffe, Torch, Theano, and the associated libraries, such as CUDA Deep Neural Network (cuDNN). The IBM PowerAI software is optimized for performance by using the IBM Power SystemsTM servers that are integrated with NVLink. The AI stack foundation starts with servers with accelerators. graphical processing unit (GPU) accelerators are well-suited for the compute-intensive nature of DL training, and servers with the highest CPU to GPU bandwidth, such as IBM Power Systems servers, enable the high-performance data transfer that is required for larger and more complex DL models. This publication targets technical readers, including developers, IT specialists, systems architects, brand specialist, sales team, and anyone looking for a guide about how to understand the IBM PowerAI Deep Learning architecture, framework configuration, application and workload configuration, and user infrastructure.

Author : Larry Coyne,Joe Dain,Eric Forestier,Patrizia Guaitani,Robert Haas,Christopher D. Maestas,Antoine Maille,Tony Pearson,Brian Sherman,Christopher Vollmar,IBM Redbooks
Publisher : IBM Redbooks
Page : 158 pages
File Size : 52,9 Mb
Release : 2018-07-21
Category : Computers
ISBN : 9780738457055

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IBM Software-Defined Storage Guide by Larry Coyne,Joe Dain,Eric Forestier,Patrizia Guaitani,Robert Haas,Christopher D. Maestas,Antoine Maille,Tony Pearson,Brian Sherman,Christopher Vollmar,IBM Redbooks Pdf

Today, new business models in the marketplace coexist with traditional ones and their well-established IT architectures. They generate new business needs and new IT requirements that can only be satisfied by new service models and new technological approaches. These changes are reshaping traditional IT concepts. Cloud in its three main variants (Public, Hybrid, and Private) represents the major and most viable answer to those IT requirements, and software-defined infrastructure (SDI) is its major technological enabler. IBM® technology, with its rich and complete set of storage hardware and software products, supports SDI both in an open standard framework and in other vendors' environments. IBM services are able to deliver solutions to the customers with their extensive knowledge of the topic and the experiences gained in partnership with clients. This IBM RedpaperTM publication focuses on software-defined storage (SDS) and IBM Storage Systems product offerings for software-defined environments (SDEs). It also provides use case examples across various industries that cover different client needs, proposed solutions, and results. This paper can help you to understand current organizational capabilities and challenges, and to identify specific business objectives to be achieved by implementing an SDS solution in your enterprise.

Author : Ivaylo B. Bozhinov,Isom Crawford Jr.,Joseph Dain,Mathias Defiebre,Maxime Deloche,Kiran Ghag,Vasfi Gucer,Xin Liu,Abeer Selim,Gauthier Siri,Christopher Vollmar,IBM Redbooks
Publisher : IBM Redbooks
Page : 170 pages
File Size : 42,7 Mb
Release : 2020-10-19
Category : Computers
ISBN : 9780738459134

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Making Data Smarter with IBM Spectrum Discover: Practical AI Solutions by Ivaylo B. Bozhinov,Isom Crawford Jr.,Joseph Dain,Mathias Defiebre,Maxime Deloche,Kiran Ghag,Vasfi Gucer,Xin Liu,Abeer Selim,Gauthier Siri,Christopher Vollmar,IBM Redbooks Pdf

More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data, such as the following examples: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM® Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on-premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum® Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research. This IBM Redbooks® publication presents several use cases that are focused on artificial intelligence (AI) solutions with IBM Spectrum Discover. This book helps storage administrators and technical specialists plan and implement AI solutions by using IBM Spectrum Discover and several other IBM Storage products.

Author : Maryela Weihrauch,Frank van der Wal,Rafael Toshio Saizaki,Kendrick Ren,Eric Radzinski,Hendrik Mynhard,Benedict Holste,Maria Sueli Almeida,IBM Redbooks
Publisher : IBM Redbooks
Page : 132 pages
File Size : 40,5 Mb
Release : 2021-09-13
Category : Computers
ISBN : 9780738459943

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Integrating Db2 for z/OS Database Changes Into a CI/CD Pipeline by Maryela Weihrauch,Frank van der Wal,Rafael Toshio Saizaki,Kendrick Ren,Eric Radzinski,Hendrik Mynhard,Benedict Holste,Maria Sueli Almeida,IBM Redbooks Pdf

The goal of this IBM® Redbooks® publication is to demonstrate the ability to perform single click automated deployments of multi-platform applications that include IBM Db2 for z/OS database schema changes by using the capabilities of IBM Db2 DevOps Experience for z/OS. Pushing the application and database code changes to a source control management system (SCM) triggers a single CI/CD pipeline execution for application and database changes. Therefore, it mitigates the dependency on the DBA to deploy those database changes in a separate process. At the same time, DBAs can safeguard the integrity of their organization's data by implementing site rules in Db2 DevOps Experience. DBAs define whether a schema change can be approved automatically after all site rules are satisfied or whether it must be approved manually. In this publication, we provide an overview of the CI/CD pipeline architecture in the context of a sample application. We also describe the steps that are relevant to the roles of the DevOps engineer who implements the enterprise CI/CD pipeline, the DBA who is responsible for database code changes in Db2 for z/OS and for defining site rules that ensure quality in production, and the application developer who changes the application code and communicates requirements for changes in the database schema.