This document outlines the technical foundations behind GigaSpaces XAP and the “secret sauce” behind the product’s unique capabilities, the Space-Based Architecture (SBA).
At time of crisis, the first instinct at many IT organizations is to freeze and do nothing. This paper prescribes exactly the opposite - innovation - as the key to survival. It focuses on the hottest trend in IT cost savings -operating system virtualization software such as VMware, which improves server utilization and reduces the number of servers, dramatically cutting ownership costs. But operating system virtualization is only part of the solution, because the applications and middleware are themselves inefficient and inflexible, wasteful of resources and too complex to scale out over the new virtualized infrastructure. GigaSpaces XAP provides application-level virtualization which solves the problem, improves server utilization even further, and thus generates substantial additional cost savings ¾ over and above the savings already enjoyed by adopters of operating system virtualization.
GigaSpaces' Service Virtualization Framework leverages GigaSpaces' Space-Based Architecture (SBA) to provide all of the components required to implement a full-featured Service Oriented Architecture (i.e., SOA). This document provides an overview of both SBA and SOA and describes how the Service Virtualization Framework, running in a space-based architecture, supports a traditional SOA. The intended audience if software architects and designers.
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Application workload is growing at an increasing pace, making scalability a prime concern of application designers and administrators. In this paper, we define scalability, and show that inherent scalability barriers represent a dead end for today's tier-based business-critical applications. We argue that in order to survive, these applications must achieve linear scalability, and that the only way to do this is to switch from the tier-based model to a new architectural approach. We suggest a novel approach in which applications are partitioned into self-sufficient processing units, and present Space-Based Architecture (SBA) as a practical implementation of this approach. We demonstrate that SBA guarantees both linear scalability and simplicity for designers, developers and administrators - transforming scalability from dead end to open road.
The emergence of powerful and new commodity hardware and the introduction of SOA/Grid architectures tout the promise of achieving true linearly-scalable systems at a lower cost. Unfortunately, these new systems and architectures are not aligned with the existing tier-based model, which lies at the heart of today's middleware and application approaches, and which is by definition centralized and static. In this paper we will introduce a new approach – Space-Based Architecture (SBA) – for transforming existing tier-based applications into linearly and dynamically scalable services.
Most of the transaction processing applications today includes incoming data feeds that are processed by some kind of business logic (depending on the exact application) and a database that stores intermediate data or long term data. This paper describes GigaSpaces Active Cache architecture that use clustered cache with asynchronous data replication into the database to boost the application performance and provide high level of scalability and availability.
This paper describes how GigaSpaces can be integrated specifically in Web Services environments. The first part of this document will clarify the differences and the commonalities between SOA and Web Services. The second part will focus on how the Data Grid architecture enables scalability, performance and resiliency using virtualization techniques in Web Services environments.
Data Grid Caching reduces overheads and boosts performance when accessing data sources. This paper describes the different caching topologies implementation in GigaSpaces, and their common application scenarios.
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This document details the migration process from a typical JEE tier-based application to a full blown Space-Based Architecture implementation, based on GigaSpaces XAP. It is the result of a project carried out by GigaSpaces in 2008, to determine the basis for comparison between GigaSpaces Space-Based Architecture and the standard JEE Tier-Based Architecture. The project was conducted by Grid Dynamics, an independent consulting and engineering company, hired by GigaSpaces for that purpose.
This paper is a brief guide to scaling Spring-based applications. It shows how
to solve well-known problems that crop up when applications begin to scale
out across multiple physical machines - a bottleneck in the data tier, a
bottleneck in the messaging tier, a bottleneck caused by the tight coupling
between business logic, data, and messaging, and a bottleneck caused by
the limited methods that exist today to deploy and provision applications
across multiple computers. We suggest a number of simple yet innovative
steps, which leverage the idea of virtualization to help you release these
bottlenecks, but do not require that you change your business logic code or
otherwise re-work your application. The steps can be performed individually,
as a targeted "cure" for each bottleneck, but together they form a holistic
solution that leverages Space-Based Architecture (SBA) to enable true
linear scalability for your application.
The Amazon Elastic Compute Cloud service provides a better economic model for large-scale applications -- the owner of the application only pays for hardware per usage and on a low-cost basis, while benefiting from the reliability of the Amazon infrastructure. However, running stateful applications in such a distributed environment faces several challenges that hinder performance and scalability. This paper describes a solution for running stateful applications (high-performance data-intensive and transactional) in the Amazon EC2 environment. Section One presents an overview of EC2 and the challenges faced by developers and architects when they need to run high-performance stateful applications in such a distributed environment. It then goes on to review the GigaSpaces solution which enables running such applications on EC2, allowing them to benefit from all of the advantages that EC2 provides. Section Two is a hands-on guide that describes the architecture of a GigaSpaces application on EC2 and provides step-by-step instructions for developing, integrating and deploying stateful applications on the EC2 environment.
This paper describes a comprehensive solution based on Microsoft and GigaSpaces technologies that addresses the fundamental scalability and performance challenge with existing Excel-based applications in Capital Markets. The solution combines the latest Microsoft technologies: Office Excel, Excel Services in Office SharePoint Server 2007, User Defined Functions (UDF), and Windows Compute Cluster Server 2003 (CCS) with the GigaSpaces eXtreme Application Platform (XAP) to deliver unparalleled usability, performance, and scalability. Section One presents an overview of the challenges with existing applications and how the new solution addresses these challenges. Section Two provides a high level overview of the Microsoft and GigaSpaces technologies involved in this solution. Section Three presents the solution and its benefits to the end user, as well as an example of a customer application (trading analysis) that leverages these benefits.
This paper outlines how organizations can gain significant computing optimizations using GigaSpaces solutions running on Sun UltraSPARC T1-based CoolThread T1000/T2000 (Niagara) servers. Conclusions and recommendations are based on the results of scalability and JVM tuning benchmark tests conducted in Sun performance labs using Sun Fire T1000/T2000 servers. The results of the benchmark tests clearly show that the highly parallel processing architectures of GigaSpaces solutions and Sun UltraSPARC T1-based servers are extremely complementary. The benchmark results and conclusions were achieved in close cooperation with the Sun Microsystems Marketing Development Engineering (MDE) division in Israel and California. Special thanks to Sun engineering experts Malcolm Kavalsky, Amit Hurvitz, and Venu Konda.
In the real world the IT fabric of the enterprise has typically been woven over time and often comprises a number of technologies that are loosely integrated by many different techniques: from file transfer through relational databases to socket-based line protocols. Integrating these infrastructures with ?always-on? customer web sites and sales channel feeder systems can be problematic. So-called fault-tolerant features provided by web service and servlet container vendors impose constraints that many applications find difficult to meet. This paper describes a resilient real-world architecture for service-oriented middle tiers based on JavaSpaces technology, which helps applications meet these constraints. The architecture is illustrated in practise by means of a case study of an implementation provided by PSJ Solutions Ltd. for Virgin Mobile, a leading UK-based mobile telecoms provider. The paper shows how using a task-oriented approach to service requests, a robust execution system can be built without significant additional coding overhead. Failures can also be handled systematically and repaired automatically or through operator intervention.
Program Trading is a high-volume, low margin business placing heavy demands on both hardware and software. The business demands low transaction costs but increasingly sophisticated trading information. Reconciling these apparently opposing requirements within existing transaction processing systems stresses these systems to their limits. In this white paper we describe a new architecture that can be deployed across a grid of commodity hardware nodes, providing a scalable and adaptable platform that supports high-volume, high-performance Program Trading. By decoupling the business logic from the mechanics of computation distribution the system is both readily scalable to meet changing business volumes, whilst remaining extendible and adaptable to evolving business landscapes.
Electronic trading continues to change the bond pricing and risk management landscape. Traders need to be able to be able to price, risk manage and respond to 'requests for quotes' in ever wider universes of fixed income instruments in real-time. Coupled with the need to price more instruments the complexity of analytics for corporate, high yield and emerging market debt require additional compute power. In order to meet the ever growing resource needs, a scalable solution for pricing and risk management is needed. The paper introduces the business problem and describes a "Compute Grid" based solution which scales to meet to the growing demands. The challenge the paper addresses is how to distribute what is a relatively low latency problem onto a Grid Architecture using JavaSpaces technology.
