This MaxFacts Guidebook describes the three components of IBM's new on demand business model so IT professionals can see the big picture and understand how their businesses can benefit. Pros will come away with a new understanding of how to evolve a current computing infrastructure to achieve the flexibility vital to the emerging on demand business world. Provided is an overview of key building-block product lines such as IBM eServer systems, TotalStorage, Infoprint printers, WebSphere, DB2, Tivoli, and Linux.
The enterprise data center has evolved dramatically in recent years. It has moved from a model that placed multiple data centers closer to users to a more centralized dynamic model. The factors influencing this evolution are varied but can mostly be attributed to regulatory, service level improvement, cost savings, and manageability. Multiple legal issues regarding the security of data housed in the data center have placed security requirements at the forefront of data center architecture. As the cost to operate data centers has increased, architectures have moved towards consolidation of servers and applications in order to better utilize assets and reduce "server sprawl." The more diverse and distributed the data center environment becomes, the more manageability becomes an issue. These factors have led to a trend of data center consolidation and resources on demand using technologies such as virtualization, higher WAN bandwidth technologies, and newer management technologies. The intended audience of this book is network architects and network administrators. In this IBM® Redbooks® publication we discuss the following topics: The current state of the data center network The business drivers making the case for change The unique capabilities and network requirements of system platforms The impact of server and storage consolidation on the data center network The functional overview of the main data center network virtualization and consolidation technologies The new data center network design landscape
Organizations are looking for ways to get more out of their already strained IT infrastructure as they face new technological and economic pressures. They are also trying to satisfy a broad set of users (internal and external to the enterprise) who demand improvements in their quality of service (QoS), regardless of increases in the number of users and applications. Cloud computing offers attractive opportunities to reduce costs, accelerate development, and increase the flexibility of the IT infrastructure, applications, and services. Infrastructure as a service (IaaS) is the typical starting point for most organizations when moving to a cloud computing environment. IaaS can be used for the delivery of resources such as compute, storage, and network services through a self-service portal. With IaaS, IT services are delivered as a subscription service, eliminating up-front costs and driving down ongoing support costs. IBM® has defined the Cloud Computing Reference Architecture (CCRA) based on years of experience of working with customers who have implemented cloud-computing solutions. The IBM CCRA is a blueprint or guide for architecting cloud-computing implementations. This IBM RedguideTM publication highlights the Cloud Enabled Data Center adoption pattern and describes how you can use it to define an IaaS solution. This guide is intended for chief technology officers, data center architects, IT architects, and application architects who want to understand the cloud-computing infrastructure necessary to support their applications and services by using an IaaS solution. It explains the technical and business benefits of a Cloud Enabled Data Center solution. It introduces a Cloud Enabled Data Center maturity model where each maturity level corresponds to an increase in the degree of automation and the cloud-computing capabilities that are available. In addition, this guide describes the architectural framework provided by the IBM CCRA and explains details about the Cloud Enabled Data Center adoption pattern.
This IBM® Redbooks® publication is designed to teach university students and app developers the foundation skills that are required to develop, test, and deploy cloud-based applications on IBM Cloud. It shows the latest features of IBM Cloud for developing cloud applications, enhancing applications by using managed services, and the use of DevOps services to manage applications. This book is used as presentations guide for the IBM Skills Academy track Cloud Application Developer and as preparation material for the IBM professional certification exam IBM Certified Application Developer - Cloud Platform. The primary target audience for this course is university students in undergraduate computer science and computer engineer programs with no previous experience working in cloud environments. However, anyone new to cloud computing or IBM Cloud can also benefit from this course.
Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.
This IBM® RedpaperTM is the second in a series that addresses the performance and capacity considerations of the evolving cloud computing model. The first Redpaper publication (Performance Implications of Cloud Computing, REDP-4875) introduced cloud computing with its various deployment models, support roles, and offerings along with IT performance and capacity implications associated with these deployment models and offerings. In this redpaper, we discuss lessons learned in the two years since the first paper was written. We offer practical guidance about how to select workloads that work best with cloud computing, and about how to address areas, such as performance testing, monitoring, service level agreements, and capacity planning considerations for both single and multi-tenancy environments. We also provide an example of a recent project where cloud computing solved current business needs (such as cost reduction, optimization of infrastructure utilization, and more efficient systems management and reporting capabilities) and how the solution addressed performance and capacity challenges. We conclude with a summary of the lessons learned and a perspective about how cloud computing can affect performance and capacity in the future.
Cloud computing opens a broad range of business opportunities across the computing industry and enables companies in other industries to provide services to their employees, customers, and partners. Cloud computing provides a compelling approach to addressing this opportunity. The IBM® SmartCloudTM for Service Providers portfolio can dramatically lower the business and technical barriers of entry to cloud computing. Companies rely on their business applications and systems as an integral part of their business. They can expand the business value of their applications and systems by using cloud computing to enable delivery of these functions as services. Companies have various options when adopting cloud computing. They can: Use existing service providers to operate services on their behalf. Implement hybrid solutions that extend existing applications through integration with cloud services. Add cloud service hosting capability to their existing facilities. For ecosystem partners, cloud computing provides compelling capabilities that ease deployment and long term management and maintenance. Equally important, cloud computing facilitates a more flexible business and technical environment. This environment can expand, contract, and adapt as services are added, removed, and evolve. The cloud replaces physical activity associated with change and change management by creating a fluid environment that adapts through automation. This IBM RedguideTM publication describes the business and technology choices companies make when entering the cloud service provider space. It introduces various cloud service provider business models and shows how to apply them to your business. This guide introduces the IBM CCRA cloud service provider adoption pattern, providing guidance about the definition, architecture, and deployment of cloud computing environments. Two cloud service provider deployment scenarios are highlighted throughout the guide, and they reflect the two most common starting points for service providers entering the cloud computing marketplace. The guide culminates with details about these deployment scenarios, and showing how they can be deployed today.
This IBM® RedpaperTM publication takes you on a journey that surveys cloud computing to answer several fundamental questions about storage cloud technology. What are storage clouds? How can a storage cloud help solve your current and future data storage business requirements? What can IBM do to help you implement a storage cloud solution that addresses these needs? This paper shows how IBM storage clouds use the extensive cloud computing experience, services, proven technologies, and products of IBM to support a smart storage cloud solution designed for your storage optimization efforts. Clients face many common storage challenges and some have variations that make them unique. It describes various successful client storage cloud implementations and the options that are available to meet your current needs and position you to avoid storage issues in the future. IBM CloudTM Services (IBM Cloud Managed Services® and IBM SoftLayer®) are highlighted as well as the contributions of IBM to OpenStack cloud storage. This paper is intended for anyone who wants to learn about storage clouds and how IBM addresses data storage challenges with smart storage cloud solutions. It is suitable for IBM clients, storage solution integrators, and IBM specialist sales representatives.
Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. - Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment - Real-world case studies include scientific, business, and energy-efficiency considerations
