Search Results

Search found 8824 results on 353 pages for 'cloud virtualization vmware density scalability'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 96/353 | < Previous Page | 92 93 94 95 96 97 98 99 100 101 102 103  | Next Page >

  • Moving StarterSTS to the (Azure) Cloud

    - by Your DisplayName here!
    Quite some people asked me about an Azure version of StarterSTS. While I kinda knew what I had to do to make the move, I couldn’t find the time. Until recently. This blog post briefly documents the necessary changes and design decisions for the next version of StarterSTS which will work both on-premise and on Azure. Provider Fortunately StarterSTS is already based on the idea of “providers”. Authentication, roles and claims generation is based on the standard ASP.NET provider infrastructure. This makes the migration to different data stores less painful. In my case I simply moved the ASP.NET provider database to SQL Azure and still use the standard SQL Server based membership, roles and profile provider. In addition StarterSTS has its own providers to abstract resource access for certificates, relying party registration, client certificate registration and delegation. So I only had to provide new implementations. Signing and SSL keys now go in the Azure certificate store and user mappings (client certificates and delegation settings) have been moved to Azure table storage. The one thing I didn’t anticipate when I originally wrote StarterSTS was the need to also encapsulate configuration. Currently configuration is “locked” to the standard .NET configuration system. The new version will have a pluggable SettingsProvider with versions for .NET configuration as well as Azure service configuration. If you want to externalize these settings into e.g. a database, it is now just a matter of supplying a corresponding provider. Moving between the on-premise and Azure version will be just a matter of using different providers. URL Handling Another thing that’s substantially different on Azure (and load balanced scenarios in general) is the handling of URLs. In farm scenarios, the standard APIs like ASP.NET’s Request.Url return the current (internal) machine name, but you typically need the address of the external facing load balancer. There’s a hotfix for WCF 3.5 (included in v4) that fixes this for WCF metadata. This was accomplished by using the HTTP Host header to generate URLs instead of the local machine name. I now use the same approach for generating WS-Federation metadata as well as information card files. New Features I introduced a cache provider. Since we now have slightly more expensive lookups (e.g. relying party data from table storage), it makes sense to cache certain data in the front end. The default implementation uses the ASP.NET web cache and can be easily extended to use products like memcached or AppFabric Caching. Starting with the relying party provider, I now also provide a read/write interface. This allows building management interfaces on top of this provider. I also include a (very) simple web page that allows working with the relying party provider data. I guess I will use the same approach for other providers in the future as well. I am also doing some work on the tracing and health monitoring area. Especially important for the Azure version. Stay tuned.

    Read the article

  • What Sort of Server Setup Am I Likely to Need? - School A/V streaming

    - by DeathMagus
    My prior experience with servers has generally been limited to home file-sharing servers, low-traffic web-servers, and the like. This leaves me with the technical knowledge of how to set up a system, but little experience in terms of scaling said system. My current project, however, has me as the technical lead in setting up a school for online audio and video streaming. The difficulty I'm running into is that I don't quite have the experience to guess what they'll need, and they don't have the experience to tell me - so I've tried to ask as many pertinent questions about what they want to do with their server, and here's what I found out: About 1000 simultaneous users, and hoping to expand (possibly significantly) Both video and audio streaming, at obviously the highest quality possible Support for both live and playlist-based streaming. Probably only one channel, but as it's an educational opportunity, I imagine letting them have a few more wouldn't hurt. No word on whether they're locked into Windows or whether Linux is acceptable. Approximate budget - $7000. It may actually be about $2k less than this, because of a mishap with another technology firm (they ordered a $7000 DV tape deck for some reason, and now the company wants them to pay a 30% restocking fee). The tentative decisions I've already made: I'm planning on using Icecast 2 for my streaming server, fed by VLC Shoutcast encoding. Since the school already has a DMZ set up, I plan on placing the Icecast server in there, and feeding it through their intranet from a simple workstation computer in their studios. This system isn't in any way mission critical - it's an education tool (they're a media magnet school), so I figure redundancy is not worthwhile to them from a cost:benefit perspective. What I don't know is this: How powerful of a server will I need? What is likely to be my major throttle - bandwidth? How can I mitigate that? Will I need anything special for the encoding workstation other than professional video and audio capture cards and a copy of VLC? Are there any other considerations that I'm simply missing? Thanks a lot for any help - if there's more information you need, let me know and I'll tell you all I can.

    Read the article

  • Sharing / replicating EBS across AWS nodes

    - by skrat
    I would like to use single EBS storage across multiple EC2 nodes (web/app servers). I've read some articles on snapshot sharing, but that doesn't suit well for what we need. We use filesystem for storing DB record attachments, so if one such attachment gets created, we need it to be immediately available to all nodes (to serve). So far only NFS seem to be viable, but it's a pain to configure and maintain. Another option could be storing those attachments on S3 instead, but that would cut us of doing any analysis on that data. This must be quite common problem when scaling in AWS, what solutions are there?

    Read the article

  • Oracle Cloud Applications Day 2013, tutte le foto!

    - by claudiac.caramelli
    Non sarete con noi al Sole 24Ore? Tutte le foto dell'evento le potrete trovare a questo link, caricate in diretta per vivere l'esperienza ancora più live.  Seguite l'andamento della plenaria su Twitter e partecipate alla discussione con l'hashtag #CloudDayIt. Non perdetevi nessun contenuto che vi aiuterà a scoprire i vantaggi e le opportunità di un nuovo modo di operare per rafforzare la propria competitività.

    Read the article

  • What are the typical methods used to scale up/out email storage servers?

    - by nareshov
    Hi, What I've tried: I have two email storage architectures. Old and new. Old: courier-imapds on several (18+) 1TB-storage servers. If one of them show signs of running out of disk space, we migrate a few email accounts to another server. the servers don't have replicas. no backups either. New: dovecot2 on a single huge server with 16TB (SATA) storage and a few SSDs we store fresh mails on the SSDs and run a doveadm purge to move mails older than a day to the SATA disks there is an identical server which has a max-15min-old rsync backup from the primary server higher-ups/management wanted to pack in as much storage as possible per server in order to minimise the cost of SSDs per server the rsync'ing is done because GlusterFS wasn't replicating well under that high small/random-IO. scaling out was expected to be done with provisioning another pair of such huge servers on facing disk-crunch issues like in the old architecture, manual moving of email accounts would be done. Concerns/doubts: I'm not convinced with the synchronously-replicated filesystem idea works well for heavy random/small-IO. GlusterFS isn't working for us yet, I'm not sure if there's another filesystem out there for this use case. The idea was to keep identical pairs and use DNS round-robin for email delivery and IMAP/POP3 access. And if one the servers went down for whatever reasons (planned/unplanned), we'd move the IP to the other server in the pair. In filesystems like Lustre, I get the advantage of a single namespace whereby I do not have to worry about manually migrating accounts around and updating MAILHOME paths and other metadata/data. Questions: What are the typical methods used to scale up/out with the traditional software (courier-imapd / dovecot)? Do traditional software that store on a locally mounted filesystem pose a roadblock to scale out with minimal "problems"? Does one have to re-write (parts of) these to work with an object-storage of some sort - such as OpenStack object storage?

    Read the article

  • MP3 files downloaded from cloud incomplete/cut off (Android app)

    - by rudefyet
    I noticed today on my phone (Droid X running Android 2.2.1) that when streaming the Ubuntu One app would skip to the next song before the previous one had finished. Looking into it, one of the mp3s downloaded from the server was only 2.5MB instead of 4.2MB as it shows on the server itself via one.ubuntu.com. It's happened with multiple tracks today (I remember it happening once the first time I used the app too but shrugged it off as a glitch). The app itself shows a star on the playlist item indicating the file was downloaded even though it was apparently cut off for some reason, perhaps lack of good cell coverage, or some sort of dropped connection. It seems like the latter may be happening and instead of showing an error or retrying it just stops and shows the download is complete.

    Read the article

  • Dynamically changing one-node Cassandra cluster to two nodes

    - by Jason Axelson
    So I have an application that will be very dormant most of the time but will need high-bursting a few days out of the month. Since we are deploying on EC2 I would like to keep only one Cassandra server up most of the time and then on burst days I want to bring one more server up (with more RAM and CPU than the first) to help serve the load. What is the best way to do this? Should I take a different approach? Some notes about what I plan to do: Bring the node up and repair it immediately After the burst time is over decommission the powerful node Use the always-on server as the seed node My main question is how to get the nodes to share all the data since I want a replication factor of 2 (so both nodes have all the data) but that won't work while there is only one server. Should I bring up 2 extra servers instead of just one?

    Read the article

  • Load testing nginx inside AWS

    - by andy
    I'm trying to load test nginx running on AWS. I need to try to optimise it to handle 1Gbps of inbound traffic. Currently I've got it to peak at 85Mbit/s by running nginx on an m1.large with 4 other machines hitting it by using ab with -i (for head requests) -k (keepalives) -r (ignore failed requests) -n 500000 -c 20000. I'm struggling to generate more than 85 Mbit/s traffic from 4 machines, yet when I do scp a large file I get nearly 0.25Gbit/s of traffic going over the network. Are there any tools or approaches that I could use to load test nginx that might generate more load? I'm only interested in inbound traffic, so perhaps a DoS tool could help if it chucks away responses? I'm hitting a very small (40 byte) static asset, and have peaked at handling 50K concurrent connections and getting 25k reqs/s when just using a single load generator machine.

    Read the article

  • How can I determine Breaking point of my Web application using JMeter?

    - by Gopu Alakrishna
    How can I determine Breaking point of my Web application using JMeter? I have executed the JMeter Testplan with different concurrent users load. EX. 300 users(0% error), 400 users(7% error in a sample, 5% error in another sample), 500 users(more than 10% error in 4 out of 6 samples). At What value of % Error, I can say system reached the Breaking point.I used concurrent users 300, 400, 500 in a PHP website. Should I consider any other parameter to determine breaking point. How many maximum concurrent users my application can support?

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 92 93 94 95 96 97 98 99 100 101 102 103  | Next Page >