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Author: Emad Benjamin
Publisher: Pearson Education
ISBN: 013349120X
Category : Computers
Languages : en
Pages : 272
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Book Description
Virtualizing and Tuning Large-Scale Java Platforms Technical best practices and real-world tips for optimizing enterprise Java applications on VMware vSphere� Enterprises no longer ask, "Can Java be virtualized"? Today, they ask, "Just how large can we scale virtualized Java application platforms, and just how efficiently can we tune them?" Now, the leading expert on Java virtualization answers these questions, offering detailed technical information you can apply in any production or QA/test environment. Emad Benjamin has spent nine years virtualizing VMware's own enterprise Java applications and working with nearly 300 leading VMware customers on projects of all types and sizes--from 100 JVMs to 10,000+, with heaps from 1GB to 360GB, and including massive big-data applications built on clustered JVMs. Reflecting all this experience, he shows you how to successfully size and tune any Java workload. This reference and performance "cookbook" identifies high-value optimization opportunities that apply to physical environments, virtual environments, or both. You learn how to rationalize and scale existing Java infrastructure, modernize architecture for new applications, and systematically benchmark and improve every aspect of virtualized Java performance. Throughout, Benjamin offers real performance studies, specific advice, and "from-the-trenches" insights into monitoring and troubleshooting. Coverage includes --Performance issues associated with large-scale Java platforms, including consolidation, elasticity, and flexibility --Technical considerations arising from theoretical and practical limits of Java platforms --Building horizontal in-memory databases with VMware vFabric SQLFire to improve scalability and response times --Tuning large-scale Java using throughput/parallel GC and Concurrent Mark and Sweep (CMS) techniques --Designing and sizing a new virtualized Java environment --Designing and sizing new large-scale Java platforms when migrating from physical to virtualized deployments --Designing and sizing large-scale Java platforms for latency-sensitive in-memory databases --Real-world performance studies: SQLFire vs. RDBMS, Spring-based Java web apps, vFabric SpringTrader, application tiers, data tiers, and more --Performance differences between ESXi3, 4.1, and 5 --Best-practice considerations for each type of workload: architecture, performance, design, sizing, and high availability --Identifying bottlenecks in the load balancer, web server, Java application server, or DB Server tiers --Advanced vSphere Java performance troubleshooting with esxtop --Performance FAQs: answers to specific questions enterprise customers have asked
Author: Emad Benjamin
Publisher: Pearson Education
ISBN: 013349120X
Category : Computers
Languages : en
Pages : 272
Get Book Here
Book Description
Virtualizing and Tuning Large-Scale Java Platforms Technical best practices and real-world tips for optimizing enterprise Java applications on VMware vSphere� Enterprises no longer ask, "Can Java be virtualized"? Today, they ask, "Just how large can we scale virtualized Java application platforms, and just how efficiently can we tune them?" Now, the leading expert on Java virtualization answers these questions, offering detailed technical information you can apply in any production or QA/test environment. Emad Benjamin has spent nine years virtualizing VMware's own enterprise Java applications and working with nearly 300 leading VMware customers on projects of all types and sizes--from 100 JVMs to 10,000+, with heaps from 1GB to 360GB, and including massive big-data applications built on clustered JVMs. Reflecting all this experience, he shows you how to successfully size and tune any Java workload. This reference and performance "cookbook" identifies high-value optimization opportunities that apply to physical environments, virtual environments, or both. You learn how to rationalize and scale existing Java infrastructure, modernize architecture for new applications, and systematically benchmark and improve every aspect of virtualized Java performance. Throughout, Benjamin offers real performance studies, specific advice, and "from-the-trenches" insights into monitoring and troubleshooting. Coverage includes --Performance issues associated with large-scale Java platforms, including consolidation, elasticity, and flexibility --Technical considerations arising from theoretical and practical limits of Java platforms --Building horizontal in-memory databases with VMware vFabric SQLFire to improve scalability and response times --Tuning large-scale Java using throughput/parallel GC and Concurrent Mark and Sweep (CMS) techniques --Designing and sizing a new virtualized Java environment --Designing and sizing new large-scale Java platforms when migrating from physical to virtualized deployments --Designing and sizing large-scale Java platforms for latency-sensitive in-memory databases --Real-world performance studies: SQLFire vs. RDBMS, Spring-based Java web apps, vFabric SpringTrader, application tiers, data tiers, and more --Performance differences between ESXi3, 4.1, and 5 --Best-practice considerations for each type of workload: architecture, performance, design, sizing, and high availability --Identifying bottlenecks in the load balancer, web server, Java application server, or DB Server tiers --Advanced vSphere Java performance troubleshooting with esxtop --Performance FAQs: answers to specific questions enterprise customers have asked
Author: Michael Corey
Publisher: VMWare Press
ISBN: 0133430154
Category : Computers
Languages : en
Pages : 512
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Book Description
The start-to-finish guide to virtualizing business-critical SQL Server databases on VMware vSphere 5 By virtualizing business-critical databases, enterprises can drive far more value from existing IT infrastructure. But squeezing maximum performance out of a virtualized database instance is an art as much as a science. This indispensable start-to-finish guide brings together all the techniques, tips, and insights you need to succeed. Drawing on unsurpassed personal experience, three leading experts share complete best practices for deploying business-critical database servers in virtualized vSphere 5 environments. They cover the entire project lifecycle, bridging technical and communications gaps between SQL Server and VMware professionals that often make database virtualization more difficult than it needs to be. You’ll find specific guidance for architects and administrators responsible for systems, storage, databases, applications, or VMware virtualization. The authors also present detailed, start-to-finish coverage of performance baselining and testing: all you need to make your virtualized databases as fast as they are cost effective. Although this book focuses on SQL, the authors’ proven guidance for enhancing performance can be leveraged by any IT professional virtualizing a demanding Tier 1 application. Coverage includes • Business cases for database virtualization: consolidation, Database as a Service (DaaS), efficiency, and “SLAs on steroids” • Using the redundancy inherent in virtualization to improve availability • Constructing a careful, conservative implementation plan • Balancing disk, CPU, memory, and network for superior performance • Mastering the five key principles of database storage design • Leveraging memory: SQL MAX, page locking, NUMA, reservations, swapping, large memory pages, and more • Ensuring responsiveness by providing a fast, reliable, low-latency network • Supporting advanced AlwaysOn Failover Cluster Instances and Availability Groups • Baselining physical systems and properly determining resource requirements • Configuring performance tests from beginning to end • Migrating existing SQL Server databases onto a vSphere platform • Avoiding traps and pitfalls in virtualizing production databases • Managing and monitoring virtualized database instances and resources
Author: Emad Benjamin
Publisher:
ISBN: 9780133491425
Category : Java (Computer program language)
Languages : en
Pages :
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Book Description
Author: Priyanka Arora
Publisher: IBM Redbooks
ISBN: 0738435201
Category : Computers
Languages : en
Pages : 164
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Book Description
IBM® WebSphere eXtreme Scale provides a powerful, elastic, high-performance solution for scalability issues through caching and grid technology. This IBM Redbooks® publication shows architects and IT personnel how to leverage the power of WebSphere eXtreme Scale technology to enhance data caching performance in their enterprise networks. This book discusses the scalability challenges and solutions facing today's dynamic business and IT environments. Topics discussed include existing scalability solutions, how WebSphere eXtreme Scale can be integrated into these solutions, and best practices for using WebSphere eXtreme Scale in different environments, including application data caching and database caching. Also included is an in-depth discussion of the WebSphere eXtreme Scale infrastructure, such as grid clients and servers, the grid catalog service, zone support, and scalability sizing considerations. This book focuses on the challenges and benefits of integrating WebSphere eXtreme Scale with other middleware products, including WebSphere® Business Events, WebSphere Commerce, WebSphere Portal, and Rational® JazzTM-based products. Detailed procedures for integrating, configuring, and monitoring WebSphere eXtreme Scale in WebSphere Portal and WebSphere Commerce environments are provided.
Author: Wei-Dong Zhu
Publisher: IBM Redbooks
ISBN: 0738435317
Category : Computers
Languages : en
Pages : 410
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Book Description
IBM® FileNet® Platform is a next-generation, unified enterprise foundation for the integrated IBM FileNet P8 products. It combines the enterprise content management with comprehensive business process management and compliance capabilities. IBM FileNet P8 addresses the most demanding compliance, content, and process management needs for your entire organization. It is a key element in creating an agile, adaptable enterprise content management (ECM) environment necessary to support a dynamic organization that must respond quickly to change. In this IBM Redbooks® publication, we provide an overview of IBM FileNet P8 and describe the core component architecture. We also introduce major expansion products that extend IBM FileNet P8 functionality in the areas of content ingestion, content accessing through connectors and federation, the application framework, and discovery and compliance. In this book, we discuss the anatomy of an ECM infrastructure, content event processing, content life cycle, and business processes. This book gives IT architects, IT specialists, and IT Technical Sales a solid understanding of IBM FileNet P8 Platform, its architecture, its functions and extensibility, and its unlimited capabilities.
Author: Jack Shirazi
Publisher: "O'Reilly Media, Inc."
ISBN: 0596003773
Category : Computers
Languages : en
Pages : 588
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Book Description
Java application performance is tied pretty heavily to the underlying Java Virtual Machine, and the new 1.4 version of Java has significant changes that mean previously used performance tips and strategies may no longer work. Significantly revised and expanded, this second edition not only covers Java 1.4, but adds new coverage of JDBC, NIO, Servlets, EJB and JavaServer Pages. Suitable for intermediate and advanced Java developers, this text also covers JDBC, RMI/CORBA, Servlets, JavaServer Pages and custom tag libraries, XML, internationalization, JavaMail, Enterprise JavaBeans and performance tuning. It should be a useful resource for teaching how to create a tuning strategy, how to use profiling tools to understand a program's behaviour, and how to avoid performance penalties from inefficient code, making them more efficient and effective. The result is code that's robust, maintainable and fast.
Author: George Trujillo
Publisher: VMWare Press
ISBN: 0133811131
Category : Computers
Languages : en
Pages : 799
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Book Description
Plan and Implement Hadoop Virtualization for Maximum Performance, Scalability, and Business Agility Enterprises running Hadoop must absorb rapid changes in big data ecosystems, frameworks, products, and workloads. Virtualized approaches can offer important advantages in speed, flexibility, and elasticity. Now, a world-class team of enterprise virtualization and big data experts guide you through the choices, considerations, and tradeoffs surrounding Hadoop virtualization. The authors help you decide whether to virtualize Hadoop, deploy Hadoop in the cloud, or integrate conventional and virtualized approaches in a blended solution. First, Virtualizing Hadoop reviews big data and Hadoop from the standpoint of the virtualization specialist. The authors demystify MapReduce, YARN, and HDFS and guide you through each stage of Hadoop data management. Next, they turn the tables, introducing big data experts to modern virtualization concepts and best practices. Finally, they bring Hadoop and virtualization together, guiding you through the decisions you’ll face in planning, deploying, provisioning, and managing virtualized Hadoop. From security to multitenancy to day-to-day management, you’ll find reliable answers for choosing your best Hadoop strategy and executing it. Coverage includes the following: • Reviewing the frameworks, products, distributions, use cases, and roles associated with Hadoop • Understanding YARN resource management, HDFS storage, and I/O • Designing data ingestion, movement, and organization for modern enterprise data platforms • Defining SQL engine strategies to meet strict SLAs • Considering security, data isolation, and scheduling for multitenant environments • Deploying Hadoop as a service in the cloud • Reviewing the essential concepts, capabilities, and terminology of virtualization • Applying current best practices, guidelines, and key metrics for Hadoop virtualization • Managing multiple Hadoop frameworks and products as one unified system • Virtualizing master and worker nodes to maximize availability and performance • Installing and configuring Linux for a Hadoop environment
Author: Ben Forta
Publisher: Pearson Education
ISBN: 032169449X
Category : Computers
Languages : en
Pages : 953
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Book Description
Written by the best known and most trusted name in the ColdFusion community, Ben Forta, The ColdFusion Web Application Construction Kit is the best-selling ColdFusion series of all time. Volume 3: Advanced Application Development, focuses on application security, scalability and high-availability, and integration with other systems and technologies. The book starts with two sections dedicated specifically to scalability and security, and then focused on extending ColdFusion applications using web technologies, other languages and platforms, and sophisticated integration techniques. Complete coverage of ColdFusion 9 is included in "Volume 1, Getting Started" (0-321-66034-X) and "Volume 2, Application Development" (0-321-67919-9).
Author: Ben Forta
Publisher: Adobe Press
ISBN: 0132701243
Category : Computers
Languages : en
Pages : 1868
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Book Description
The ColdFusion Web Application Construction Kit is the best-selling ColdFusion series of all time—used by more ColdFusion developers to learn the product than any other books. Volume 3, Advanced Application Development introduces advanced ColdFusion features and technologies, including ensuring high availability, security and access control implementations, Java and .NET integration, using feeds and web services, connecting to IM networks, and server OS integration. Complete coverage of ColdFusion 8 starts in Volume 1, Getting Started (ISBN 0-321-51548-X) and Volume 2 Application Development (ISBN 0-321-51546-3).
Author: Ben Wilson
Publisher: Simon and Schuster
ISBN: 1617298719
Category : Computers
Languages : en
Pages : 574
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Book Description
Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you’ll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You’ll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You’ll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author’s extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer. Table of Contents PART 1 AN INTRODUCTION TO MACHINE LEARNING ENGINEERING 1 What is a machine learning engineer? 2 Your data science could use some engineering 3 Before you model: Planning and scoping a project 4 Before you model: Communication and logistics of projects 5 Experimentation in action: Planning and researching an ML project 6 Experimentation in action: Testing and evaluating a project 7 Experimentation in action: Moving from prototype to MVP 8 Experimentation in action: Finalizing an MVP with MLflow and runtime optimization PART 2 PREPARING FOR PRODUCTION: CREATING MAINTAINABLE ML 9 Modularity for ML: Writing testable and legible code 10 Standards of coding and creating maintainable ML code 11 Model measurement and why it’s so important 12 Holding on to your gains by watching for drift 13 ML development hubris PART 3 DEVELOPING PRODUCTION MACHINE LEARNING CODE 14 Writing production code 15 Quality and acceptance testing 16 Production infrastructure
