Hype Cycle for Servers, 2003

Transcription

1 G. Weiss, D. Scott, T. Bittman, C. Claunch, J. Enck, J. Phelps, E. Cowger, I. Brown Strategic Analysis Report 30 May 2003 Hype Cycle for Servers, 2003 Among the important technologies in the server area are those that speed server deployments, manage their use efficiently, and increase scalability through intrasystem parallelism and wide-area "grid" networking methods. Management Summary For those who work with servers, the 1990s were a time to focus on getting the best performance from components such as CPUs, memory and input/output. With the rapid increase of Web server farms and the proliferation of commodity-based servers, IS organizations began demanding better frameworks to manage vertically integrated servers through partitioning and capacity on demand, as well as horizontally scalable farms comprised of racks, clusters and blades. Servers will likely evolve into more-modular constructs that combine the best of both of these worlds. With such a complex mix, the Hype Cycle for Servers displays a rich range of hardware and software technologies with widely varying levels of maturity. The lack of convergence, standards and maturity has benefits and drawbacks for IS organizations. On the positive side, servers can be differentiated across a wider spectrum of capabilities. The downside is that server resource management in increasingly complex horizontal and vertical server deployments leading eventually to commercial grids may progress only in fits and starts as vendors jockeying for leadership position roll out proprietary technologies. Gartner Reproduction of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The reader assumes sole responsibility for the selection of these materials to achieve its intended results. The opinions expressed herein are subject to change without notice.

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3 CONTENTS 1.0 The Hype Cycle On the Rise Mission-Critical Linux Service Governor Policy-Based Management At the Peak Mixed Workload Management (Windows) Modular Computing Fabrics Commercial Grids Server Provisioning Opteron (AMD64) Software Partitioning (Non-Mainframe) Sliding Into the Trough Sci/Tech Grids Mixed Workload Management (Unix) CPU Chip Parallelism Climbing the Slope Itanium Processor Family Capacity on Demand (Unix) HPC Clusters Capacity on Demand (Mainframe and Proprietary) SMP/NUMA (Unix/RISC) Entering the Plateau Internal MPP Grids HA/Failover Horizontal Scaling Way SMP/NUMA Conclusion...12 Appendix A:Hype Cycle Definitions...13 Appendix B:Acronym Key May

4 FIGURES Figure 1. Hype Cycle for Servers, May

5 1.0 The Hype Cycle Visibility Server Provisioning Key: Time to Plateau Commercial Grids Modular Computing Fabrics Mixed Workload Mgt. (Windows) Opteron (AMD64) Software Partitioning (Non-Mainframe) Less than two years Twotofiveyears Five to 10 years Policy-Based Mgt. Service Governor Mission-Critical Linux CPU Chip Parallelism Sci/Tech Grids Mixed Workload Mgt. (Unix) Itanium Processor Family HPC Clusters Internal MPP Grids Capacity on Demand (Mf/prop.) Capacity on Demand (Unix) 32+ SMP/NUMA (Unix/RISC) Horizontal Scaling HA/ Failover Way SMP/NUMA As of May 2003 Technology Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Maturity Acronym Key HA HPC MPP NUMA RISC SMP high availability high-performance computing massively parallel processing nonuniform memory access reduced instruction set computer symmetrical multiprocessing Source: Gartner Research (May 2003) Figure 1. Hype Cycle for Servers, On the Rise 2.1 Mission-Critical Linux Definition: High-performance Linux applications in areas where a failure would seriously disrupt operations. Time to Plateau/Adoption Speed: Five to 10 years. Justification for Hype Cycle Position/Adoption Speed: Linux is just emerging from the appliance and infrastructure stage, with little real deployment or experience in critical back-office applications. 30 May

6 Business Impact Areas: Mission-critical applications, such as those involved in customer relationship management, enterprise resource planning and supply chain management. Also affects applications that require scaling beyond current Linux platform capabilities, such as large data warehouses. Analysis by George Weiss 2.2 Service Governor Definition: The technology that assesses business priorities, IT services and user experience. The service governor dynamically optimizes the IT infrastructure to meet business and service goals at the lowest cost. It must be actively aware of the IT service architecture and understand resource consumption and service performance. It must also be aware of available inventory. Time to Plateau/Adoption Speed: Five to 10 years. Justification for Hype Cycle Position/Adoption Speed: The hype has just started in the area of real-time infrastructure. Vendors, offering products such as Hewlett-Packard's Adaptive Infrastructure, Sun Microsystems' N1 and IBM's Autonomic Computing, are making big promises. However, the technology is years away from making those promises reality. Business Impact Areas: Reduced management costs by managing the infrastructure at a higher IT service level. Better use of IT capital as shared capacity models evolve vs. the islands in place today. Increased agility to move IT resources where they are needed based on business priorities. Better quality of service with automated optimization of the IT infrastructure. Analysis by Donna Scott 2.3 Policy-Based Management Definition: Policy-based server management enables server tuning (for example, dynamic reconfiguration, dynamic allocation of resources) based on business policy and service-level agreements. A key prerequisite is management instrumentation to discover and resolve any localized faults that may arise, as well as application programming interfaces (APIs) so that server tuning knobs can be adjusted automatically. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: Instrumentation just starting to be available, but lack of a common management schema is an inhibiting factor. Business Impact Areas: Server components (including the operating system) will be self-aware and able to manage their own availability. APIs will enable future distributed workload managers to dynamically tune server resources to meet business policies and service-level agreements, which is required for a real-time infrastructure. Analysis by Donna Scott 3.0 At the Peak 3.1 Mixed Workload Management (Windows) Definition: The ability to run multiple applications within a single image of an operating system and dynamically allocate appropriate resources to each without affecting the applications. Time to Plateau/Adoption Speed: Five to 10 years. 30 May

7 Justification for Hype Cycle Position/Adoption Speed: Tools are very immature and many applications cannot be combined; major effort will be needed to test applications for compatibility. Business Impact Areas: Consolidating to fewer images could dramatically reduce total cost of ownership for operating systems and improve flexibility. Selected Vendors: Aurema, Hewlett-Packard, IBM, Microsoft and Unisys. Analysis by Thomas Bittman 3.2 Modular Computing Fabrics Definition: Modular computing fabrics support dynamic aggregation and disaggregation of processor, memory and input/output resources into a common framework. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: Fabric standards are not finalized. Granular dynamic input/output assignment is still under construction. Business Impact Areas: Primary advantage is the ability to apply the ideal amount of resources to a given application at any given time. Analysis by John Enck 3.3 Commercial Grids Definition: Grid formed for nonscientific, nontechnical tasks across multiple enterprises to address a single, large-scale purpose. Grids can also be used within one enterprise. The term "grid" is sometimes misused to denote the related technologies of distributed and utility computing. Time to Plateau/Adoption Speed: Five to 10 years. Justification for Hype Cycle Position/Adoption Speed: Growing movement by vendors to call products and long-term visions "grid." Growing confusion over definitions, benefits, maturity and applicability. Little is known about what commercial grid applications might be. Business Impact Areas: New industry models could replace third-party intermediaries for large, multienterprise systems. Joint business opportunities with combined data warehouse and analytics. Distributed computing to increase efficiency and use of IT resources. Some claim grids will transform commercial IT operations. Selected Vendors: Avaki, DataSynapse, IBM, Hewlett-Packard, Platform Computing, Sun Microsystems and Oracle. Analysis by Carl Claunch 3.4 Server Provisioning Definition: A set of emerging tools for configuration management that are capable of image management, discovery of hardware and software assets and their relationships inside and across servers, change and configuration management, and dynamically provisioning servers based on policies. 30 May

8 Justification for Hype Cycle Position/Adoption Speed: The technology is beginning to mature, and solutions are becoming more widely deployed for automated server provisioning and configuration management. Dynamic provisioning based on business policies and service-level agreements is two to five years away. Business Impact Areas: Configuration consistency for higher availability; increased automation for reduced deployment time and labor. Selected Vendors: BladeLogic, Novadigm, Opsware and Sun Microsystems. Analysis by Donna Scott 3.5 Opteron (AMD64) Definition: Advanced Micro Devices' 64-bit processor, designed as an extension to the existing x86 processor. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: Application vendor interest and production deployments are lagging. Business Impact Areas: Provides 64-bit addressability and strong performance for current IA-32 software and ported 64-bit software. Analysis by John Enck 3.6 Software Partitioning (Non-Mainframe) Definition: The ability to configure a single physical system into multiple smaller systems, each capable of running their own version of an operating system via a software layer that controls the physical hardware and assigns resources to the different partitions. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: For Unix only, Hewlett-Packard has a very basic product, allowing no resource sharing. Current Windows product supports only single CPU virtual systems (two-way coming soon); has Microsoft and independent software vendor support issues. Business Impact Areas: Enables computing resource use to be maximized while maintaining isolation among applications. Also enables different levels and types of operating systems and middleware to share resources in a consolidated environment. Analysis by John Phelps and Ed Cowger 4.0 Sliding Into the Trough 4.1 Sci/Tech Grids Definition: Coordinated collection of computing systems from multiple organizations used to solve single problems. This technology also used for internal high-performance computing tasks. 30 May

9 Justification for Hype Cycle Position/Adoption Speed: Well-understood applicability and practices in "big science," but government funding preferences are leading to less-appropriate uses and subsequent disappointments. Business Impact Areas: Lower-cost supercomputers for computationally intensive tasks. Ability to build more powerful systems. Collaboration by pooling computing resources. Increased accuracy of answers. Selected Vendors: Hewlett-Packard, IBM Global Services and United Devices. Analysis by Carl Claunch 4.2 Mixed Workload Management (Unix) Definition: The ability to run multiple applications within a single image of an operating system and dynamically allocate appropriate resources to each without affecting the effective operation of the applications. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: Tools beginning to mature; applications maturing to run without collision. Business Impact Areas: Operating system management is a major expense; consolidating to fewer images could dramatically reduce total cost of ownership and improve flexibility. Selected Vendors: Aurema, Hewlett-Packard, IBM and Sun Microsystems. AnalysisbyTomBittman 4.3 CPU Chip Parallelism Definition: Placement of multiple cores on a single piece of silicon, with each core processing multiple threads simultaneously. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: Will require nanometer geometries and improved multithreading levels. Business Impact Areas: High-performance applications, such as those in some scientific and engineering disciplines, that employ relatively large numbers of processors for supercomputing. Analysis by George Weiss 5.0 Climbing the Slope 5.1 Itanium Processor Family Definition: Intel's 64-bit Explicitly Parallel Instruction Computing (EPIC)-based processor family. Time to Plateau/Adoption Speed: Twotofiveyears. Justification for Hype Cycle Position/Adoption Speed: Application support is slowly building, but more applications and production deployments are needed. Business Impact Areas: Targeted for applications needing large memory or floating point performance. Examples include database products and high performance computing clusters. 30 May

10 Analysis by John Enck 5.2 Capacity on Demand (Unix) Definition: The availability of inactive components (processors, memory, input/output) in systems that can be activated rapidly for failure replacement, permanent or temporary increases in capacity, and disaster recovery. Justification for Hype Cycle Position/Adoption Speed: Rapid deployment of additional capacity with reduced up-front costs. Business Impact Areas: Avoids overconfiguring systems at higher costs to meet unanticipated demands; reduces the need for separate backup systems. Analysis by Ed Cowger 5.3 HPC Clusters Definition: Clusters of small, identical, interconnected computers. By scaling out and splitting a computing task into subtasks that run in parallel, the high-performance computing (HPC) cluster aims to match the throughput of a dedicated monolithic supercomputer. Justification for Hype Cycle Position/Adoption Speed: Cost of the platform and the ability to grow the resource from a few nodes to thousands. Business Impact Areas: Appropriate solution for many technical, scientific or other computing-intensive applications. Analysis by Ian Brown 5.4 Capacity on Demand (Mainframe and Proprietary) Definition: The availability of inactive components (processors, memory, input/output) in systems that can be activated rapidly for failure replacement, permanent or temporary increases in capacity, and disaster recovery. The IBM iseries is included here. Justification for Hype Cycle Position/Adoption Speed: Rapid deployment of additional capacity, with reduced up-front costs. Business Impact Areas: Avoids overconfiguring systems at higher costs to meet unanticipated demands and reduces the need for separate backup systems. Analysis by John Phelps and Ed Cowger SMP/NUMA (Unix/RISC). Definition: Global shared-memory servers made up of "cells," usually consisting of four CPUs and memory, connected to each other and input/output subsystems via an internal crossbar and using directory-based protocols to maintain cache coherency. 30 May

11 Justification for Hype Cycle Position/Adoption Speed: Offers greatest potential for single-system scalability. Business Impact Areas: Enables consolidation of applications, such as databases, and offers the ability to handle more than 5,000 concurrent users. Analysis by Ian Brown 6.0 Entering the Plateau 6.1 Internal MPP Grids Definition: The ability to identify, acquire and use excess computing capacity on distributed clients or servers for parallel processing in a secure, intraenterprise environment. Justification for Hype Cycle Position/Adoption Speed: Less-secure parallel grid computing is mature and well understood. Business Impact Areas: Reduces cost by allowing businesses with technical or scientific workloads to use excess compute cycles rather than maintaining a dedicated supercomputer. Selected Vendors: Globus, Hewlett-Packard, IBM, Platform Computing, Sun Microsystems and United Devices. Analysis by Thomas Bittman 6.2 HA/Failover Definition: The ability of system nodes in a cluster to monitor each other's continued operation. When one processor node fails, the workload is automatically recovered and shifted to other processor nodes without a system administrator's intervention. Justification for Hype Cycle Position/Adoption Speed: HA/failover clusters are mainstream and used in more than 50 percent of large database deployments. Business Impact Areas: Deployed so that critical database servers are not a single point of failure; Reduce unplanned downtime by automating recovery and having "hot" resources available when a server fails; Also used to reduce planned downtime by shifting the workload between the primary and secondary nodes. Selected Vendors: Hewlett-Packard, IBM, Microsoft, Sun Microsystems and Veritas. Analysis by Donna Scott 6.3 Horizontal Scaling Definition: The ability to scale by adding small connected or clustered servers to provide more performance in small incremental units. 30 May

12 Justification for Hype Cycle Position/Adoption Speed: Web servers are commonly deployed in rack-dense configurations. Business Impact Areas: Useful in front-end applications (such as SAP), Web servers and hosting environments, technical computing clusters. Analysis by George Weiss Way SMP/NUMA Definition: Global shared-memory servers made up of "cells," usually consisting of four CPUs and memory, interconnected to each other and input/output subsystems via an internal crossbar and using directory-based protocols to maintain cache coherency. Justification for Hype Cycle Position/Adoption Speed: Proven scalability. Business Impact Areas: Enables consolidation of applications such as databases. Allows support of more than 2,500 concurrent users. Analysis by Ian Brown 7.0 Conclusion The Hype Cycle for Servers shows that component, system and management technologies will require deeper levels of integration into the enterprise. Approximately 60 percent of the server infrastructure have yet to approach the slope of enlightenment. 30 May

13 Appendix A: Hype Cycle Definitions Technology Trigger: A breakthrough, public demonstration, product launch or other event generates significant press and industry interest. Peak of Inflated Expectations: During this phase of overenthusiasm and unrealistic projections, a flurry of well-publicized activity by technology leaders results in some successes, but more failures, as the technology is pushed to its limits. The only enterprises making money are conference organizers and magazine publishers. Trough of Disillusionment: Because the technology does not live up to its overinflated expectations, it rapidly becomes unfashionable. Media interest wanes, except for a few cautionary tales. Slope of Enlightenment: Focused experimentation and solid hard work by an increasingly diverse range of organizations lead to a true understanding of the technology's applicability, risks and benefits. Commercial, off-the-shelf methodologies and tools ease the development process. Plateau of Productivity: The real-world benefits of the technology are demonstrated and accepted. Tools and methodologies are increasingly stable as they enter their second and third generations. The final height of the plateau varies according to whether the technology is broadly applicable or benefits only a niche market. Approximately 30 percent of the technology's target audience has or is adopting the technology as it enters the Plateau. Time to Plateau/Adoption Speed: The time required for the technology to reach the Plateau of Productivity. 30 May

14 Appendix B: Acronym Key API EPIC HPC application programming interface Explicitly Parallel Instruction Computing high-performance clusters 30 May