Published: 06 November 1998
Analyst(s): Bruce Guptill, Tom Berg, Ken Bergstrom, Bill Redman
Until the 1990s, the world of data-center technology has been driven primarily by hardware vendors. The purchase of the machine was the first order of business; the software to run the machine was installed; and, people were trained to operate it. This paradigm influenced the way IT budgets were established, data centers were built, applications developed, IS organizations staffed and how services eventually were charged back to the lines of business. During the past three to five years, GartnerMeasurement has seen substantial movement toward converging technologies, especially in the mainframe vs. midrange arenas. The advent of less-expensive, more-powerful, yet smaller mainframes with CMOS (complementary metal-oxide semiconductor) chips and the promised scalability of Unix have been driving the forces behind this movement. Other drivers have been corporate pressures for staffing reductions and the obvious economies of scale possible by centralizing operations for the management of diverse technology platforms. The traditional mainframe data center was a haven of security for operations managers. Tried-and-true methods of managing diverse application environments in a homogeneous architecture, coupled with other key management functions (e.g., storage management, capacity planning and performance levels), gave those managers confidence to be able to report performance proficiency. Another part of the traditional data center managed the centralized midrange servers. At the same time, business units began to see the productivity enhancements and cost-savings potential by moving applications away from the mainframe. Those platforms began as file-and-print servers, workgroup applications platforms and delivery engines for electronic mail. They now are relied on to deliver more-critical business functions. As the number of those distributed platforms grew, business units began pushing them back to the data center to be managed; and the role of the traditional data...
©2020 Gartner, Inc. and/or its affiliates.
All rights reserved.
Gartner is a registered trademark of Gartner, Inc. and its affiliates.
This publication may not be reproduced or distributed in any form without Gartner’s prior written permission.
It consists of the opinions of Gartner’s research organization, which should not be construed as statements of fact.
While the information contained in this publication has been obtained from sources believed to be reliable, Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information.
Although Gartner research may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such.
Your access and use of this publication are governed by Gartner’s Usage Policy.
Gartner prides itself on its reputation for independence and objectivity.
Its research is produced independently by its research organization without input or influence from any third party.
For further information, see
Guiding Principles on Independence and Objectivity.