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  • Dans le Cloud computing, un tutoriel pour débutant, traduit par Nicolas vieux et Vincent Viale

    Qu'est-ce que le Cloud computing ? Le Cloud computing est devenu le nouveau mot à la mode tirée en grande partie par le marketing et les offres de services de grands groupes comme Google, IBM et Amazon. Cloud computing est la prochaine étape dans l'évolution d'Internet. Cloud computing fournit le moyen par lequel tout - de la puissance de calcul de l'infrastructure informatique, des applications, des processus d'affaires pour une autoentreprise - peut être livré comme un service où et quand vous en avez besoin.

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  • Collision detection on a 2D hexagonal grid

    - by SundayMonday
    I'm making a casual grid-based 2D iPhone game using Cocos2D. The grid is a "staggered" hex-like grid consisting of uniformly sized and spaced discs. It looks something like this. I've stored the grid in a 2D array. Also I have a concept of "surrounding" grid cells. Namely the six grid cells surrounding a particular cell (except those on the boundries which can have less than six). Anyways I'm testing some collision detection and it's not working out as well as I had planned. Here's how I currently do collision detection for a moving disc that's approaching the stationary group of discs: Calculate ij-coordinates of grid cell closest to moving cell using moving cell's xy-position Get list of surrounding grid cells using ij-coordinates Examine the surrounding cells. If they're all empty then no collision If we have some non-empty surrounding cells then compare the distance between the disc centers to some minimum distance required for a collision If there's a collision then place the moving disc in grid cell ij So this works but not too well. I've considered a potentially simpler brute force approach where I just compare the moving disc to all stationary discs at each step of the game loop. This is probably feasible in terms of performance since the stationary disc count is 300 max. If not then some space-partitioning data structure could be used however that feels too complex. What are some common approaches and best practices to collision detection in a game like this?

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  • Parallel computing in .net

    - by HotTester
    Since the launch of .net 4.0 a new term that has got into lime light is parallel computing. Does parallel computing provide us some benefits or its just another concept or feature. Further is .net really going to utilize it in applications ? Further is parallel computing different from parallel programming ? Kindly throw some light on the issue in perspective of .net and some examples would be helpful. Thanks...

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  • The future of cloud computing? [closed]

    - by Vimvq1987
    As far as I know, cloud computing is growing rapidly. Amazon EC2, Google App Engine, Microsoft Windows Azure...But I can't imagine how cloud computing will change the world. Will cloud computing will play the main role in software industry? Will our data be stored at one place and then can be accessed from any where? Shall we need powerful PCs no more because everything will be processed at "cloud"? Thank you so much

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  • Cloud computing?

    - by Suraj
    I'm writing a report advising on future technologies that a manufacturing company could use. I've highlighted a number of advanced manufacturing technologies such as CAD etc. However, I want to bring cloud computing into the report just to score some extra points. I am not sure how one would bring together cloud computing with the advanced technologies though. Basically what would be the process of integrating these technologies into a cloud computing "environment"? Say the organisation buys a CAD package, how could they make use of cloud computing here?

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  • Open source Distributed computing tool

    - by Prasenjit Chatterjee
    I want to set up distributed computing on my Local Area Network consisting a bunch of PCs. Say for the time being each one has the same OS - Windows 7. Is there any opensource tool available so that I can share the resources of these PCs over the LAN and increase the speed of my applications and the memory space. I know that if its a graphics intensive application then, it is not very practical, because the speed of LAN is much slower than Graphics processors. But I only want to share general applications, some basic softwares, Programming language IDEs etc. Can anyone shed some light on it? Thanks in Advance..

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  • Cloud Computing - Multiple Physical Computers, One Logical Computer

    - by bundini
    I know that you can set up multiple virtual machines per physical computer. I'm wondering if it's possible to make multiple physical computers behave as one logical unit? Fundamentally the way I imagine it working is that you can throw 10 computers into a facility one day. You've got one client that requires the equivalent of two computers worth, and 100 others that eat up the remaining 8. As demands change you're just reallocating logical resources, maybe the 2 computer client now requires a third physical system. You just add it to the cloud, and don't worry about sharding the database, or migrating data over to a new server. Can it work this way? If yes, why would anyone ever do things like hand partition their database servers anymore? Just add more computing resources. You scale horizontally with the hardware, but your server appears to scale vertically. There's no need to modify your application's supporting infrastructure to support multiple databases etc.

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  • cloud computing ? Eucalyptus

    - by neolix
    Hi Greeting!! I want to setup small cloud computing using our old 2 core server system? we are new to cloud system we have google for the same. We are looking host VM's on top any one has done pls share me doc or how to ? we have 50 plus server which we are not using. 2 core each 4GB RAM, 1TB HDD centos is my base os we looking host windows. Right now we can use this server only paravirtualization ignore my english Thanks

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  • Python Tkinter Tix: How to use ScrolledWindow with grid in Tix NoteBook

    - by Sano98
    Hi guys, I'm adding several widgets to a Frame which is located in a tix.NoteBook. When there are too much widgets to fit in the window, I want to use a scrollbar, so I put tix.ScrolledWindow inside that Frame and add my widgets to this ScrolledWindow instead. The problem is that when using the grid() geometry manager, the scrollbar appears, but it is not working (The drag bar occupies the whole scroll bar). from Tkinter import * import Tix class Window: def __init__(self, root): self.labelList = [] self.notebook = Tix.NoteBook(root, ipadx=3, ipady=3) self.notebook.add('sheet_1', label="Sheet 1", underline=0) self.notebook.add('sheet_2', label="Sheet 2", underline=0) self.notebook.add('sheet_3', label="Sheet 3", underline=0) self.notebook.pack() #self.notebook.grid(row=0, column=0) tab1=self.notebook.sheet_1 tab2=self.notebook.sheet_2 tab3=self.notebook.sheet_3 self.myMainContainer = Frame(tab1) self.myMainContainer.pack() #self.myMainContainer.grid(row=0, column=0) scrwin = Tix.ScrolledWindow(self.myMainContainer, scrollbar='y') scrwin.pack() #scrwin.grid(row=0, column=0) self.win = scrwin.window for i in range (100): self.labelList.append((Label(self.win))) self.labelList[-1].config(text= "Bla", relief = SUNKEN) self.labelList[-1].grid(row=i, column=0, sticky=W+E) root = Tix.Tk() myWindow = Window(root) root.mainloop() Whenever I change at least one of the geometry managers from pack() to grid(), the problem occurs. (Actually, I'd prefer using grid() for all containers.) When I don't use the NoteBook widget, the problem does not occur either. The other examples here all seem to rely on pack(). Any ideas? Many thanks, Sano

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  • Extjs - Loading Grid when call

    - by Oxi
    I have form and grid. the user must enter data in form fields then display related records in the grid. I want to implement a search form, e.g: user will type the name and gender of the student, then will get a grid of all students have the same name and gender. So, I use ajax to send form fields value to PHP and then creat a json_encode wich will be used in grid store. I am really not sure if my idea is good. But I haven't found another way to do that. The problem is when I set autoLoad to true in the store, the grid automatically filled with all data - not just what I asked for - So, I understand that I have to set autoLoad to false, but then the result not shown in the grid even it returned successfully in the firebug! I don't know what to do. My View: { xtype: 'panel', layout: "fit", id: 'searchResult', flex: 7, title: '<div style="text-align:center;"/>SearchResultGrid</div>', items: [ { xtype: 'gridpanel', store: 'advSearchStore', id: 'AdvSearch-grid', columns: [ { xtype: 'gridcolumn', dataIndex: 'name', align: 'right', text: 'name' }, { xtype: 'gridcolumn', dataIndex: 'gender', align: 'right', text: 'gender' } ], viewConfig: { id : 'Arr' ,emptyText: 'noResult' }, requires: ['MyApp.PrintSave_toolbar'], dockedItems: [ { xtype: 'PrintSave_tb', dock: 'bottom', } ] } ] }, My Store and Model: Ext.define('AdvSearchPost', { extend: 'Ext.data.Model', proxy: { type: 'ajax', url: 'AdvSearch.php', reader: { type: 'json', root: 'Arr', totalProperty: 'totalCount' } }, fields: [ { name: 'name'}, { name: 'type_and_cargo'} ] }); Ext.create('Ext.data.Store', { pageSize: 10, autoLoad: false, model: 'AdvSearchPost', storeId: 'AdvSearchPost' });

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  • dhtmlxgrid: getting an xml string of grid data

    - by user823527
    The dhtmlxgrid documentation is saying that I should be able to get a string with the grid data with the serialize feature. mygrid.setSerializationLevel(true,true); var myXmlStr = mygrid.serialize(); I'd like to use that feature to get the updated grid data. But I don't get the xml string. Is that feature not available in the open source version? If I could get a csv string, that would also be OK. But I don't get that either. var gridcsv=mygrid.serializeToCSV(); document.getElementById("mytextareax").value = gridcsv; The html information for the grid is: <a href="#" onclick="savegrid();">Save Grid</a> <textarea id="mytextareax"><rows><row id='r1'><cell>index ... </rows></textarea> <div id="mytextarea" style="width:400px; height: 400px;"> </div> <div id="gridbox" style="width:600px; height:270px; background-color:white;"></div> <a href='#alfa' onClick="ser()">Reload grid with another structure</a> <br> The script for creating the grid is: <script> mygrid = new dhtmlXGridObject('gridbox'); mygrid.setImagePath("../../codebase/imgs/"); mygrid.loadXML("../common/grid500.xml"); function ser(){ mygrid.clearAll(true); mygrid.loadXML("../common/gridH3.xml"); } function savegrid(){ alert('save grid'); mygrid.setSerializationLevel(true,true); var myXmlStr = mygrid.serialize(); /* document.getElementById("mytextarea").innerHTML = myXmlStr; */ document.getElementById("mytextareax").value = myXmlStr; alert(myXmlStr); } </script> Is there any way to get the data out of the dhtmlx grid to be able to create my own xml file from it?

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  • Configuration management in support of scientific computing

    - by Sharpie
    For the past few years I have been involved with developing and maintaining a system for forecasting near-shore waves. Our team has just received a significant grant for further development and as a result we are taking the opportunity to refactor many components of the old system. We will also be receiving a new server to run the model and so I am taking this opportunity to consider how we set up the system. Basically, the steps that need to happen are: Some standard packages and libraries such as compilers and databases need to be downloaded and installed. Some custom scientific models need to be downloaded and compiled from source as they are not commonly provided as packages. New users need to be created to manage the databases and run the models. A suite of scripts that manage model-database interaction needs to be checked out from source code control and installed. Crontabs need to be set up to run the scripts at regular intervals in order to generate forecasts. I have been pondering applying tools such as Puppet, Capistrano or Fabric to automate the above steps. It seems perfectly possible to implement most of the above functionality except there are a couple usage cases that I am wondering about: During my preliminary research, I have found few examples and little discussion on how to use these systems to abstract and automate the process of building custom components from source. We may have to deploy on machines that are isolated from the Internet- i.e. all configuration and set up files will have to come in on a USB key that can be inserted into a terminal that can connect to the server that will run the models. I see this as an opportunity to learn a new tool that will help me automate my workflow, but I am unsure which tool I should start with. If any member of the community could suggest a tool that would support the above workflow and the issues specific to scientific computing, I would be very grateful. Our production server will be running Linux, but support for OS X would be a bonus as it would allow the development team to setup test installations outside of VirtualBox.

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  • Configuration management in support of scientific computing

    - by Sharpie
    For the past few years I have been involved with developing and maintaining a system for forecasting near-shore waves. Our team has just received a significant grant for further development and as a result we are taking the opportunity to refactor many components of the old system. We will also be receiving a new server to run the model and so I am taking this opportunity to consider how we set up the system. Basically, the steps that need to happen are: Some standard packages and libraries such as compilers and databases need to be downloaded and installed. Some custom scientific models need to be downloaded and compiled from source as they are not commonly provided as packages. New users need to be created to manage the databases and run the models. A suite of scripts that manage model-database interaction needs to be checked out from source code control and installed. Crontabs need to be set up to run the scripts at regular intervals in order to generate forecasts. I have been pondering applying tools such as Puppet, Capistrano or Fabric to automate the above steps. It seems perfectly possible to implement most of the above functionality except there are a couple usage cases that I am wondering about: During my preliminary research, I have found few examples and little discussion on how to use these systems to abstract and automate the process of building custom components from source. We may have to deploy on machines that are isolated from the Internet- i.e. all configuration and set up files will have to come in on a USB key that can be inserted into a terminal that can connect to the server that will run the models. I see this as an opportunity to learn a new tool that will help me automate my workflow, but I am unsure which tool I should start with. If any member of the community could suggest a tool that would support the above workflow and the issues specific to scientific computing, I would be very grateful. Our production server will be running Linux, but support for OS X would be a bonus as it would allow the development team to setup test installations outside of VirtualBox.

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  • Distributed storage and computing

    - by Tim van Elteren
    Dear Serverfault community, After researching a number of distributed file systems for deployment in a production environment with the main purpose of performing both batch and real-time distributed computing I've identified the following list as potential candidates, mainly on maturity, license and support: Ceph Lustre GlusterFS HDFS FhGFS MooseFS XtreemFS The key properties that our system should exhibit: an open source, liberally licensed, yet production ready, e.g. a mature, reliable, community and commercially supported solution; ability to run on commodity hardware, preferably be designed for it; provide high availability of the data with the most focus on reads; high scalability, so operation over multiple data centres, possibly on a global scale; removal of single points of failure with the use of replication and distribution of (meta-)data, e.g. provide fault-tolerance. The sensitivity points that were identified, and resulted in the following questions, are: transparency to the processing layer / application with respect to data locality, e.g. know where data is physically located on a server level, mainly for resource allocation and fast processing, high performance, how can this be accomplished? Do you from experience know what solutions provide this transparency and to what extent? posix compliance, or conformance, is mentioned on the wiki pages of most of the above listed solutions. The question here mainly is, how relevant is support for the posix standard? Hadoop for example isn't posix compliant by design, what are the pro's and con's? what about the difference between synchronous and asynchronous opeartion of a distributed file system. Though a synchronous distributed file system has the preference because of reliability it also imposes certain limitations with respect to scalability. What would be, from your expertise, the way to go on this? I'm looking forward to your replies. Thanks in advance! :) With kind regards, Tim van Elteren

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  • Big Data – Role of Cloud Computing in Big Data – Day 11 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud in Big Data Story What is Cloud? Cloud is the biggest buzzword around from last few years. Everyone knows about the Cloud and it is extremely well defined online. In this article we will discuss cloud in the context of the Big Data. Cloud computing is a method of providing a shared computing resources to the application which requires dynamic resources. These resources include applications, computing, storage, networking, development and various deployment platforms. The fundamentals of the cloud computing are that it shares pretty much share all the resources and deliver to end users as a service.  Examples of the Cloud Computing and Big Data are Google and Amazon.com. Both have fantastic Big Data offering with the help of the cloud. We will discuss this later in this blog post. There are two different Cloud Deployment Models: 1) The Public Cloud and 2) The Private Cloud Public Cloud Public Cloud is the cloud infrastructure build by commercial providers (Amazon, Rackspace etc.) creates a highly scalable data center that hides the complex infrastructure from the consumer and provides various services. Private Cloud Private Cloud is the cloud infrastructure build by a single organization where they are managing highly scalable data center internally. Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:   Public Cloud Private Cloud Initial cost Typically zero Typically high Running cost Unpredictable Unpredictable Customization Impossible Possible Privacy No (Host has access to the data Yes Single sign-on Impossible Possible Scaling up Easy while within defined limits Laborious but no limits Hybrid Cloud Hybrid Cloud is the cloud infrastructure build with the composition of two or more clouds like public and private cloud. Hybrid cloud gives best of the both the world as it combines multiple cloud deployment models together. Cloud and Big Data – Common Characteristics There are many characteristics of the Cloud Architecture and Cloud Computing which are also essentially important for Big Data as well. They highly overlap and at many places it just makes sense to use the power of both the architecture and build a highly scalable framework. Here is the list of all the characteristics of cloud computing important in Big Data Scalability Elasticity Ad-hoc Resource Pooling Low Cost to Setup Infastructure Pay on Use or Pay as you Go Highly Available Leading Big Data Cloud Providers There are many players in Big Data Cloud but we will list a few of the known players in this list. Amazon Amazon is arguably the most popular Infrastructure as a Service (IaaS) provider. The history of how Amazon started in this business is very interesting. They started out with a massive infrastructure to support their own business. Gradually they figured out that their own resources are underutilized most of the time. They decided to get the maximum out of the resources they have and hence  they launched their Amazon Elastic Compute Cloud (Amazon EC2) service in 2006. Their products have evolved a lot recently and now it is one of their primary business besides their retail selling. Amazon also offers Big Data services understand Amazon Web Services. Here is the list of the included services: Amazon Elastic MapReduce – It processes very high volumes of data Amazon DynammoDB – It is fully managed NoSQL (Not Only SQL) database service Amazon Simple Storage Services (S3) – A web-scale service designed to store and accommodate any amount of data Amazon High Performance Computing – It provides low-tenancy tuned high performance computing cluster Amazon RedShift – It is petabyte scale data warehousing service Google Though Google is known for Search Engine, we all know that it is much more than that. Google Compute Engine – It offers secure, flexible computing from energy efficient data centers Google Big Query – It allows SQL-like queries to run against large datasets Google Prediction API – It is a cloud based machine learning tool Other Players Besides Amazon and Google we also have other players in the Big Data market as well. Microsoft is also attempting Big Data with the Cloud with Microsoft Azure. Additionally Rackspace and NASA together have initiated OpenStack. The goal of Openstack is to provide a massively scaled, multitenant cloud that can run on any hardware. Thing to Watch The cloud based solutions provides a great integration with the Big Data’s story as well it is very economical to implement as well. However, there are few things one should be very careful when deploying Big Data on cloud solutions. Here is a list of a few things to watch: Data Integrity Initial Cost Recurring Cost Performance Data Access Security Location Compliance Every company have different approaches to Big Data and have different rules and regulations. Based on various factors, one can implement their own custom Big Data solution on a cloud. Tomorrow In tomorrow’s blog post we will discuss about various Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Cloud Computing Forces Better Design Practices

    - by Herve Roggero
    Is cloud computing simply different than on premise development, or is cloud computing actually forcing you to create better applications than you normally would? In other words, is cloud computing merely imposing different design principles, or forcing better design principles?  A little while back I got into a discussion with a developer in which I was arguing that cloud computing, and specifically Windows Azure in his case, was forcing developers to adopt better design principles. His opinion was that cloud computing was not yielding better systems; just different systems. In this blog, I will argue that cloud computing does force developers to use better design practices, and hence better applications. So the first thing to define, of course, is the word “better”, in the context of application development. Looking at a few definitions online, better means “superior quality”. As it relates to this discussion then, I stipulate that cloud computing can yield higher quality applications in terms of scalability, everything else being equal. Before going further I need to also outline the difference between performance and scalability. Performance and scalability are two related concepts, but they don’t mean the same thing. Scalability is the measure of system performance given various loads. So when developers design for performance, they usually give higher priority to a given load and tend to optimize for the given load. When developers design for scalability, the actual performance at a given load is not as important; the ability to ensure reasonable performance regardless of the load becomes the objective. This can lead to very different design choices. For example, if your objective is to obtains the fastest response time possible for a service you are building, you may choose the implement a TCP connection that never closes until the client chooses to close the connection (in other words, a tightly coupled service from a connectivity standpoint), and on which a connection session is established for faster processing on the next request (like SQL Server or other database systems for example). If you objective is to scale, you may implement a service that answers to requests without keeping session state, so that server resources are released as quickly as possible, like a REST service for example. This alternate design would likely have a slower response time than the TCP service for any given load, but would continue to function at very large loads because of its inherently loosely coupled design. An example of a REST service is the NO-SQL implementation in the Microsoft cloud called Azure Tables. Now, back to cloud computing… Cloud computing is designed to help you scale your applications, specifically when you use Platform as a Service (PaaS) offerings. However it’s not automatic. You can design a tightly-coupled TCP service as discussed above, and as you can imagine, it probably won’t scale even if you place the service in the cloud because it isn’t using a connection pattern that will allow it to scale [note: I am not implying that all TCP systems do not scale; I am just illustrating the scalability concepts with an imaginary TCP service that isn’t designed to scale for the purpose of this discussion]. The other service, using REST, will have a better chance to scale because, by design, it minimizes resource consumption for individual requests and doesn’t tie a client connection to a specific endpoint (which means you can easily deploy this service to hundreds of machines without much trouble, as long as your pockets are deep enough). The TCP and REST services discussed above are both valid designs; the TCP service is faster and the REST service scales better. So is it fair to say that one service is fundamentally better than the other? No; not unless you need to scale. And if you don’t need to scale, then you don’t need the cloud in the first place. However, it is interesting to note that if you do need to scale, then a loosely coupled system becomes a better design because it can almost always scale better than a tightly-coupled system. And because most applications grow overtime, with an increasing user base, new functional requirements, increased data and so forth, most applications eventually do need to scale. So in my humble opinion, I conclude that a loosely coupled system is not just different than a tightly coupled system; it is a better design, because it will stand the test of time. And in my book, if a system stands the test of time better than another, it is of superior quality. Because cloud computing demands loosely coupled systems so that its underlying service architecture can be leveraged, developers ultimately have no choice but to design loosely coupled systems for the cloud. And because loosely coupled systems are better… … the cloud forces better design practices. My 2 cents.

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  • Podcast Show Notes &ndash; Oracle Coherence and Data Grid Technology - Part 1

    - by Bob Rhubart
    This week’s ArchBeat Podcast program kicks off a three-part series featuring a discussion of Oracle Coherence and data grid technology. Listen to Part 1 The panelists for this discussion are: Cameron Purdy, VP of Development, Oracle Blog | Twitter | LinkedIn | Oracle Mix Aleksandar Seovic, founder and managing director at S4HC Inc. Blog| Twitter | LinkedIn | Oracle Mix | Oracle ACE Profile (Aleks is also the author of  Oracle Coherence 3.5 from Packt Publishing.) John Stouffer, independent consultant, Oracle Applications DBA/Architect Blog |  LinkedIn | Oracle Mix | Oracle ACE Profile Part two will be available on June 23, part 3 on June 30. Coming soon On July 7 the ArchBeat Podcast kicks of a series featuring an open discussion of Architecture and Agility. Stay tuned: RSS   Technorati Tags: oracle,otn,arch2arch,archbeat,coherence,data grid,cameron purdy,aleks seovic del.icio.us Tags: oracle,otn,arch2arch,archbeat,coherence,data grid,cameron purdy,aleks seovic

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  • Cloud Computing = Elasticity * Availability

    - by Herve Roggero
    What is cloud computing? Is hosting the same thing as cloud computing? Are you running a cloud if you already use virtual machines? What is the difference between Infrastructure as a Service (IaaS) and a cloud provider? And the list goes on… these questions keep coming up and all try to fundamentally explain what “cloud” means relative to other concepts. At the risk of over simplification, answering these questions becomes simpler once you understand the primary foundations of cloud computing: Elasticity and Availability.   Elasticity The basic value proposition of cloud computing is to pay as you go, and to pay for what you use. This implies that an application can expand and contract on demand, across all its tiers (presentation layer, services, database, security…).  This also implies that application components can grow independently from each other. So if you need more storage for your database, you should be able to grow that tier without affecting, reconfiguring or changing the other tiers. Basically, cloud applications behave like a sponge; when you add water to a sponge, it grows in size; in the application world, the more customers you add, the more it grows. Pure IaaS providers will provide certain benefits, specifically in terms of operating costs, but an IaaS provider will not help you in making your applications elastic; neither will Virtual Machines. The smallest elasticity unit of an IaaS provider and a Virtual Machine environment is a server (physical or virtual). While adding servers in a datacenter helps in achieving scale, it is hardly enough. The application has yet to use this hardware.  If the process of adding computing resources is not transparent to the application, the application is not elastic.   As you can see from the above description, designing for the cloud is not about more servers; it is about designing an application for elasticity regardless of the underlying server farm.   Availability The fact of the matter is that making applications highly available is hard. It requires highly specialized tools and trained staff. On top of it, it's expensive. Many companies are required to run multiple data centers due to high availability requirements. In some organizations, some data centers are simply on standby, waiting to be used in a case of a failover. Other organizations are able to achieve a certain level of success with active/active data centers, in which all available data centers serve incoming user requests. While achieving high availability for services is relatively simple, establishing a highly available database farm is far more complex. In fact it is so complex that many companies establish yearly tests to validate failover procedures.   To a certain degree certain IaaS provides can assist with complex disaster recovery planning and setting up data centers that can achieve successful failover. However the burden is still on the corporation to manage and maintain such an environment, including regular hardware and software upgrades. Cloud computing on the other hand removes most of the disaster recovery requirements by hiding many of the underlying complexities.   Cloud Providers A cloud provider is an infrastructure provider offering additional tools to achieve application elasticity and availability that are not usually available on-premise. For example Microsoft Azure provides a simple configuration screen that makes it possible to run 1 or 100 web sites by clicking a button or two on a screen (simplifying provisioning), and soon SQL Azure will offer Data Federation to allow database sharding (which allows you to scale the database tier seamlessly and automatically). Other cloud providers offer certain features that are not available on-premise as well, such as the Amazon SC3 (Simple Storage Service) which gives you virtually unlimited storage capabilities for simple data stores, which is somewhat equivalent to the Microsoft Azure Table offering (offering a server-independent data storage model). Unlike IaaS providers, cloud providers give you the necessary tools to adopt elasticity as part of your application architecture.    Some cloud providers offer built-in high availability that get you out of the business of configuring clustered solutions, or running multiple data centers. Some cloud providers will give you more control (which puts some of that burden back on the customers' shoulder) and others will tend to make high availability totally transparent. For example, SQL Azure provides high availability automatically which would be very difficult to achieve (and very costly) on premise.   Keep in mind that each cloud provider has its strengths and weaknesses; some are better at achieving transparent scalability and server independence than others.    Not for Everyone Note however that it is up to you to leverage the elasticity capabilities of a cloud provider, as discussed previously; if you build a website that does not need to scale, for which elasticity is not important, then you can use a traditional host provider unless you also need high availability. Leveraging the technologies of cloud providers can be difficult and can become a journey for companies that build their solutions in a scale up fashion. Cloud computing promises to address cost containment and scalability of applications with built-in high availability. If your application does not need to scale or you do not need high availability, then cloud computing may not be for you. In fact, you may pay a premium to run your applications with cloud providers due to the underlying technologies built specifically for scalability and availability requirements. And as such, the cloud is not for everyone.   Consistent Customer Experience, Predictable Cost With all its complexities, buzz and foggy definition, cloud computing boils down to a simple objective: consistent customer experience at a predictable cost.  The objective of a cloud solution is to provide the same user experience to your last customer than the first, while keeping your operating costs directly proportional to the number of customers you have. Making your applications elastic and highly available across all its tiers, with as much automation as possible, achieves the first objective of a consistent customer experience. And the ability to expand and contract the infrastructure footprint of your application dynamically achieves the cost containment objectives.     Herve Roggero is a SQL Azure MVP and co-author of Pro SQL Azure (APress).  He is the co-founder of Blue Syntax Consulting (www.bluesyntax.net), a company focusing on cloud computing technologies helping customers understand and adopt cloud computing technologies. For more information contact herve at hroggero @ bluesyntax.net .

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  • Any way to set up a grid for a board game in cocos 2d?

    - by Scott
    My first idea was to create a 2d array for my columns and rows, but it seems like there should be a better, or possibly cleaner, way to achieve this. Each square on the grid is going to have a background image, probably a .png although I might just draw the images with a draw method. Basically, I want to be able to drag and drop images onto the individual grid squares. I've been searching for a solution and the closest thing I can find is the tiled map solution. That just seems like a little overkill for what I'm trying to accomplish. Also, I don't know if this helps but i need my grid to be 12 by 12 and take up the entire width of the iphone screen.

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  • Finding the closest grid coordinate to the mouse position with javascript/jQuery

    - by Acorn
    What I'm trying to do is make a grid of invisible coordinates on the page equally spaced. I then want a <div> to be placed at whatever grid coordinate is closest to the pointer when onclick is triggered. Here's the rough idea: I have the tracking of the mouse coordinates and the placing of the <div> worked out fine. What I'm stuck with is how to approach the problem of the grid of coordinates. First of all, should I have all my coordinates in an array which I then compare my onclick coordinate to? Or seeing as my grid coordinates follow a rule, could I do something like finding out which coordinate that is a multiple of whatever my spacing is is closest to the onclick coordinate? And then, where do I start with working out which grid point coordinate is closest? What's the best way of going about it? Thanks!

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  • Finding the closest grid coordinate to the mouse onclick with javascript/jQuery

    - by Acorn
    What I'm trying to do is make a grid of invisible coordinates on the page equally spaced. I then want a <div> to be placed at whatever grid coordinate is closest to the pointer when onclick is triggered. Here's the rough idea: I have the tracking of the mouse coordinates and the placing of the <div> worked out fine. What I'm stuck with is how to approach the problem of the grid of coordinates. First of all, should I have all my coordinates in an array which I then compare my onclick coordinate to? Or seeing as my grid coordinates follow a rule, could I do something like finding out which coordinate that is a multiple of whatever my spacing is is closest to the onclick coordinate? And then, where do I start with working out which grid point coordinate is closest? What's the best way of going about it? Thanks!

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  • WxPython multiple grid instances

    - by randomPythonHacker
    Does anybody know how I can get multiple instances of the same grid to display on one frame? Whenever I create more than 1 instance of the same object, the display of the original grid widget completely collapses and I'm left unable to do anything with it. For reference, here's the code: import wx import wx.grid as gridlib class levelGrid(gridlib.Grid): def __init__(self, parent, rows, columns): gridlib.Grid.__init__(self, parent, -1) self.moveTo = None self.CreateGrid(rows, columns) self.SetDefaultColSize(32) self.SetDefaultRowSize(32) self.SetColLabelSize(0) self.SetRowLabelSize(0) self.SetDefaultCellBackgroundColour(wx.BLACK) self.EnableDragGridSize(False) class mainFrame(wx.Frame): def __init__(self, parent, id, title): wx.Frame.__init__(self, parent, id, title, size=(768, 576)) editor = levelGrid(self, 25, 25) panel1 = wx.Panel(editor, -1) #vbox = wx.BoxSizer(wx.VERTICAL) #vbox.Add(editor, 1, wx.EXPAND | wx.ALL, 5) #selector = levelGrid(self, 1, 25) #vbox.Add(selector, 1, wx.EXPAND |wx.BOTTOM, 5) self.Centre() self.Show(True) app = wx.App() mainFrame(None, -1, "SLAE") app.MainLoop()

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  • [Python/Tkinter] Grid within a frame?

    - by Sam
    Is it possible to place a grid of buttons in Tkinter inside another frame? I'm wanting to create a tic-tac-toe like game and want to use the grid feature to put gamesquares (that will be buttons). However, I'd like to have other stuff in the GUI other than just the game board so it's not ideal to just have everything in the one grid. To illustrate: O | X | X | ---------- | O | O | X | Player 2 wins! ---------- | X | O | X | The tic tac toe board is in a grid that is made up of all buttons and the 'player 2 wins' is a label inside a frame. This is an oversimplification of what I'm trying to do so bear with me, for the way I've designed the program so far (the board is dynamically created) a grid makes the most sense.

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  • SL3 Grid RowDefinition Height Problem

    - by Chris
    I have a parent grid that contains multiple row definitions, all of which have their height set to 'auto'. Within the parent grid are individual grids - each individual grid contains a custom content control. When the custom content control loads, the height may increase. What I am noticing is that when the height does increase, the content overlaps with the content in other rows. I have specified the horizontal and vertical alignments - am I missing something? Here is an example: <Grid x:Name="LayoutRoot"> <Grid x:Name="ParentGrid>"> <Grid.RowDefinitions> <RowDefinition Height="Auto"/> <RowDefinition Height="Auto"/> <RowDefinition Height="Auto"/> </Grid.RowDefinitions> <Grid Grid.Row="0"> <CustomContentControl/> </Grid> <Grid Grid.Row="1"> <CustomContentControl/> </Grid> <Grid Grid.Row="2"> <CustomContentControl/> </Grid> </Grid> </Grid>

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  • Oracle Database 11g now certified on Oracle Linux 6 and RHEL 6

    - by Chuck Speaks
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 DefSemiHidden="true" DefQFormat="false" DefPriority="99" LatentStyleCount="267" UnhideWhenUsed="false" QFormat="true" Name="Normal"/ UnhideWhenUsed="false" QFormat="true" Name="heading 1"/ UnhideWhenUsed="false" QFormat="true" Name="Title"/ UnhideWhenUsed="false" QFormat="true" Name="Subtitle"/ UnhideWhenUsed="false" QFormat="true" Name="Strong"/ UnhideWhenUsed="false" QFormat="true" Name="Emphasis"/ UnhideWhenUsed="false" Name="Table Grid"/ UnhideWhenUsed="false" QFormat="true" Name="No Spacing"/ UnhideWhenUsed="false" Name="Light Shading"/ UnhideWhenUsed="false" Name="Light List"/ UnhideWhenUsed="false" Name="Light Grid"/ UnhideWhenUsed="false" Name="Medium Shading 1"/ UnhideWhenUsed="false" Name="Medium Shading 2"/ UnhideWhenUsed="false" Name="Medium List 1"/ UnhideWhenUsed="false" Name="Medium List 2"/ UnhideWhenUsed="false" Name="Medium Grid 1"/ UnhideWhenUsed="false" Name="Medium Grid 2"/ UnhideWhenUsed="false" Name="Medium Grid 3"/ UnhideWhenUsed="false" Name="Dark List"/ UnhideWhenUsed="false" Name="Colorful Shading"/ UnhideWhenUsed="false" Name="Colorful List"/ UnhideWhenUsed="false" Name="Colorful Grid"/ UnhideWhenUsed="false" Name="Light Shading Accent 1"/ UnhideWhenUsed="false" Name="Light List Accent 1"/ UnhideWhenUsed="false" Name="Light Grid Accent 1"/ UnhideWhenUsed="false" Name="Medium Shading 1 Accent 1"/ UnhideWhenUsed="false" Name="Medium Shading 2 Accent 1"/ UnhideWhenUsed="false" Name="Medium List 1 Accent 1"/ UnhideWhenUsed="false" QFormat="true" Name="List Paragraph"/ UnhideWhenUsed="false" QFormat="true" Name="Quote"/ UnhideWhenUsed="false" QFormat="true" Name="Intense Quote"/ UnhideWhenUsed="false" Name="Medium List 2 Accent 1"/ UnhideWhenUsed="false" Name="Medium Grid 1 Accent 1"/ UnhideWhenUsed="false" Name="Medium Grid 2 Accent 1"/ UnhideWhenUsed="false" Name="Medium Grid 3 Accent 1"/ UnhideWhenUsed="false" Name="Dark List Accent 1"/ UnhideWhenUsed="false" Name="Colorful Shading Accent 1"/ UnhideWhenUsed="false" Name="Colorful List Accent 1"/ UnhideWhenUsed="false" Name="Colorful Grid Accent 1"/ UnhideWhenUsed="false" Name="Light Shading Accent 2"/ UnhideWhenUsed="false" Name="Light List Accent 2"/ UnhideWhenUsed="false" Name="Light Grid Accent 2"/ UnhideWhenUsed="false" Name="Medium Shading 1 Accent 2"/ UnhideWhenUsed="false" Name="Medium Shading 2 Accent 2"/ UnhideWhenUsed="false" Name="Medium List 1 Accent 2"/ UnhideWhenUsed="false" Name="Medium List 2 Accent 2"/ UnhideWhenUsed="false" Name="Medium Grid 1 Accent 2"/ UnhideWhenUsed="false" Name="Medium Grid 2 Accent 2"/ UnhideWhenUsed="false" Name="Medium Grid 3 Accent 2"/ UnhideWhenUsed="false" Name="Dark List Accent 2"/ UnhideWhenUsed="false" Name="Colorful Shading Accent 2"/ UnhideWhenUsed="false" Name="Colorful List Accent 2"/ UnhideWhenUsed="false" Name="Colorful Grid Accent 2"/ UnhideWhenUsed="false" Name="Light Shading Accent 3"/ UnhideWhenUsed="false" Name="Light List Accent 3"/ UnhideWhenUsed="false" Name="Light Grid Accent 3"/ UnhideWhenUsed="false" Name="Medium Shading 1 Accent 3"/ UnhideWhenUsed="false" Name="Medium Shading 2 Accent 3"/ UnhideWhenUsed="false" Name="Medium List 1 Accent 3"/ UnhideWhenUsed="false" Name="Medium List 2 Accent 3"/ UnhideWhenUsed="false" Name="Medium Grid 1 Accent 3"/ UnhideWhenUsed="false" Name="Medium Grid 2 Accent 3"/ UnhideWhenUsed="false" Name="Medium Grid 3 Accent 3"/ UnhideWhenUsed="false" Name="Dark List Accent 3"/ UnhideWhenUsed="false" Name="Colorful Shading Accent 3"/ UnhideWhenUsed="false" Name="Colorful List Accent 3"/ UnhideWhenUsed="false" Name="Colorful Grid Accent 3"/ UnhideWhenUsed="false" Name="Light Shading Accent 4"/ UnhideWhenUsed="false" Name="Light List Accent 4"/ UnhideWhenUsed="false" Name="Light Grid Accent 4"/ UnhideWhenUsed="false" Name="Medium Shading 1 Accent 4"/ UnhideWhenUsed="false" Name="Medium Shading 2 Accent 4"/ UnhideWhenUsed="false" Name="Medium List 1 Accent 4"/ UnhideWhenUsed="false" Name="Medium List 2 Accent 4"/ UnhideWhenUsed="false" Name="Medium Grid 1 Accent 4"/ UnhideWhenUsed="false" Name="Medium Grid 2 Accent 4"/ UnhideWhenUsed="false" Name="Medium Grid 3 Accent 4"/ UnhideWhenUsed="false" Name="Dark List Accent 4"/ UnhideWhenUsed="false" Name="Colorful Shading Accent 4"/ UnhideWhenUsed="false" Name="Colorful List Accent 4"/ UnhideWhenUsed="false" Name="Colorful Grid Accent 4"/ UnhideWhenUsed="false" Name="Light Shading Accent 5"/ UnhideWhenUsed="false" Name="Light List Accent 5"/ UnhideWhenUsed="false" Name="Light Grid Accent 5"/ UnhideWhenUsed="false" Name="Medium Shading 1 Accent 5"/ UnhideWhenUsed="false" Name="Medium Shading 2 Accent 5"/ UnhideWhenUsed="false" Name="Medium List 1 Accent 5"/ UnhideWhenUsed="false" Name="Medium List 2 Accent 5"/ UnhideWhenUsed="false" Name="Medium Grid 1 Accent 5"/ UnhideWhenUsed="false" Name="Medium Grid 2 Accent 5"/ UnhideWhenUsed="false" Name="Medium Grid 3 Accent 5"/ UnhideWhenUsed="false" Name="Dark List Accent 5"/ UnhideWhenUsed="false" Name="Colorful Shading Accent 5"/ UnhideWhenUsed="false" Name="Colorful List Accent 5"/ UnhideWhenUsed="false" Name="Colorful Grid Accent 5"/ UnhideWhenUsed="false" Name="Light Shading Accent 6"/ UnhideWhenUsed="false" Name="Light List Accent 6"/ UnhideWhenUsed="false" Name="Light Grid Accent 6"/ UnhideWhenUsed="false" Name="Medium Shading 1 Accent 6"/ UnhideWhenUsed="false" Name="Medium Shading 2 Accent 6"/ UnhideWhenUsed="false" Name="Medium List 1 Accent 6"/ UnhideWhenUsed="false" Name="Medium List 2 Accent 6"/ UnhideWhenUsed="false" Name="Medium Grid 1 Accent 6"/ UnhideWhenUsed="false" Name="Medium Grid 2 Accent 6"/ UnhideWhenUsed="false" Name="Medium Grid 3 Accent 6"/ UnhideWhenUsed="false" Name="Dark List Accent 6"/ UnhideWhenUsed="false" Name="Colorful Shading Accent 6"/ UnhideWhenUsed="false" Name="Colorful List Accent 6"/ UnhideWhenUsed="false" Name="Colorful Grid Accent 6"/ UnhideWhenUsed="false" QFormat="true" Name="Subtle Emphasis"/ UnhideWhenUsed="false" QFormat="true" Name="Intense Emphasis"/ UnhideWhenUsed="false" QFormat="true" Name="Subtle Reference"/ UnhideWhenUsed="false" QFormat="true" Name="Intense Reference"/ UnhideWhenUsed="false" QFormat="true" Name="Book Title"/ /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} http://www.oracle.com/us/corporate/press/1563775  By popular demand....The Oracle 11g database is now certified on Oracle Linux 6 and RHEL 6.  See the link for details. Chuck Speaks @ChuckatOracle

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