Cover Image
市場調查報告書

全球虛擬機器 (VM) 市場預測:2015年∼2019年

Worldwide Virtual Machine Forecast, 2015-2019: Strong Virtualization Growth Is Tempered by Cloud and Containers

出版商 IDC 商品編碼 347729
出版日期 內容資訊 英文 14 Pages
訂單完成後即時交付
價格
Back to Top
全球虛擬機器 (VM) 市場預測:2015年∼2019年 Worldwide Virtual Machine Forecast, 2015-2019: Strong Virtualization Growth Is Tempered by Cloud and Containers
出版日期: 2015年12月22日 內容資訊: 英文 14 Pages
簡介

虛擬機器 (VM) 市場,由於私有雲端的引進和下一代雲端本機應用程式的轉變,預計強力成長。

本報告提供全球虛擬機器 (VM) 市場相關調查分析、出貨台數與成長率、虛擬化率等,最新的預測相關的系統性資訊。

IDC的市場預測值

摘要整理

對技術供應商的建議

市場預測

  • VM市場預測

市場背景

  • 推動因素及阻礙因素
    • 推動因素
    • 阻礙因素
  • 重要的市場趨勢
  • 上次預測後的變更

市場定義

調查手法

相關調查

目錄
Product Code: US40315215

This IDC study reviews shipment growth of the server market and presents an updated forecast for the rate of virtualization and IDC's forecast for virtual machine density up to 2019."Virtualization has made its way into almost all datacenter environments, and we continue to expect strong adoption across all server market sectors," says Jorge Vela, research analyst, Servers and Virtualization at IDC. "Our forecast for VMs remains robust, driven by adoption of the private cloud and a shift to next-generation cloud-native apps. However, saturation in mature market and the deployment of competing technologies - including Docker containers and open source cloud system software - will put downward pressure on virtualization license ASPs in the out-years of our forecast."

IDC Market Forecast Figure

Executive Summary

Advice for Technology Suppliers

Market Forecast

  • Virtual Machine Forecast

Market Context

  • Drivers and Inhibitors
    • Drivers
      • Increasing Adoption of Private Cloud
      • Shift to Next-Generation Cloud-Native Applications
    • Inhibitors
      • High Virtualization Rates in Mature Markets
      • Commoditization of Virtualization Software
  • Significant Market Developments
  • Changes from Prior Forecast

Market Definition

  • Physical Server
  • New Server Shipments Virtualized
  • Logical Server Units
  • Virtual Machine Software
  • Server Instance
  • Virtual Machine Density

Methodology

Related Research

Back to Top