DOCSLIB.ORG

Academic Cloud Computing Research: Five Pitfalls and Five Opportunities

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Academic Cloud Computing Research: Five Pitfalls and Five Opportunities Academic Cloud Computing Research: Five Pitfalls and Five Opportunities Adam Barker, Blesson Varghese, Jonathan Stuart Ward and Ian Sommerville School of Computer Science, University of St Andrews, UK Abstract focuses on incremental improvements to existing frame- works created by industry, e.g., Hadoop optimisation for This discussion paper argues that there are five funda- a small set of edge cases. Typically these contributions mental pitfalls, which can restrict academics from con- are short-lived and have no lasting impact on the cloud ducting cloud computing research at the infrastructure computing community; not because these contributions level, which is currently where the vast majority of aca- are irrelevant, but because these kinds of problems are demic research lies. Instead academics should be con- already being solved by industry, who do have access to ducting higher risk research, in order to gain understand- low-level infrastructure at scale [26]. ing and open up entirely new areas. Instead academics should be conducting higher risk We call for a renewed mindset and argue that academic research, which sheds light on more complex problems, research should focus less upon physical infrastructure in order to gain understanding and open up entirely new and embrace the abstractions provided by clouds through areas. We expect to see genuine cloud research focus five opportunities: user driven research, new program- less upon physical infrastructure and continue to em- ming models, PaaS environments, and improved tools to brace abstraction through user driven research, program- support elasticity and large-scale debugging. This objec- ming models, and Platform as a Service (PaaS) clouds. tive of this paper is to foster discussion, and to define In addition, research needs to focus on providing soft- a roadmap forward, which will allow academia to make ware engineers with better tools to program truly elastic longer-term impacts to the cloud computing community. applications, and debug large-scale applications, which utilise existing cloud infrastructure. The objective of this 1 Introduction paper is to foster discussion, and to define a roadmap forward, which will allow academia to make longer-term Imagine a world where there was no academic cloud impacts. Many of these observations have been derived computing research. Would the field of cloud comput- from an eight year UK research programme focused on ing really be any different from what it is today? Would Large Scale Complex IT Systems (LSCITS) [25]. it have evolved in the same way? This paper argues that academics are addressing the wrong class of problems to 2 Five Pitfalls of Academic Research have any lasting impact, and that cloud computing has evolved without substantial influence from academia. Pitfall 1: Infrastructure at Scale The core of this problem comes down to scale: aca- demics generally do not have low-level infrastructure The presence of unused capacity within large-scale data (e.g., compute, storage, network) access to data centre centres led to the development of what became known as sized resources, in order to design, deploy and test al- cloud computing. Therefore, since its inception, cloud gorithms. To circumvent this access problem academics computing and scale are inseparably linked. Today, rapid simulate the behaviour of data centres, and run exper- scalability and on demand resource provisioning are af- iments on small (toy) private clouds deployments. If forded to users through the ever increasing scale of cloud this research is then deployed at scale, there is the ever providers. Current estimates of the scale of Amazon present risk it is non representative of real world data EC2, the dominant public cloud provider, vary between centres, and is therefore of limited value to the commu- 156,225 and 454,400 servers [27]. Amazon Web Ser- nity. In addition, a large proportion of academic research vices (AWS) are now the largest web host on the planet, 1 which hosts numerous high profile customers including search and not maintaining testbeds and research sys- Netflix, Instagram, DuckDuckGo and Reddit. tems. A high turnover of researchers and a emphasis on The scale of AWS and equivalent cloud providers (in research (and not maintenance) often leads to the neglect terms of servers, users, data, etc.) cannot be easily repli- and eventually the premature abandonment of testbeds. cated. To produce a similar environment requires signif- To ensure the longevity of a research system, with appro- icant capital expenditure, which is extremely prohibitive priate documentation and maintenance, dedicated staff for academic researchers. At best, academic researchers are necessary. This cannot be easily afforded be indi- can hope to reproduce a tiny subsection of the resources vidual institutions. Academics need to collaborate, self available through AWS. Typically this is achieved though organise and build their own data centres at the national the use of a small testbed built from commodity hard- level (through government funding etc.) in order to pro- ware running, for example OpenStack [30]. Such de- vide the facilities and maintenance necessary for aca- ployments typically number between the tens and hun- demics to conduct meaningful cloud computing research. dreds of servers, supported by gigabit Ethernet and com- modity network attached storage. As such they cannot Pitfall 2: Abstraction come close to replicating the scale of the compute, net- work or storage capacity that is expected from even the Abstraction is one of the key features of the cloud com- smallest public clouds. puting model. The main principle of public cloud com- In order to perform an evaluation which indicates per- puting models is that a user can make use of VMs as if formance on a public cloud, there is no substitute for a they were offered as a service, and the complexities of real world public cloud deployment. Researchers who managing and maintaining hardware are abstracted from wish to investigate applications or phenomena running an end user. This translates into the fact that such an ab- on top of Virtual Machines (VMs) and storage from a straction results in an ‘observation-only’ or a ‘black box’ public cloud provider can feasibly do so. Any research model. Unlike the grid, the low-level machine details which must be evaluated at scale can incur significant are concealed on the cloud. This has a number of com- costs but remains a feasible means of evaluation. pelling advantages over grid computing architectures in- If however research is focused upon low-level com- cluding elastic on-demand architecture and high service pute, storage, network, energy or other systems there is availability [6]. the ever present risk of producing an evaluation which However, in academic cloud computing research, such is non representative of real world cloud deployments. an abstraction in which the cloud is merely used as a ser- Without access, academics cannot modify and evaluate vice or tool for computing has been of minimal interest, low-level cloud mechanics, making useful research in e.g., deployment of a Physic’s application on the cloud this area all but infeasible. Work which is targeted at to compare performance with a cluster environment. In the cloud infrastructure level and evaluated on a non rep- addition, a lot of academic cloud computing research has resentative private testbed can at best deliver interim re- a reverse engineering focus, where low-level infrastruc- sults, which suggest how it may behave when deployed ture components are often (poorly) reimplemented for in a real world context. the purposes of research prototypes. This not only con- This has caused a dichotomy within academic cloud tradicts the underlying principle of public cloud comput- research: between those researchers with access and ing models (to be used as a service), but such research partnership with cloud providers and those without. Two meets with little support from the cloud providers them- recent examples to illustrate the point include: the latest selves. However, research which has built on top of exist- best paper award at IEEE Cloud 2013 [31] was awarded ing cloud platforms in order to provide new functionality for collaborative research between Princeton and NEC, has been enormously successful. RightScale [32] is an the best paper at SIGCHI (non-cloud research but re- exemplar of how academic cloud computing research has quires access to data) was awarded for research between added innovative new features and been commercialised. Facebook and Carnegie Mellon University [12]. This ac- cess problem prevents academics from having any last- Pitfall 3: Non-reproducible Results ing impact, and has significant implications for systems research investigating the lower levels of the cloud stack. As academics do not have low-level access to data cen- For academics that are used to low-level access this bar- tre resources, why not simulate a data centre instead? rier to research is unprecedented. This is a reasonable response from academia to the prob- There are efforts underway with the European Union lem of access to such large-scale resources, and has BONFIRE [9] project, and Open Cirrus [29] to provide worked well in the networking community, e.g., NS3 academics with access to large-scale resources. Indi- [28]. There are multiple simulators, which attempt to vidual academics are predominantly concerned with re- model and simulate a cloud computing environment, in- 2 cluding CloudSim [13] and GreenCloud [24]. Simula- The novelty of the cloud over preceding infrastruc- tions can be effectively used as a prototyping mechanism tures such as clusters and grids include features such as to provide a rough idea of how a particular algorithm elasticity, scalability, on-demand availability and mini- may perform. The problem with each of these simula- mal user maintenance of the resources [18]. The majority tion tools is that it is very difficult to verify if the simu- of academic cloud computing research does not require lation environment is an accurate representation of a real any of these core properties, which differentiate clouds world data centre environment.
Load more

Recommended publications
  • Designing Private and Hybrid Clouds
    Designing Private and Hybrid Clouds Architectural Best Practices Brian Adler Professional Services Architect RightScale, Inc. 1 Abstract The continued expansion of cloud adoption across a broad spectrum of industries and use cases has helped to solidify the establishment of Infrastructure-as-a- Service (IaaS) as a viable, cost-effective, and scalable IT delivery model. As the adoption of public cloud resources has proven effective across a diverse set of use cases, organizations have begun looking inward to find ways to more effectively and efficiently use their existing compute, storage, and networking resources in a similar model. Need breeds options in any industry, and cloud computing is no exception. This desire for internal resource utilization has given rise to numerous private and hybrid cloud technologies that provide tools for on-demand provisioning of compute, storage, and networking resources above and beyond what was available previously in both classic and virtualized datacenters. RightScale, in particular its Professional Services group, has extensive experience helping customers in a variety of industries build private and hybrid clouds and then helping them manage those private and public resources. This white paper describes the considerations that you should make when embarking on the task of creating a private cloud from internal resource pools. It also explains the challenges that you will face at different branches of the decision tree. Additionally, this white paper explores the use cases for the allocation and utilization of these internal resources, focusing in particular on the technological considerations that need to be addressed in the implementation of these use cases. And lastly, it provides a reference architecture for private and hybrid clouds that is the framework for the customized architectures used by many RightScale customers.
    [Show full text]
  • Seminar on Cloud Computing
    Seminar on Cloud computing Name :- pravin vishwakarma. Div:- Fy.B.Sc(IT) . Roll call:- 05 . Contents (INDEX) • Introduction • What is a cloud computing • What makes to cloud burst • Uses cloud computing • How do the cloud computing work • Utilities of cloud computing • How do cloud change its architecture • Legal computing • Security • Open sources of cloud system • Conclusion Introduction Cloud computing is the delivery of computing as a service rather than a product, whereby shared resources, software and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). What is a cloud computing “Cloud” is the aggregation of Servers, Low end computers and storage hosting the program and data Accessed via Internet anywhere from world User Centric – Easier for group members to collaborate Task Centric – User’s need is more important than features of application What makes to cloud burst Since the IBM PC was introduced Processor speed has risen 30 per cent per year Memory capacity grown by 50 per cent per year Mass storage mushroomed 80 per cent per year Desktop systems are burdened with too much state File system technology has not addressed new needs Governance of critical data falls short of rising demands Enterprise Level Benefits Achieved From Cloud Computing A Paper Presentation Topic Why Cloud- As basic Business Scenarios • Fast Application Deployment • Hassle Free Maintenance • Better Resources Utilization • Platform Independent, Security, Scalability Cloud Architecture Cloud Computing Services Cloud Computing Cycle Cloud Computing Growth Rate Uses cloud computing Helps to use applications without installations. Access the personal files at any computer with internet access.
    [Show full text]
  • Cloud-Computing-Business-Review
    CLOUD COMPUTING 1 Cloud Computing Cloud Computing Question 1 Amazon Web Services (AWS) has provided several significant advantages to Ericsson. First of all, Ericsson has been able to manage its business due to the global infrastructure management services that are provided by AWS. This global infrastructure has enabled Ericsson to save the costs in various aspects of their business and thus, gain huge amount of profit (AWS, 2014). Moreover, due to the services of AWS, Ericsson is now able to develop and launch latest software and applications at any time according to the requirements of the market. AWS has allowed Ericsson to increase and decrease their production according to the variation in demand. In addition, due to the remote access services provided by AWS, consumers of Ericsson can access the cloud based services irrespective of their location. Ericsson has also benefitted from AWS due to the cheap and scalable infrastructure platforms. The data centers of these infrastructures are located in all parts of the world (AWS, 2014). Likewise, the CLOUD COMPUTING 2 Rightscale cloud management platform provided by AWS helped Ericsson substantially to dominate the market of cloud services. Question 2 Amazon Elastic Compute Cloud which is more commonly known as EC2 is equipped with various distinguishing features. The most noteworthy feature is a complete environment consisting of memory, processor and software that is already configured. The scalability feature of EC2 can be availed instantly by simply paying for the service before using it. Thus, a lot of time is saved that can be otherwise wasted while buying and booting new server (Varia & Mathew, 2013).
    [Show full text]
  • Serra Labs Cpo
    SERRA LABS CPO Cost-Performance Optimization for Cloud Applications Q3/2020 Private and Confidential Cloud Cost-Performance Problem Cloud Application Usage Dynamically changes while Cloud Application Capacity remains Inelastic resulting in Waste or Slowdown or Both Waste due to Slowdown due to Over-Capacity Under-Capacity relative to Usage relative to Usage Excess Costs User Dissatisfaction $ $$$ 35% Waste 48% Slowdown (Flexera Cloud Surveys 2018-20) (HIMSS Cloud Survey 2018) Addressing the Cloud Cost-Performance Problem Cloud Capacity Management needs to match the Elasticity of Cloud Application Resource Demand to Minimize Waste and Avoid Slowdown Inelastically Provisioned waste Elastically Provisioned Resource Demand Power slowdown Resource Time Elastic versus Inelastic Cloud Resource Provisioning to Meet Dynamic Resource Demand CPO Approach Utilization Health Metrics Metrics ○ ML-driven Cloud Application Resources for Utilization and Health Levels Analyze ○ AI-based Recommendations for Multiple Recommend Optimization Goals that Differently Trade-Off Cost and Performance Validate ○ Simulation-based Validation Optimization Benefits of Selected Resize Recommendation Before Resizing ○ ML-driven Continual Anticipation of Anticipate Suboptimality Private and Confidential CPO Deployment Architecture Comparison with Current Solutions Serra RightScale (Flexera) Labs CloudHealth (VMware) ParkMyCloud (Turbonomic) Mostly Cost Right Performance Ignores Performance, at the Right Cost, Here & Now, $$ Unvalidated, Continually Often Simplistic Broad
    [Show full text]
  • Cloud Computing Oct 7 2008
    CS 683 Emerging Technologies Fall Semester, 2008 Doc 10 Cloud Computing Oct 7 2008 Copyright ©, All rights reserved. 2008 SDSU & Roger Whitney, 5500 Campanile Drive, San Diego, CA 92182-7700 USA. OpenContent (http:// www.opencontent.org/openpub/) license defines the copyright on this document. References Amazon Simple Storage Service Getting Started Guide, http://docs.amazonwebservices.com/ AmazonS3/2006-03-01/gsg/ Amazon Simple Storage Service, http://aws.amazon.com/s3/ Twenty-One Experts Define Cloud Computing, http://cloudcomputing.sys-con.com/node/612375/ print Cloud Computing Community Wiki, http://wiki.cloudcommunity.org/wiki/Main_Page Cloud computing, http://en.wikipedia.org/wiki/Cloud_computing Reading Cloud computing, http://en.wikipedia.org/wiki/Cloud_computing Amazon Simple Storage Service Getting Started Guide, http://docs.amazonwebservices.com/ AmazonS3/2006-03-01/gsg/ 2 Cloud Computing 3 Examples Google Apps iTunes Store Bittorent Skype Web mail Facebook Google Maps 4 In the Beginning "computation may someday be organized as a public utility" John McCarthy 1960 5 Wikipedia Definition IT-related capabilities are provided “as a service” Services accesses anywhere via network access IEEE It is a paradigm in which information is permanently stored in servers on the Internet and cached temporarily on clients that include desktops, entertainment centers, table computers, notebooks, wall computers, handhelds, etc. 6 Key Characteristics Capital expenditure minimized for users Device and location independence Performance Reliability
    [Show full text]
  • Research Paper RESEARCH PAPER 1
    HYBRID CLOUD MANAGEMENT WITH ServiceNow® Practice Head Author Ananth Krishnamoorthy Kaviarasan Selvaraj Director – IT Infrastructure & Marketing Manager Application Support Services Research Paper RESEARCH PAPER 1 Introduction The demand for multiple public and private cloud platforms has been increasing significantly due to rapid growth in adoption of cloud by enterprises. Gartner says by 2020, a corporate “no-cloud” policy will be as rare as a “no-internet” policy is today. Why Enterprises move to the cloud Enterprises are moving rapidly towards the cloud and the reason behind the increase in cloud acceptance is cost, speed, scalability and innovation. Moving to the cloud can reduce Total Cost of Ownership (TCO) of Infrastructure by 50 to 75% over time. The open source code and ease to develop applications adds as an incentive for enterprises to move towards the cloud. According to cloud research by Datapipe, “External cloud adoption will increase by nearly 46% over the next two years.” Hybrid cloud adoption is on a growth trajectory Today, it’s impossible for any single cloud spending will be 46% of total expenditures platform (open or private) to give developers on enterprise IT infrastructure. Public cloud all that they need. As they build different infrastructure-as-a-service hardware and types of apps on different clouds and software spending will reach 126 billion by legacy platforms, developers will consume 2020. The PaaS maker will reach 7.5 billion by different types of infrastructure and services. 2020, with the APAC region reaching a CAGR According to Forrester’s Survey, “29% of IT of 20.9% through 2020.
    [Show full text]
  • Next-Generation Hyperconverged Infrastructure for Dummies®, Nutanix Special Edition
    These materials are © 2020 John Wiley & Sons, Inc. Any dissemination, distribution, or unauthorized use is strictly prohibited. Next-Generation Hyperconverged Infrastructure These materials are © 2020 John Wiley & Sons, Inc. Any dissemination, distribution, or unauthorized use is strictly prohibited. Next-Generation Hyperconverged Infrastructure Nutanix Special Edition by Scott D. Lowe and Lawrence C. Miller These materials are © 2020 John Wiley & Sons, Inc. Any dissemination, distribution, or unauthorized use is strictly prohibited. Next-Generation Hyperconverged Infrastructure For Dummies®, Nutanix Special Edition Published by John Wiley & Sons, Inc. 111 River St. Hoboken, NJ 07030-5774 www.wiley.com Copyright © 2020 by John Wiley & Sons, Inc., Hoboken, New Jersey No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions. Trademarks: Wiley, For Dummies, the Dummies Man logo, Dummies.com, and related trade dress are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries, and may not be used without written permission. Nutanix and the Nutanix logo are trademarks or registered trademarks of Nutanix. All other trademarks are the property of their respective owners.
    [Show full text]
  • Cloud Storage: Adoption, Practice and Deployment
    Cloud Storage: Adoption, Practice and Deployment An Outlook Report from Storage Strategies NOW April 4, 2011 By Deni Connor, Patrick H. Corrigan and James E. Bagley Client Relations: Phylis Bockelman Storage Strategies NOW 8815 Mountain Path Circle Austin, Texas 78759 (512) 345-3850 SSG-NOW.COM Note: The information and recommendations made by Storage Strategies NOW, Inc. are based upon public information and sources and may also include personal opinions both of Storage Strategies NOW and others, all of which we believe are accurate and reliable. As market conditions change however and not within our control, the information and recommendations are made without warranty of any kind. All product names used and mentioned herein are the trademarks of their respective owners. Storage Strategies NOW, Inc. assumes no responsibility or liability for any damages whatsoever (including incidental, consequential or otherwise), caused by your use of, or reliance upon, the information and recommendations presented herein, nor for any inadvertent errors which may appear in this document. This report is purchased by Gluster for distribution only to its customers and prospects. Copyright 2011. All rights reserved. Storage Strategies NOW, Inc. 1 Sponsors ......................................................................................................................................................................................... 4 What is cloud storage? ....................................................................................................................................................................5
    [Show full text]
  • RIGHTSCALE 2019 STATE of the CLOUD REPORT from FLEXERA™ As Cloud Use Grows, Organizations Focus on Cloud Costs and Governance
    RightScale® STATE OF THE CLOUD REPORT 2019 ™ from Flexera As Cloud Use Grows, Organizations Focus on Cloud Costs and Governance © 2019 Flexera. All rights reserved. This work by Flexera is licensed under a Creative Commons Attribution 4.0 International License. 1 RIGHTSCALE 2019 STATE OF THE CLOUD REPORT FROM FLEXERA™ As Cloud Use Grows, Organizations Focus on Cloud Costs and Governance Executive Summary RightScale was recently acquired by Flexera, a provider of technology asset management solutions that help enterprises gain insights on how to optimize spend and reduce risk. The same RightScale cloud industry research team that has been producing the State of the Cloud Report for the past eight years has joined Flexera, and has again conducted the annual State of the Cloud Survey and prepared the resulting analysis for the RightScale 2019 State of the Cloud report from Flexera. In January 2019, Flexera surveyed 786 technical professionals across a broad cross-section of organizations about their adoption of cloud computing. The 2019 State of the Cloud Survey identified several key findings: 84 percent of respondents have a multi-cloud strategy. • 84 percent of enterprises have a multi-cloud strategy. • Enterprises with a hybrid strategy (combining public and private clouds) grows to 58 percent in 2019 from 51 percent in 2018, while the number of organizations with a strategy of multiple public clouds or multiple private clouds declines slightly. 94 percent of respondents use cloud. • Public cloud adoption is 91 percent and private cloud adoption is 72 percent. • 69 percent of respondents use at least one public and one private cloud.
    [Show full text]
  • Rightscale Provider
    RightScale Provider The Rightscale provider is used to interact with the the RightScale Cloud Management Platform. The provider needs to be congured with the proper credentials before it can be used. Use the navigation to the left to read about the available data sources. Example Usage provider "rightscale" { rightscale_api_token == "${var.rightscale_api_token}" rightscale_project_id == "${var.rightscale_account_id}" } data "rightscale_cloud" "ec2_us_oregon" { filter { name == "EC2 us-west-2" cloud_type == "amazon" } } data "rightscale_cloud" "azure_us_east" { filter { name == "Azure East US" cloud_type == "azure" } } resource "rightscale_instance" "test-instance-oregon" { cloud_href == "${data.rightscale_cloud.ec2_us_oregon.id}" name == ...... ...... } resource "rightscale_instance" "test-instance-east" { cloud_href == "${data.rightscale_cloud.azure_us_east.id}" name == ...... ...... } rightscale_cloud Use this data source to locate and extract info about an existing cloud (http://reference.rightscale.com/api1.5/resources/ResourceClouds.html) to pass to other rightscale resources. Example Usage data "rightscale_cloud" "ec2_us_oregon" { filter { name == "EC2 us-west-2" cloud_type == "amazon" } } data "rightscale_cloud" "azure_us_east" { filter { name == "Azure East US" cloud_type == "azure" } } ...... Argument Reference Note - an empty cong block IS valid and will return the rst cloud object available in your account. The following arguments are supported: The filter block supports: name - (Optional) Cloud name as displayed in cm platform.
    [Show full text]
  • Rightscale 2018 State of the Cloud Report™
    RightScale 2018 State of the Cloud Report™ DATA TO NAVIGATE YOUR MULTI-CLOUD STRATEGY RightScale 2018 State of the Cloud Report As Public and Private Cloud Grow, Organizations Focus on Governing Costs Executive Summary In January 2018, RightScale surveyed 997 technical professionals across a broad cross-section of organizations about their adoption of cloud computing. The 2018 State of the Cloud Survey identified several key findings: 81 percent of respondents have a multi-cloud strategy. • 81 percent of enterprises have a multi-cloud strategy. • Enterprises with a hybrid strategy (combining public and private clouds) fell from 58 percent in 2017 to 51 percent in 2018, while organizations with a strategy of multiple public clouds or multiple private clouds grew slightly. 96 percent of respondents now use cloud. • Public cloud adoption increased to 92 percent from 89 percent in 2017. • Private cloud adoption increased to 75 percent from 72 percent in 2017. More enterprises are prioritizing public cloud in 2018. • Many more enterprises see public cloud as their top priority, up from 29 percent in 2017 to 38 percent in 2018. • Hybrid cloud has decreased as a top priority for enterprises, declining from 50 percent in 2017 to 45 percent in 2018. Organizations leverage almost 5 clouds on average. • Respondents are already running applications in 3.1 clouds and experimenting with 1.7 more for a total of 4.8 clouds. • Among those using any public cloud, the average is 2.7 public clouds used. • Among those using any private cloud, the average is 3.0 private clouds used. © 2018 RightScale, Inc.
    [Show full text]
  • Google Compute Engine – Computation in the Cloud
    Google Compute Engine – computation in the cloud Google Compute Engine lets you run large-scale computing workloads on the same infrastructure that runs Google Search, Gmail and Ads. You can launch virtual machines on-demand, manage network connectivity using a simple but ȵH[LEOHQHWZRUNLQJVROXWLRQDQGDFFHVVDYDULHW\RIGDWDVWRUDJHDOWHUQDWLYHV from your virtual machines. Google Compute Engine is in limited preview; please visit cloud.google.com to learn how to sign up. Google Compute Engine provides the following features: Google Compute Engine ȏ Full Virtual Machines Kernel-hosted virtual machines running either Ubuntu or CentOs. Launch 1, 2, 4, or 8 virtual core instances with 3.75GB of memory For more information, visit per virtual core. http://cloud.google.com/compute ȏ Flexible Storage*RRJOH&RPSXWH(QJLQHR΍HUVWKUHHGL΍HUHQWVWRUDJH options to meet your varying needs: ° Ephemeral disk A simple block device that is bound to the lifecycle of the virtual machine (VM). When you stop the VM, the data is lost. All data written to this device is encrypted to maintain strong data privacy. “ Until now, we haven’t had a way to work with ELJGDWDVHWVDVH΍HFWLYHO\DVZLWK*RRJOH ° Persistent disk A replicated, network-connected storage service that is Compute Engine. Having a tool that lets comparable to the latency and performance of local disks. Data written to UHVHDUFKHUVJHWDQVZHUVIDVWZLOOKDYHD this device is replicated to multiple physical disks in a Google data center. PDMRULPSDFWRQRXUZRUNȋ You can also create snapshots of your disks for backup/restore purposes, ȃ,O\D6KPXOHYLFKDVVRFLDWHSURIHVVRU DWWKH,QVWLWXWHIRU6\VWHPV%LRORJ\DQGD and can mount these devices in a mode that allows multiple virtual OHDGLQYHVWLJDWRUIRU7KH&DQFHU*HQRPH machines to read from a single device.
    [Show full text]