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• How to improve network performance between two Win 2008 KMV guest having virtio driver already?

  - by taazaa

  I have two physical servers with Ubuntu 10.04 server on them. They are connected with a 1Gbps card over a gigabit switch. Each of these host servers has one Win 2008 guest VM. Both VMs are well provisioned (4 cores, 12GB RAM), RAW disks. My asp.net/sql server applications are running much slower compared to very similar physical setups. Both machines are setup to use virtio for disk and network. I used iperf to check network performance and I get: Physical host 1 ----- Physical Host 2: 957 Mbits/sec Physical host 1 ----- Win 08 Guest 1: 557 Mbits/sec Win 08 Guest 1 ----- Phy host 1: 182 Mbits/sec Win 08 Guest 1 ----- Win 08 Guest 2: 111 Mbits /sec My app is running on Win08 Guest 1 and Guest 2 (web and db). There is a huge drop in network throughput (almost 90%) between the two guest. Further the throughput does not seem to be symmetric between host and guest as well. The CPU utilization on the guests and hosts is less than 2% right now (we are just testing right now). Apart from this, there have been random slow downs in the network to as low as 1 Mbits/sec making the whole application unusable. Any help to trouble shoot this would be appreciated.

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• Is there a way to use VirtualBox without using it's resource registry?

  - by Catskul

  Summary VirtualBox seems to want everything to be "registered" which makes it much more annoying to work with on the command line. I'm attempting to create an automated script which will create, move, start, stop, and destroy virtual machines and virtual disks. Requiring registration will complicate the task for the following reasons. leaves state information around that can cause unpredicted edgecases causing scripts to fail. creates potential name space collisions for multiple process creating VMs with the same name moving/copying resources on the same machine is more complicated because references in the registry need to be updated copying resources (disk + vm combination) to another machine require reconfiguration once they reach their target machine, and require the transfer of extra meta data to do the reconfiguration. If something unexpectedly fails, and an unregister thus fails to happen, left over configuration information can cause problems in subsequent runs. Use Case My specific use case is for a continuous integration server which creates and destroys VMs and Disk images potentially with the same name, and would require more logic to deal with the registry's statefulness. Imaginary Example It seems that I should just be able to for example (using some imaginary and/or incorrect commands): mkdir foobar customdiskimg_script ./foo/foo.vdi vboxmanage createvm --name "foo" --ostype Linux --basefolder ./foo/foo.xml vboxmanage storagectl ./foo/foo.xml --name foo --add ide vboxmanage storageattach --storagectl foo --medium ./foo/foo.vdi ./foo/foo.xml vboxmanage startvm ./foo/foo.xml TLDR Is there a way to use virtualbox without "registering" harddisks and VMs?

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• Why am I getting programs stuck in log_wait_commit under Linux?

  - by staticsan

  There is something subtly wrong with my Linux install that I just can't locate. It is Ubuntu Lucid Lynx (10.04) 64-bit. Hardware is a Dell Optiplex 960: Intel Core 2 Quad CPU, 8Gb of RAM, 2x 300Gb HDDs. /home is ext2 on one disk and everything else is on the other (/ is also ext3). I have VirtualBox running a 64-bit Vista image for Outlook calendaring, but the heavyweight apps are IntelliJ, NetBeans, MySQL and Opera. Opera also loads my mail (IMAP) of which there is over 10,000 messages. The problem is that Opera stalls for a few seconds from time-to-time. Watching the process list shows it's in log_wait_commit which means (as far as I have figured out) the filesystem is holding things up. Sometimes I can make this happen by doing a subversion update, but usually it happens for no reason I can see. It usually happens to Opera, but I've seen NetBeans go under, too. It doesn't make the app crash - it's just completely unresponsive for a few seconds. Googling has not helped. The closest I got was to remove the sync attribute in the file system. This achieved nothing. On the advice of a Linux guru friend, I lowered /proc/sys/vm/dirty_writeback_centisecs to 300, but that didn't do anything, either. And it was all he could think of. What is going on and can I fix it? (And how?)

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• Ethernet cable unplugged after updating from windows 8.0 to 8.1

  - by Pehmolelu

  Yeah, so I went and updated my windows 8 pro to 8.1. Now everything else seems to work but the network. The Ethernet just says that Network cable is unplugged, even though it is plugged and I have tried different cord as well and I have tested that the router works. I have tried uninstalling the network drivers (Realtec PCIe GBE) and reinstall them with no success. After installing drivers the Device Management gives error for it "Device could not be started. Code 10" Before 8.1 update I had rt630x64.inf, after update it was netrt630x64.inf, and after installing the latest driver rt630x64.inf. With rt630x64.inf there isn't any error, but it's still not just working. New downloaded version: 8.020.0815.2013 (From Realtek website) The driver before: 8.1.510.2013 (After updating the windows to 8.1) I'm using Desktop PC, no VM. I dont have VirtualBox or Vmware installed. I have checked from BIOS that the card is enabled. I have booted in safe mode with network enabled. Says unplugged there as well. I have put the power off for few minutes and put back on, no effect. If anyone has any kind of suggestions, please tell.

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• Removed Old Domain Trust. Now Progress (9.1D) can't open DB File

  - by RLH

  My company has an old server, running Progress 9.1D on a Windows 2000 VM, which was used by our company OS (Vantage 6 by Epicor.) Vantage was our primary OS for a very long time. About 2 years ago, we migrated to a larger, corporate OS and we cancelled our service contract with Epicor. Yesterday, we removed an AD trust between the corporate domain and our old AD domain we used in the days of Vantage. After restarting the virtual server, I have been able to start the ProService for 9.1D Windows service, however, I can not get Vantage to start back up. When I run the application, I get the error in the message listed below. Transcript: ** Could not connect to server for database [progress db file], errno 0. (1432) How can I fix this? FYI, I haven't had to work with Progress in years and even then I wouldn't have considered myself a "novice"-- I'm even less knowledgeable than that title would suggest. Vantage had a lot of internal tools and I recall that Epicor support managed to prevent .pf scripts from being executed. If there was a Progress specific patch that needed to be applied, you had to do it within the Vantage software OR they had to remote into the machine to fix this. I may not be able to run a .pf script but I do know that I can log into the console-based server application. (Yes, I can't even recall which utility that was called. It is sad.) It's been a long time and I never had to digg into Progress that much. Please help and feel free to ask questions. If you need more info, I'll update this post.

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• Minecraft server hosting hardware specifications [on hold]

  - by Andrew Wright

  I am planning on purchasing a server to rent off Minecraft game servers, largely to friends. I am planning on purchasing a 128GB RAM server to save on colocation costs (as I am likely to need more than 32GB and would have to rent 2U of space...) I am hoping for some advice about the processing power needed to deal with this level of RAM. The servers will be run in a shared environment on linux in a VM to make backups easier. The server I have in mind is dual CPU. I have been considering at the low end dual Xeon E5-2609V2 Quad-Core 2.5Ghz, and at the high end dual Xeon E5-2650V2 Eight-Core 2.6Ghz. The difference between these is 6.4 GT/s and 8 GT/s and £3000 for the lower spec server, £4300 for the higher spec. I was hoping I could get advice about whether it is worth paying for the extra/higher speed processor or if I would be wasting my money? Thank you for any help - I appreciate that this is not directly related to professional system administration.

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• Reverse NAT Setup for Hyper-V on Win 2008 R2

  - by sukru

  I'm trying to setup a Linux server behind a Windows Hyper-V host that will help supply some of the services (SSH, HTTPS, etc). However getting RRAS configured for reverse NAT (port forwarding) turned out to be a non trivial task. As a staring point, I tried forwarding port 22 (SSH) to the virtual machine. The virtual machine is on a public interface (i.e.: it also has a visible IP on the same network as the host). On RRAS management console I tried to add a rule, by adding "Local Area Connection" to NAT pool (Public Interface - Enable Nat), and an incoming rule for port 22 - :22. I also tried with the same port enabled on Windows Firewall (and not). The NAT management page tells there are "1 mappings" and "30+ Outbound packets transleted". However all other counters (Inbound packets translated, and respective rejected ones) are always zero. (I'm trying to access the server from an external machine). I can directly access the service if I give the VM's public IP, but not the host's one. Is there a way to enable this on RRAS?

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• How to keep multiple servers in sync file wise?

  - by GForceSys

  I'm currently managing a cluster of PHP-FPM servers, all of which tend to get out of sync with each other. The application that I'm using on top of the app servers (Magento) allows for admins to modify various files on the system, but now that the site is in a clustered set up modifying a file only modifies it on a single instance (on one of the app servers) of the various machines in the cluster. Is there an open-source application for Linux that may allow me to keep all of these servers in sync? I have no problem with creating a small VM instance that can listen for changes from machines to sync. In theory, the perfect application would have small clients that run on each machine to be synced, which would talk to the master server which would then decide how/what to sync from each machine. I have already examined the possibilities of running a centralized file server, but unfortunately my app servers are spread out between EC2 and physical machines, which makes this unfeasible. As there are multiple app servers (some of which are dynamically created depending on the load of the site), simply setting up a rsync cron job is not efficient as the cron job would have to be modified on each machine to send files to every other machine in the cluster, and that would just be a whole bunch of unnecessary data transfers/ssh connections.

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• How to "open" existing VMs in Hyper-V without importing them?

  - by Borek

  I had a PC with two physical disks: C: containing the host operating system D: containing a folder D:\VMs where all my virtual machines were stored Now, the C: disk died. I bought a new one, reinstalled Windows on it, enabled Hyper-V feature and now I just need to open the VMs from the D:\VMs folder. However, I don't seem to be able to find a menu item or anything that would allow me to do that - the only thing I see is the "import" command which unfortunately requires the VMs to be explicitly exported (my machines weren't). I firmly believe that when I have all the files constituting a VM (the VHD file, some XML files describing the settings etc.) it must be somehow possible to just "open" these existing VMs in Hyper-V, right? What command am I missing? Edit: I know I can create a blank virtual machines and then just point them to use existing VHDs. However, I am not sure about all the different settings I've made to those VMs so I hope there's a way to simply open those existing VMs instead of recreating them.

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• Xen HVM Windows 2008 network bridge

  - by JavierMartinz

  I have a problem with the Windows Server 2008 guest (hvm). I can't get a network interface running for him. I also have a Debian guest and it's working ok, but I can't do it with the Win2k8 guest. When I started the VM, the machine freezes and I can't connect by ssh to the host. /etc/network/interfaces # The loopback network interface auto lo iface lo inet loopback auto eth0 iface eth0 inet static address 188.165.B.C netmask 255.255.255.0 network 188.165.B.0 broadcast 188.165.255.255 gateway 188.165.B.254 brctl show bridge name bridge id STP enabled interfaces eth0 8000.e840f20acc28 no peth0 /etc/xen/xend-config.sxp ... (vif-script vif-bridge) (network-script 'network-bridge') ... /etc/xen/win2k8.cfg # Networking # vif = [ 'ip=5.39.F.G,mac=yy:yy:yy:yy:yy:yy,type=ioemu,bridge=eth0' ] /etc/xen/debian.cfg # Networking # vif = [ 'ip=178.33.D.E,mac=xx:xx:xx:xx:xx:xx' ] As you can see, in the Debian guest I only have to specify an IP address and a MAC. But if I put that in the Win2k8 guest, the machine does not start. I am using Xen 4.0

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• (squid): failed to find or read error text file.

  - by adam

  There is something in our ERR_NO_RELAY that is causing this error to be logged and for the squid process to fail on start up. I can't show you the exact content of the file but I can tell you It has several lines of JavaScript When we remove the JavaScript, the problem goes away. This same file does not cause any issues other 3 instances of squid that we have running internally. All instances of squid came from the same VM images so they should be the same. We are unable to reproduce this issue except on the one box and we are unable to debug more on this box right now because it is running in production. I know these files are interpreted so squid can replace certain values available in the session so it may be that a syntax error caused this issue. That does not explain why we cannot reproduce it on other (virtually the same) images. One difference is that the instance of squid that has the issue was under load when the issue occurred. Any suggestions/insight would be appreciated. thanks!

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• Auto-restart mysql when it dies

  - by Los Frijoles

  I have a rackspace server that I have been renting to run my personal projects upon. Since I am cheap, it has 256Mb of RAM and honestly can't handle alot. Every once in a while, when there is a sharp uptick in traffic, the server decides to start killing processes and it seems that mysqld is a popular one for it to kill. I try to visit my site and am greeted with the message that there was an error establishing the database connection. Inspection of the logs reveals that mysqld was killed due to lack of memory. Since I am still as poor as I was yesterday and don't want to upgrade my rackspace VM's RAM, is there a way I can tell it to automagically restart mysqld when it dies? I have a thought to use something like crontab, but alas, I don't know exactly what to do there either. I guess I am product of the "Linux on your desktop" generation since I can do most things on my desktop and laptop (which run Linux almost exclusively), but still lack a lot of server administration skills for Linux. The server runs CentOS 6.3

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• Windows Server 2008 Alerting to Low memory

  - by t1nt1n

  I have a file and print server running on Windows 2008 R2 fully patched in a VSphere environment (ESXi 5.1 fully updated). Every evening between 19:20 and 19:30 our monitoring software reported that the available memory is 1% and performance is dire. There is nothing in the event logs to point to an issue. At this point in the evening I am general the only user on the system to check to see why these alerts are going off. Things I have done; Checked to see if any backups are running – None at all. Checked Scheduled tasks – None before or during this time period. Moved the VM to another host. AV is disabled to rule out that as the issue. The server does not have any problems during the day with memory when fully loaded with about 50 users. The server did have 4GB ram provisioned but I have increased this to 5Gb. Running PrefMon at the time (I will save the graphs tonight) There very little CPU usage at the time but RAM usage goes up.

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• oracle access on vmware fusion

  - by gaudi_br

  Hello, I'm running snow leopard and I'm doing some development that requires some network knowledge. I've installed vmware fusion 3.0 and I've set up a virtual machine with windows 2003 server. I need to mimic the exact configuration of another server in the network, so I really need to run the versions I'll be mentioning here. Besides, I set up two network configurations on the VM: one NAT config (so that I can have internet access) and one host-only config (because I need to use another server's mac adress and my local area network might have a problem with it) From the installation of windows 2003, I then installed oracle 10.2.0.1. During the installation I received a warning about the primary ip-address of the system being dhcp assigned, but I ignored it (maybe it was a mistake)... Now, from experience, unless the DHCP assigned address changes, I should be able to access the guest system's database from the host system, so I went to safari and tried to access the oracle em. As it turns out, because my computer is on a company network, the company's DNS doesn't know about the virtual machine, unless of course I switch to a bridged network config. However, I don't want to do that because I don't to mix up the domains. So I guess the question is, how can I define my own dns or router, or whatever it is that I need to define so that whenever I try the guest system's ip address form the host, it will use the vmnet1 or vmnet8 interface define by vmware and bypass the dns configuration of my local area network. I'd also like to know what to do incase I want to change ip addresses on the guest machine without having oracle go haywire (I've noticed a few folders on the structure which are specific for the very first IP Address)... Any help would be appreciated. Thanks in advance.

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• How can I undo what I did when I accidentally booted linux host inside itself with VMware?

  - by ThomasGHenry

  Hello, I'm dual booting XP and Kubuntu. I wanted to boot to my existing raw scsi XP partition inside Kubuntu, not a virtual XP instance. I accidentally booted Kubuntu inside itself. I know this is a big mistake, so I interrupted the VM, which saved the state and closed. I rebooted the host and now I can't load the Kubuntu partition at boot time. I get a maintenance shell and the Kubuntu partition is read-only. I am able to boot XP as usual. I removed the HDD and tried to mount it on another computer as an external drive and neither partition (XP or Kubuntu) will be recognized, it just appears to be one device that still mounts and appears empty. From the maintenance shell I can see all the files are still on the Kubuntu partition. How can I undo what I did when I accidentally booted Kubuntu inside itself? Is it a matter of unlocking some files somewhere? how can I do that on a RO filesystem? Thanks!

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• Print over the internet from a remote linux session locally (on a Windows 7 machine) to the shared printers?

  - by obeliksz

  I'm trying to use a linux virtual machine as a file server for windows clients. I have successfully implemented remote file sharing (samba+ssh) with which I am able to print locally with a little program that I made for this purpose (jetforms style)... but I would like to hear about a somewhat more direct approach. How can I attach the printers to the server, so that I can for example open a file on the remote session and in the print dialogbox I would see my local printers (on the machine from which I have established a remote session)? I guess there should be some kind of putty tunneling, but dont know how. I have a windows 7 machine locally; there is a CentOS 6 VM over the internet. It has ssh, cups, and samba. I have found a question which asks the opposite: there is a windows based server to connect form linux but that windows has a domain, mine is just a simple windows workstation that is behind NAT and has a dynamic IP. That question is: Print from Linux to Windows networked printer.

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• What are the ways to build a failover cluster?

  - by light

  I have a task where I need to build a failover cluster in two cases: first with servers on Red Hat Enterprise 5.1 and second with SUSE Linux Enterprise 11 SP1. Both cases have SAN. I know there are many ways to build failover cluster, but I can’t find out more, so I need next: The ways to build it? I know only virtualization. Any good book or resource to broad my mind? I’ll be glad to hear any suggestion. Thanks! EDIT #1: failover of servers with bussiness application on it. EDIT #2: will be great to hear summary about solutions with SLES servers? EDIT #3: So if I understand correctly, in my cases the main ways are to use internal solutions or virtualization. So now I have additional questions: Does manufacturer of blades provide some solution? For example HP or IBM. (Without virtualization) Do I need additional server to control "heartbeat" between main and redundant servers? (Virtualization) For example I have several physical servers with VMs. Do I need additional server to control availability of VMs and to move VMs to another physical server in the case their physical server failure? Sorry for my poor English. EDIT #4: Failover of VM or OS on physical server. In both cases will be used SAN , it's not specified, but I think with file system image on it. I started to think that my question is stupid and I need to remake it.

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• System requirements for running windows 8 (basic office use) in virtualbox (ubuntu as host os)

  - by Tor Thommesen

  I want to run windows 8 as a guest os with virtualbox on some thinkpad (haven't bought one yet) running Ubuntu 12.04. Apart from virtualizing windows 8 (mostly just for use with the office suite app) my needs are very modest, I don't need much more than emacs and a browser. What I'd like to know is what kind of specs will be necessary to run windows 8 well as a vm, using the office apps. It would be a shame to waste money on overpowered hardware. Are there any official guidelines from oracle or windows on this? Would this lenovo x220, for example, be sufficiently strong? The specs below were taken from this review. Intel Core i5-2520M dual-core processor (2.5GHz, 3MB cache, 3.2GHz Turbo frequency) Windows 7 Professional (64-bit) 12.5-inch Premium HD (1366 x 768) LED Backlit Display (IPS) Intel Integrated HD Graphics 4GB DDR3 (1333MHz) 320GB Hitachi Travelstar hard drive (Z7K320) Intel Centrino Advanced-N 6205 (Taylor Peak) 2x2 AGN wireless card Intel 82579LM Gigabit Ethernet 720p High Definition webcam Fingerprint reader 6-cell battery (63Wh) and optional slice battery (65Wh) Dimensions: 12 (L) x 8.2 (W) x 0.5-1.5 (H) inches with 6-cell battery Weight: 3.5 pounds with 6-cell battery 4.875 pounds with 6-cell battery and optional external battery slice Price as configured: $1,299.00 (starting at $979.00)

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• CentOS 6 and Sun/Oracle Java Issue

  - by user1710563

  I have a OpenVZ VPS running CentOS 6.3 64 bit and when I try to install JRE 7 64bit using the command: rpm -Uvh java.rpm It gives me this error: Preparing... ########################################### [100%] 1:jre ########################################### [100%] Unpacking JAR files... rt.jar... Error: Could not open input file: /usr/java/jre1.7.0_09/lib/rt.pack jsse.jar... Error: Could not open input file: /usr/java/jre1.7.0_09/lib/jsse.pack charsets.jar... Error: Could not open input file: /usr/java/jre1.7.0_09/lib/charsets.pack localedata.jar... Error: Could not open input file: /usr/java/jre1.7.0_09/lib/ext/localedata.pack I then tried the command: java -version And it gives me this error: Error occurred during initialization of VM Could not reserve enough space for object heap Error: Could not create the Java Virtual Machine Error: A fatal exception has occurred. Program will exit. Why does this happen if I have more than enough RAM on the VPS to run this (1GB)? Could it be an issue with the host node of the VPS? Thanks EDIT 1: Link to beancounter screenshot http://puu.sh/1xwxB EDIT 2: Link to htop screenshot http://puu.sh/1xwDl

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• 256 Windows Azure Worker Roles, Windows Kinect and a 90's Text-Based Ray-Tracer

  - by Alan Smith

  For a couple of years I have been demoing a simple render farm hosted in Windows Azure using worker roles and the Azure Storage service. At the start of the presentation I deploy an Azure application that uses 16 worker roles to render a 1,500 frame 3D ray-traced animation. At the end of the presentation, when the animation was complete, I would play the animation delete the Azure deployment. The standing joke with the audience was that it was that it was a “$2 demo”, as the compute charges for running the 16 instances for an hour was $1.92, factor in the bandwidth charges and it’s a couple of dollars. The point of the demo is that it highlights one of the great benefits of cloud computing, you pay for what you use, and if you need massive compute power for a short period of time using Windows Azure can work out very cost effective. The “$2 demo” was great for presenting at user groups and conferences in that it could be deployed to Azure, used to render an animation, and then removed in a one hour session. I have always had the idea of doing something a bit more impressive with the demo, and scaling it from a “$2 demo” to a “$30 demo”. The challenge was to create a visually appealing animation in high definition format and keep the demo time down to one hour.  This article will take a run through how I achieved this. Ray Tracing Ray tracing, a technique for generating high quality photorealistic images, gained popularity in the 90’s with companies like Pixar creating feature length computer animations, and also the emergence of shareware text-based ray tracers that could run on a home PC. In order to render a ray traced image, the ray of light that would pass from the view point must be tracked until it intersects with an object. At the intersection, the color, reflectiveness, transparency, and refractive index of the object are used to calculate if the ray will be reflected or refracted. Each pixel may require thousands of calculations to determine what color it will be in the rendered image. Pin-Board Toys Having very little artistic talent and a basic understanding of maths I decided to focus on an animation that could be modeled fairly easily and would look visually impressive. I’ve always liked the pin-board desktop toys that become popular in the 80’s and when I was working as a 3D animator back in the 90’s I always had the idea of creating a 3D ray-traced animation of a pin-board, but never found the energy to do it. Even if I had a go at it, the render time to produce an animation that would look respectable on a 486 would have been measured in months. PolyRay Back in 1995 I landed my first real job, after spending three years being a beach-ski-climbing-paragliding-bum, and was employed to create 3D ray-traced animations for a CD-ROM that school kids would use to learn physics. I had got into the strange and wonderful world of text-based ray tracing, and was using a shareware ray-tracer called PolyRay. PolyRay takes a text file describing a scene as input and, after a few hours processing on a 486, produced a high quality ray-traced image. The following is an example of a basic PolyRay scene file. background Midnight_Blue   static define matte surface { ambient 0.1 diffuse 0.7 } define matte_white texture { matte { color white } } define matte_black texture { matte { color dark_slate_gray } } define position_cylindrical 3 define lookup_sawtooth 1 define light_wood <0.6, 0.24, 0.1> define median_wood <0.3, 0.12, 0.03> define dark_wood <0.05, 0.01, 0.005>     define wooden texture { noise surface { ambient 0.2  diffuse 0.7  specular white, 0.5 microfacet Reitz 10 position_fn position_cylindrical position_scale 1  lookup_fn lookup_sawtooth octaves 1 turbulence 1 color_map( [0.0, 0.2, light_wood, light_wood] [0.2, 0.3, light_wood, median_wood] [0.3, 0.4, median_wood, light_wood] [0.4, 0.7, light_wood, light_wood] [0.7, 0.8, light_wood, median_wood] [0.8, 0.9, median_wood, light_wood] [0.9, 1.0, light_wood, dark_wood]) } } define glass texture { surface { ambient 0 diffuse 0 specular 0.2 reflection white, 0.1 transmission white, 1, 1.5 }} define shiny surface { ambient 0.1 diffuse 0.6 specular white, 0.6 microfacet Phong 7  } define steely_blue texture { shiny { color black } } define chrome texture { surface { color white ambient 0.0 diffuse 0.2 specular 0.4 microfacet Phong 10 reflection 0.8 } }   viewpoint {     from <4.000, -1.000, 1.000> at <0.000, 0.000, 0.000> up <0, 1, 0> angle 60     resolution 640, 480 aspect 1.6 image_format 0 }       light <-10, 30, 20> light <-10, 30, -20>   object { disc <0, -2, 0>, <0, 1, 0>, 30 wooden }   object { sphere <0.000, 0.000, 0.000>, 1.00 chrome } object { cylinder <0.000, 0.000, 0.000>, <0.000, 0.000, -4.000>, 0.50 chrome }   After setting up the background and defining colors and textures, the viewpoint is specified. The “camera” is located at a point in 3D space, and it looks towards another point. The angle, image resolution, and aspect ratio are specified. Two lights are present in the image at defined coordinates. The three objects in the image are a wooden disc to represent a table top, and a sphere and cylinder that intersect to form a pin that will be used for the pin board toy in the final animation. When the image is rendered, the following image is produced. The pins are modeled with a chrome surface, so they reflect the environment around them. Note that the scale of the pin shaft is not correct, this will be fixed later. Modeling the Pin Board The frame of the pin-board is made up of three boxes, and six cylinders, the front box is modeled using a clear, slightly reflective solid, with the same refractive index of glass. The other shapes are modeled as metal. object { box <-5.5, -1.5, 1>, <5.5, 5.5, 1.2> glass } object { box <-5.5, -1.5, -0.04>, <5.5, 5.5, -0.09> steely_blue } object { box <-5.5, -1.5, -0.52>, <5.5, 5.5, -0.59> steely_blue } object { cylinder <-5.2, -1.2, 1.4>, <-5.2, -1.2, -0.74>, 0.2 steely_blue } object { cylinder <5.2, -1.2, 1.4>, <5.2, -1.2, -0.74>, 0.2 steely_blue } object { cylinder <-5.2, 5.2, 1.4>, <-5.2, 5.2, -0.74>, 0.2 steely_blue } object { cylinder <5.2, 5.2, 1.4>, <5.2, 5.2, -0.74>, 0.2 steely_blue } object { cylinder <0, -1.2, 1.4>, <0, -1.2, -0.74>, 0.2 steely_blue } object { cylinder <0, 5.2, 1.4>, <0, 5.2, -0.74>, 0.2 steely_blue }   In order to create the matrix of pins that make up the pin board I used a basic console application with a few nested loops to create two intersecting matrixes of pins, which models the layout used in the pin boards. The resulting image is shown below. The pin board contains 11,481 pins, with the scene file containing 23,709 lines of code. For the complete animation 2,000 scene files will be created, which is over 47 million lines of code. Each pin in the pin-board will slide out a specific distance when an object is pressed into the back of the board. This is easily modeled by setting the Z coordinate of the pin to a specific value. In order to set all of the pins in the pin-board to the correct position, a bitmap image can be used. The position of the pin can be set based on the color of the pixel at the appropriate position in the image. When the Windows Azure logo is used to set the Z coordinate of the pins, the following image is generated. The challenge now was to make a cool animation. The Azure Logo is fine, but it is static. Using a normal video to animate the pins would not work; the colors in the video would not be the same as the depth of the objects from the camera. In order to simulate the pin board accurately a series of frames from a depth camera could be used. Windows Kinect The Kenect controllers for the X-Box 360 and Windows feature a depth camera. The Kinect SDK for Windows provides a programming interface for Kenect, providing easy access for .NET developers to the Kinect sensors. The Kinect Explorer provided with the Kinect SDK is a great starting point for exploring Kinect from a developers perspective. Both the X-Box 360 Kinect and the Windows Kinect will work with the Kinect SDK, the Windows Kinect is required for commercial applications, but the X-Box Kinect can be used for hobby projects. The Windows Kinect has the advantage of providing a mode to allow depth capture with objects closer to the camera, which makes for a more accurate depth image for setting the pin positions. Creating a Depth Field Animation The depth field animation used to set the positions of the pin in the pin board was created using a modified version of the Kinect Explorer sample application. In order to simulate the pin board accurately, a small section of the depth range from the depth sensor will be used. Any part of the object in front of the depth range will result in a white pixel; anything behind the depth range will be black. Within the depth range the pixels in the image will be set to RGB values from 0,0,0 to 255,255,255. A screen shot of the modified Kinect Explorer application is shown below. The Kinect Explorer sample application was modified to include slider controls that are used to set the depth range that forms the image from the depth stream. This allows the fine tuning of the depth image that is required for simulating the position of the pins in the pin board. The Kinect Explorer was also modified to record a series of images from the depth camera and save them as a sequence JPEG files that will be used to animate the pins in the animation the Start and Stop buttons are used to start and stop the image recording. En example of one of the depth images is shown below. Once a series of 2,000 depth images has been captured, the task of creating the animation can begin. Rendering a Test Frame In order to test the creation of frames and get an approximation of the time required to render each frame a test frame was rendered on-premise using PolyRay. The output of the rendering process is shown below. The test frame contained 23,629 primitive shapes, most of which are the spheres and cylinders that are used for the 11,800 or so pins in the pin board. The 1280x720 image contains 921,600 pixels, but as anti-aliasing was used the number of rays that were calculated was 4,235,777, with 3,478,754,073 object boundaries checked. The test frame of the pin board with the depth field image applied is shown below. The tracing time for the test frame was 4 minutes 27 seconds, which means rendering the2,000 frames in the animation would take over 148 hours, or a little over 6 days. Although this is much faster that an old 486, waiting almost a week to see the results of an animation would make it challenging for animators to create, view, and refine their animations. It would be much better if the animation could be rendered in less than one hour. Windows Azure Worker Roles The cost of creating an on-premise render farm to render animations increases in proportion to the number of servers. The table below shows the cost of servers for creating a render farm, assuming a cost of $500 per server. Number of Servers Cost 1 $500 16 $8,000 256 $128,000   As well as the cost of the servers, there would be additional costs for networking, racks etc. Hosting an environment of 256 servers on-premise would require a server room with cooling, and some pretty hefty power cabling. The Windows Azure compute services provide worker roles, which are ideal for performing processor intensive compute tasks. With the scalability available in Windows Azure a job that takes 256 hours to complete could be perfumed using different numbers of worker roles. The time and cost of using 1, 16 or 256 worker roles is shown below. Number of Worker Roles Render Time Cost 1 256 hours $30.72 16 16 hours $30.72 256 1 hour $30.72   Using worker roles in Windows Azure provides the same cost for the 256 hour job, irrespective of the number of worker roles used. Provided the compute task can be broken down into many small units, and the worker role compute power can be used effectively, it makes sense to scale the application so that the task is completed quickly, making the results available in a timely fashion. The task of rendering 2,000 frames in an animation is one that can easily be broken down into 2,000 individual pieces, which can be performed by a number of worker roles. Creating a Render Farm in Windows Azure The architecture of the render farm is shown in the following diagram. The render farm is a hybrid application with the following components: ·         On-Premise o   Windows Kinect – Used combined with the Kinect Explorer to create a stream of depth images. o   Animation Creator – This application uses the depth images from the Kinect sensor to create scene description files for PolyRay. These files are then uploaded to the jobs blob container, and job messages added to the jobs queue. o   Process Monitor – This application queries the role instance lifecycle table and displays statistics about the render farm environment and render process. o   Image Downloader – This application polls the image queue and downloads the rendered animation files once they are complete. ·         Windows Azure o   Azure Storage – Queues and blobs are used for the scene description files and completed frames. A table is used to store the statistics about the rendering environment.   The architecture of each worker role is shown below.   The worker role is configured to use local storage, which provides file storage on the worker role instance that can be use by the applications to render the image and transform the format of the image. The service definition for the worker role with the local storage configuration highlighted is shown below. <?xml version="1.0" encoding="utf-8"?> <ServiceDefinition name="CloudRay" >   <WorkerRole name="CloudRayWorkerRole" vmsize="Small">     <Imports>     </Imports>     <ConfigurationSettings>       <Setting name="DataConnectionString" />     </ConfigurationSettings>     <LocalResources>       <LocalStorage name="RayFolder" cleanOnRoleRecycle="true" />     </LocalResources>   </WorkerRole> </ServiceDefinition>     The two executable programs, PolyRay.exe and DTA.exe are included in the Azure project, with Copy Always set as the property. PolyRay will take the scene description file and render it to a Truevision TGA file. As the TGA format has not seen much use since the mid 90’s it is converted to a JPG image using Dave's Targa Animator, another shareware application from the 90’s. Each worker roll will use the following process to render the animation frames. 1.       The worker process polls the job queue, if a job is available the scene description file is downloaded from blob storage to local storage. 2.       PolyRay.exe is started in a process with the appropriate command line arguments to render the image as a TGA file. 3.       DTA.exe is started in a process with the appropriate command line arguments convert the TGA file to a JPG file. 4.       The JPG file is uploaded from local storage to the images blob container. 5.       A message is placed on the images queue to indicate a new image is available for download. 6.       The job message is deleted from the job queue. 7.       The role instance lifecycle table is updated with statistics on the number of frames rendered by the worker role instance, and the CPU time used. The code for this is shown below. public override void Run() {     // Set environment variables     string polyRayPath = Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), PolyRayLocation);     string dtaPath = Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), DTALocation);       LocalResource rayStorage = RoleEnvironment.GetLocalResource("RayFolder");     string localStorageRootPath = rayStorage.RootPath;       JobQueue jobQueue = new JobQueue("renderjobs");     JobQueue downloadQueue = new JobQueue("renderimagedownloadjobs");     CloudRayBlob sceneBlob = new CloudRayBlob("scenes");     CloudRayBlob imageBlob = new CloudRayBlob("images");     RoleLifecycleDataSource roleLifecycleDataSource = new RoleLifecycleDataSource();       Frames = 0;       while (true)     {         // Get the render job from the queue         CloudQueueMessage jobMsg = jobQueue.Get();           if (jobMsg != null)         {             // Get the file details             string sceneFile = jobMsg.AsString;             string tgaFile = sceneFile.Replace(".pi", ".tga");             string jpgFile = sceneFile.Replace(".pi", ".jpg");               string sceneFilePath = Path.Combine(localStorageRootPath, sceneFile);             string tgaFilePath = Path.Combine(localStorageRootPath, tgaFile);             string jpgFilePath = Path.Combine(localStorageRootPath, jpgFile);               // Copy the scene file to local storage             sceneBlob.DownloadFile(sceneFilePath);               // Run the ray tracer.             string polyrayArguments =                 string.Format("\"{0}\" -o \"{1}\" -a 2", sceneFilePath, tgaFilePath);             Process polyRayProcess = new Process();             polyRayProcess.StartInfo.FileName =                 Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), polyRayPath);             polyRayProcess.StartInfo.Arguments = polyrayArguments;             polyRayProcess.Start();             polyRayProcess.WaitForExit();               // Convert the image             string dtaArguments =                 string.Format(" {0} /FJ /P{1}", tgaFilePath, Path.GetDirectoryName (jpgFilePath));             Process dtaProcess = new Process();             dtaProcess.StartInfo.FileName =                 Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), dtaPath);             dtaProcess.StartInfo.Arguments = dtaArguments;             dtaProcess.Start();             dtaProcess.WaitForExit();               // Upload the image to blob storage             imageBlob.UploadFile(jpgFilePath);               // Add a download job.             downloadQueue.Add(jpgFile);               // Delete the render job message             jobQueue.Delete(jobMsg);               Frames++;         }         else         {             Thread.Sleep(1000);         }           // Log the worker role activity.         roleLifecycleDataSource.Alive             ("CloudRayWorker", RoleLifecycleDataSource.RoleLifecycleId, Frames);     } }     Monitoring Worker Role Instance Lifecycle In order to get more accurate statistics about the lifecycle of the worker role instances used to render the animation data was tracked in an Azure storage table. The following class was used to track the worker role lifecycles in Azure storage.   public class RoleLifecycle : TableServiceEntity {     public string ServerName { get; set; }     public string Status { get; set; }     public DateTime StartTime { get; set; }     public DateTime EndTime { get; set; }     public long SecondsRunning { get; set; }     public DateTime LastActiveTime { get; set; }     public int Frames { get; set; }     public string Comment { get; set; }       public RoleLifecycle()     {     }       public RoleLifecycle(string roleName)     {         PartitionKey = roleName;         RowKey = Utils.GetAscendingRowKey();         Status = "Started";         StartTime = DateTime.UtcNow;         LastActiveTime = StartTime;         EndTime = StartTime;         SecondsRunning = 0;         Frames = 0;     } }     A new instance of this class is created and added to the storage table when the role starts. It is then updated each time the worker renders a frame to record the total number of frames rendered and the total processing time. These statistics are used be the monitoring application to determine the effectiveness of use of resources in the render farm. Rendering the Animation The Azure solution was deployed to Windows Azure with the service configuration set to 16 worker role instances. This allows for the application to be tested in the cloud environment, and the performance of the application determined. When I demo the application at conferences and user groups I often start with 16 instances, and then scale up the application to the full 256 instances. The configuration to run 16 instances is shown below. <?xml version="1.0" encoding="utf-8"?> <ServiceConfiguration serviceName="CloudRay" xmlns="http://schemas.microsoft.com/ServiceHosting/2008/10/ServiceConfiguration" osFamily="1" osVersion="*">   <Role name="CloudRayWorkerRole">     <Instances count="16" />     <ConfigurationSettings>       <Setting name="DataConnectionString"         value="DefaultEndpointsProtocol=https;AccountName=cloudraydata;AccountKey=..." />     </ConfigurationSettings>   </Role> </ServiceConfiguration>     About six minutes after deploying the application the first worker roles become active and start to render the first frames of the animation. The CloudRay Monitor application displays an icon for each worker role instance, with a number indicating the number of frames that the worker role has rendered. The statistics on the left show the number of active worker roles and statistics about the render process. The render time is the time since the first worker role became active; the CPU time is the total amount of processing time used by all worker role instances to render the frames.   Five minutes after the first worker role became active the last of the 16 worker roles activated. By this time the first seven worker roles had each rendered one frame of the animation.   With 16 worker roles u and running it can be seen that one hour and 45 minutes CPU time has been used to render 32 frames with a render time of just under 10 minutes.     At this rate it would take over 10 hours to render the 2,000 frames of the full animation. In order to complete the animation in under an hour more processing power will be required. Scaling the render farm from 16 instances to 256 instances is easy using the new management portal. The slider is set to 256 instances, and the configuration saved. We do not need to re-deploy the application, and the 16 instances that are up and running will not be affected. Alternatively, the configuration file for the Azure service could be modified to specify 256 instances.   <?xml version="1.0" encoding="utf-8"?> <ServiceConfiguration serviceName="CloudRay" xmlns="http://schemas.microsoft.com/ServiceHosting/2008/10/ServiceConfiguration" osFamily="1" osVersion="*">   <Role name="CloudRayWorkerRole">     <Instances count="256" />     <ConfigurationSettings>       <Setting name="DataConnectionString"         value="DefaultEndpointsProtocol=https;AccountName=cloudraydata;AccountKey=..." />     </ConfigurationSettings>   </Role> </ServiceConfiguration>     Six minutes after the new configuration has been applied 75 new worker roles have activated and are processing their first frames.   Five minutes later the full configuration of 256 worker roles is up and running. We can see that the average rate of frame rendering has increased from 3 to 12 frames per minute, and that over 17 hours of CPU time has been utilized in 23 minutes. In this test the time to provision 140 worker roles was about 11 minutes, which works out at about one every five seconds.   We are now half way through the rendering, with 1,000 frames complete. This has utilized just under three days of CPU time in a little over 35 minutes.   The animation is now complete, with 2,000 frames rendered in a little over 52 minutes. The CPU time used by the 256 worker roles is 6 days, 7 hours and 22 minutes with an average frame rate of 38 frames per minute. The rendering of the last 1,000 frames took 16 minutes 27 seconds, which works out at a rendering rate of 60 frames per minute. The frame counts in the server instances indicate that the use of a queue to distribute the workload has been very effective in distributing the load across the 256 worker role instances. The first 16 instances that were deployed first have rendered between 11 and 13 frames each, whilst the 240 instances that were added when the application was scaled have rendered between 6 and 9 frames each.   Completed Animation I’ve uploaded the completed animation to YouTube, a low resolution preview is shown below. Pin Board Animation Created using Windows Kinect and 256 Windows Azure Worker Roles   The animation can be viewed in 1280x720 resolution at the following link: http://www.youtube.com/watch?v=n5jy6bvSxWc Effective Use of Resources According to the CloudRay monitor statistics the animation took 6 days, 7 hours and 22 minutes CPU to render, this works out at 152 hours of compute time, rounded up to the nearest hour. As the usage for the worker role instances are billed for the full hour, it may have been possible to render the animation using fewer than 256 worker roles. When deciding the optimal usage of resources, the time required to provision and start the worker roles must also be considered. In the demo I started with 16 worker roles, and then scaled the application to 256 worker roles. It would have been more optimal to start the application with maybe 200 worker roles, and utilized the full hour that I was being billed for. This would, however, have prevented showing the ease of scalability of the application. The new management portal displays the CPU usage across the worker roles in the deployment. The average CPU usage across all instances is 93.27%, with over 99% used when all the instances are up and running. This shows that the worker role resources are being used very effectively. Grid Computing Scenarios Although I am using this scenario for a hobby project, there are many scenarios where a large amount of compute power is required for a short period of time. Windows Azure provides a great platform for developing these types of grid computing applications, and can work out very cost effective. ·         Windows Azure can provide massive compute power, on demand, in a matter of minutes. ·         The use of queues to manage the load balancing of jobs between role instances is a simple and effective solution. ·         Using a cloud-computing platform like Windows Azure allows proof-of-concept scenarios to be tested and evaluated on a very low budget. ·         No charges for inbound data transfer makes the uploading of large data sets to Windows Azure Storage services cost effective. (Transaction charges still apply.) Tips for using Windows Azure for Grid Computing Scenarios I found the implementation of a render farm using Windows Azure a fairly simple scenario to implement. I was impressed by ease of scalability that Azure provides, and by the short time that the application took to scale from 16 to 256 worker role instances. In this case it was around 13 minutes, in other tests it took between 10 and 20 minutes. The following tips may be useful when implementing a grid computing project in Windows Azure. ·         Using an Azure Storage queue to load-balance the units of work across multiple worker roles is simple and very effective. The design I have used in this scenario could easily scale to many thousands of worker role instances. ·         Windows Azure accounts are typically limited to 20 cores. If you need to use more than this, a call to support and a credit card check will be required. ·         Be aware of how the billing model works. You will be charged for worker role instances for the full clock our in which the instance is deployed. Schedule the workload to start just after the clock hour has started. ·         Monitor the utilization of the resources you are provisioning, ensure that you are not paying for worker roles that are idle. ·         If you are deploying third party applications to worker roles, you may well run into licensing issues. Purchasing software licenses on a per-processor basis when using hundreds of processors for a short time period would not be cost effective. ·         Third party software may also require installation onto the worker roles, which can be accomplished using start-up tasks. Bear in mind that adding a startup task and possible re-boot will add to the time required for the worker role instance to start and activate. An alternative may be to use a prepared VM and use VM roles. ·         Consider using the Windows Azure Autoscaling Application Block (WASABi) to autoscale the worker roles in your application. When using a large number of worker roles, the utilization must be carefully monitored, if the scaling algorithms are not optimal it could get very expensive!

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• SOA 10g Developing a Simple Hello World Process

  - by [email protected]

  Softwares & Hardware Needed Intel Pentium D CPU 3 GHz, 2 GB RAM, Windows XP System ( Thats what i am using ) You could as well use Linux , but please choose High End RAM 10G SOA Suite from Oracle(TM) , Read Installation documents at www.Oracle.com J Developer 10.1.3.3 Official Documents at http://www.oracle.com/technology/products/ias/bpel/index.html java -version Java HotSpot(TM) Client VM (build 1.5.0_06-b05, mixed mode)BPEL Introduction - Developing a Simple Hello World Process  Synchronous BPEL Process      This Exercise focuses on developing a Synchronous Process, which mean you give input to the BPEL Process you get output immediately no waiting at all. The Objective of this exercise is to give input as name and it greets with Hello Appended by that name example, if I give input as "James" the BPEL process returns "Hello James". 1. Open the Oracle JDeveloper click on File -> New Application give the name "JamesApp" you can give your own name if it pleases you. Select the folder where you want to place the application. Click "OK" 2. Right Click on the "JamesApp" in the Application Navigator, Select New Menu. 3. Select "Projects" under "General" and "BPEL Process Project", click "OK" these steps remain same for all BPEL Projects 4. Project Setting Wizard Appears, Give the "Process Name" as "MyBPELProc" and Namespace as http://xmlns.james.com/ MyBPELProc, Select Template as "Synchronous BPEL Process click "Next" 5. Accept the input and output schema names as it is, click "Finish" 6. You would see the BPEL Process Designer, some of the folders such as Integration content and Resources are created and few more files 7. Assign Activity : Allows Assigning values to variables or copying values of one variable to another and also do some string manipulation or mathematical operations In the component palette at extreme right, select Process Activities from the drop down, and drag and drop "Assign" between "receive Input" and "replyOutput" 8. You can right click and edit the Assign activity and give any suitable name "AssignHello", 9. Select "Copy Operation" Tab create "Copy Operation" 10. In the From variables click on expression builder, select input under "input variable", Click on insert into expression bar, complete the concat syntax, Note to use "Ctrl+space bar" inside expression window to Auto Populate the expression as shown in the figure below. What we are actually doing here is concatenating the String "Hello ", with the variable value received through the variable named "input" 11. Observe that once an expression is completed the "To Variable" is assigned to a variable by name "result" 12. Finally the copy variable looks as below 13. It's the time to deploy, start the SOA Suite 14. Establish connection to the Server from JDeveloper, this can be done adding a New Application Server under Connection, give the server name, username and password and test connection. 15. Deploy the "MyBPELProc" to the "default domain" 16. http://localhost:8080/ allows connecting to SOA Suite web portal, click on "BPEL Control" , login with the username "oc4jadmin" password what ever you gave during installation 17. "MyBPELProc" is visisble under "Deployed BPEL Processes" in the "Dashboard" Tab, click on the it 18. Initiate tab open to accept input, enter data such as input is "James" click on "Post XML Button" 19. Click on Visual Flow 20. Click on receive Input , it shows "James" as input received 21. Click on reply Output, it shows "Hello James" so the BPEL process is successfully executed. 22. It may be worth seeing all the instance created everytime a BPEL process is executed by giving some inputs. Purge All button allows to delete all the unwanted previous instances of BPEL process, dont worry it wont delete the BPEL process itself :-) 23. It may also be some importance to understand the XSD File which holds input & output variable names & data types. 24. You could drag n drop variables as elements over sequence at the designer or directly edit the XML Source file. 

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• TCP RST right after FIN/ACK

  - by Nitzan Shaked

  I am having the weirdest issue: I have a web server which sometimes, only on very specific requests, will send a RST to the client after having sent the FIN datagram. First, a description of the setup: The server runs on an Ubuntu 12.04.1 LTS, which itself is a VM guest inside a Win7 x64 host, in bridged mode. ufw is disabled on the host The client runs on a iOS simulator, which runs on OS X Mountain Lion, which is a VM guest (hackintosh) inside a Win7 x64 host, in bridged mode. Both client and server are on the same LAN, one is connected to the home router via an Ethernet cable, and then other thru WiFi. I happened to glimpse over the server's http logs and found that the client sometimes issuing multiple subsequent identical requests. Further investigation led me to discover that this happens when the server sends a RST, and that the client is simply re-trying. I am attaching several tcpdump's: Good1 is the server-side tcpdump of a good session ("good" meaning no RST was generated). Good3 is another sever-side tcpdump of a good session. (The difference between Good1 and Good3 is the order in which ACK's were sent from the server to the client, ACK'ing the client's request. The client's request arives in 2 segements (specifically: one for the http headers, and another for a body containing an empty json object, "{}"). In Good1, the server ACK's both request segments, using 2 ACK segments, after the second request has arrived. In Good3, the server ACK's each request segment with an ACK segment as soon as the request segment arrives. Not that it should make a difference.) Bad1 is a dump, both client- and server-side, of a bad session. Bad2 is another bad session, this time server-side only. Note that in all "bad" sessions, the server ACK's each request segments immediately after having received it. I've looked at a few other bad sessions, and the situation is the same in all of them. But this is also the behavior in "Good3", so I don't see how that observation helps me, of for that matter why it should matter. I can't find any difference between good and bad sessions, or at least one that I think should matter. My question is: why are those RST's being generated? Or at least: how do I go about debugging this, or providing more info here that'll help? Edit 2 new facts that I have learned: Section 4.2.2.13 of the RFC (1122) (and Wikipedia, in the article "TCP", under "Connection Termination") says that a TCP application on one host may close the connection before it has read all of the data in its socket buffer, and in such a case the TCP on the host will sent a RST to the other side, to let it know that not all the data it has sent has been read. I'm not sure I completely understand this, since closing my side of the connection still allows me to read, no? It also means that I can't write any more. I am not sure this is relevant, though, since I see a RST after FIN. There are multiple complaints of this happening with wsgiref (Python's dev-mode HTTP server), which is exactly what I'm using. I'll keep updating as I find out more. Thanks! ~~~~~~~~~~~~~~~~~~~~ Good1 -- Server Side ~~~~~~~~~~~~~~~~~~~~ 13:28:02.308319 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [S], seq 94268074, win 65535, options [mss 1460,nop,wscale 4,nop,nop,TS val 943308864 ecr 0,sackOK,eol], length 0 13:28:02.308336 IP 192.168.1.132.5000 > 192.168.1.51.51479: Flags [S.], seq 1726304574, ack 94268075, win 14480, options [mss 1460,sackOK,TS val 326480982 ecr 943308864,nop,wscale 3], length 0 13:28:02.309750 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [.], ack 1, win 8235, options [nop,nop,TS val 943308865 ecr 326480982], length 0 13:28:02.310744 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [P.], seq 1:351, ack 1, win 8235, options [nop,nop,TS val 943308865 ecr 326480982], length 350 13:28:02.310766 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [P.], seq 351:353, ack 1, win 8235, options [nop,nop,TS val 943308865 ecr 326480982], length 2 13:28:02.310841 IP 192.168.1.132.5000 > 192.168.1.51.51479: Flags [.], ack 351, win 1944, options [nop,nop,TS val 326480983 ecr 943308865], length 0 13:28:02.310918 IP 192.168.1.132.5000 > 192.168.1.51.51479: Flags [.], ack 353, win 1944, options [nop,nop,TS val 326480983 ecr 943308865], length 0 13:28:02.315931 IP 192.168.1.132.5000 > 192.168.1.51.51479: Flags [P.], seq 1:18, ack 353, win 1944, options [nop,nop,TS val 326480984 ecr 943308865], length 17 13:28:02.316107 IP 192.168.1.132.5000 > 192.168.1.51.51479: Flags [FP.], seq 18:684, ack 353, win 1944, options [nop,nop,TS val 326480984 ecr 943308865], length 666 13:28:02.317651 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [.], ack 18, win 8234, options [nop,nop,TS val 943308872 ecr 326480984], length 0 13:28:02.318288 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [.], ack 685, win 8192, options [nop,nop,TS val 943308872 ecr 326480984], length 0 13:28:02.318640 IP 192.168.1.51.51479 > 192.168.1.132.5000: Flags [F.], seq 353, ack 685, win 8192, options [nop,nop,TS val 943308872 ecr 326480984], length 0 13:28:02.318651 IP 192.168.1.132.5000 > 192.168.1.51.51479: Flags [.], ack 354, win 1944, options [nop,nop,TS val 326480985 ecr 943308872], length 0 ~~~~~~~~~~~~~~~~~~~~ Good3 -- Server Side ~~~~~~~~~~~~~~~~~~~~ 13:28:03.311143 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [S], seq 1982901126, win 65535, options [mss 1460,nop,wscale 4,nop,nop,TS val 943309853 ecr 0,sackOK,eol], length 0 13:28:03.311155 IP 192.168.1.132.5000 > 192.168.1.51.51486: Flags [S.], seq 2245063571, ack 1982901127, win 14480, options [mss 1460,sackOK,TS val 326481233 ecr 943309853,nop,wscale 3], length 0 13:28:03.312671 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [.], ack 1, win 8235, options [nop,nop,TS val 943309854 ecr 326481233], length 0 13:28:03.313330 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [P.], seq 1:351, ack 1, win 8235, options [nop,nop,TS val 943309855 ecr 326481233], length 350 13:28:03.313337 IP 192.168.1.132.5000 > 192.168.1.51.51486: Flags [.], ack 351, win 1944, options [nop,nop,TS val 326481234 ecr 943309855], length 0 13:28:03.313342 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [P.], seq 351:353, ack 1, win 8235, options [nop,nop,TS val 943309855 ecr 326481233], length 2 13:28:03.313346 IP 192.168.1.132.5000 > 192.168.1.51.51486: Flags [.], ack 353, win 1944, options [nop,nop,TS val 326481234 ecr 943309855], length 0 13:28:03.327942 IP 192.168.1.132.5000 > 192.168.1.51.51486: Flags [P.], seq 1:18, ack 353, win 1944, options [nop,nop,TS val 326481237 ecr 943309855], length 17 13:28:03.328253 IP 192.168.1.132.5000 > 192.168.1.51.51486: Flags [FP.], seq 18:684, ack 353, win 1944, options [nop,nop,TS val 326481237 ecr 943309855], length 666 13:28:03.329076 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [.], ack 18, win 8234, options [nop,nop,TS val 943309868 ecr 326481237], length 0 13:28:03.329688 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [.], ack 685, win 8192, options [nop,nop,TS val 943309868 ecr 326481237], length 0 13:28:03.330361 IP 192.168.1.51.51486 > 192.168.1.132.5000: Flags [F.], seq 353, ack 685, win 8192, options [nop,nop,TS val 943309869 ecr 326481237], length 0 13:28:03.330370 IP 192.168.1.132.5000 > 192.168.1.51.51486: Flags [.], ack 354, win 1944, options [nop,nop,TS val 326481238 ecr 943309869], length 0 ~~~~~~~~~~~~~~~~~~~~ Bad1 -- Server Side ~~~~~~~~~~~~~~~~~~~~ 13:28:01.311876 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [S], seq 920400580, win 65535, options [mss 1460,nop,wscale 4,nop,nop,TS val 943307883 ecr 0,sackOK,eol], length 0 13:28:01.311896 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [S.], seq 3103085782, ack 920400581, win 14480, options [mss 1460,sackOK,TS val 326480733 ecr 943307883,nop,wscale 3], length 0 13:28:01.313509 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [.], ack 1, win 8235, options [nop,nop,TS val 943307884 ecr 326480733], length 0 13:28:01.315614 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [P.], seq 1:351, ack 1, win 8235, options [nop,nop,TS val 943307886 ecr 326480733], length 350 13:28:01.315727 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [.], ack 351, win 1944, options [nop,nop,TS val 326480734 ecr 943307886], length 0 13:28:01.316229 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [P.], seq 351:353, ack 1, win 8235, options [nop,nop,TS val 943307886 ecr 326480733], length 2 13:28:01.316242 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [.], ack 353, win 1944, options [nop,nop,TS val 326480734 ecr 943307886], length 0 13:28:01.321019 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [P.], seq 1:18, ack 353, win 1944, options [nop,nop,TS val 326480735 ecr 943307886], length 17 13:28:01.321294 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [FP.], seq 18:684, ack 353, win 1944, options [nop,nop,TS val 326480736 ecr 943307886], length 666 13:28:01.321386 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [R.], seq 685, ack 353, win 1944, options [nop,nop,TS val 326480736 ecr 943307886], length 0 13:28:01.322727 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [.], ack 18, win 8234, options [nop,nop,TS val 943307891 ecr 326480735], length 0 13:28:01.322733 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [R], seq 3103085800, win 0, length 0 13:28:01.323221 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [.], ack 685, win 8192, options [nop,nop,TS val 943307892 ecr 326480736], length 0 13:28:01.323231 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [R], seq 3103086467, win 0, length 0 ~~~~~~~~~~~~~~~~~~~~ Bad1 -- Client Side ~~~~~~~~~~~~~~~~~~~~ 13:28:11.374654 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [S], seq 920400580, win 65535, options [mss 1460,nop,wscale 4,nop,nop,TS val 943307883 ecr 0,sackOK,eol], length 0 13:28:11.375764 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [S.], seq 3103085782, ack 920400581, win 14480, options [mss 1460,sackOK,TS val 326480733 ecr 943307883,nop,wscale 3], length 0 13:28:11.376352 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [.], ack 1, win 8235, options [nop,nop,TS val 943307884 ecr 326480733], length 0 13:28:11.378252 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [P.], seq 1:351, ack 1, win 8235, options [nop,nop,TS val 943307886 ecr 326480733], length 350 13:28:11.379027 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [P.], seq 351:353, ack 1, win 8235, options [nop,nop,TS val 943307886 ecr 326480733], length 2 13:28:11.379732 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [.], ack 351, win 1944, options [nop,nop,TS val 326480734 ecr 943307886], length 0 13:28:11.380592 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [.], ack 353, win 1944, options [nop,nop,TS val 326480734 ecr 943307886], length 0 13:28:11.384968 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [P.], seq 1:18, ack 353, win 1944, options [nop,nop,TS val 326480735 ecr 943307886], length 17 13:28:11.385044 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [.], ack 18, win 8234, options [nop,nop,TS val 943307891 ecr 326480735], length 0 13:28:11.385586 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [FP.], seq 18:684, ack 353, win 1944, options [nop,nop,TS val 326480736 ecr 943307886], length 666 13:28:11.385743 IP 192.168.1.51.51472 > 192.168.1.132.5000: Flags [.], ack 685, win 8192, options [nop,nop,TS val 943307892 ecr 326480736], length 0 13:28:11.385966 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [R.], seq 685, ack 353, win 1944, options [nop,nop,TS val 326480736 ecr 943307886], length 0 13:28:11.387343 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [R], seq 3103085800, win 0, length 0 13:28:11.387344 IP 192.168.1.132.5000 > 192.168.1.51.51472: Flags [R], seq 3103086467, win 0, length 0 ~~~~~~~~~~~~~~~~~~~~ Bad2 -- Server Side ~~~~~~~~~~~~~~~~~~~~ 13:28:01.319185 IP 192.168.1.51.51473 > 192.168.1.132.5000: Flags [S], seq 1631526992, win 65535, options [mss 1460,nop,wscale 4,nop,nop,TS val 943307889 ecr 0,sackOK,eol], length 0 13:28:01.319197 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [S.], seq 2524685719, ack 1631526993, win 14480, options [mss 1460,sackOK,TS val 326480735 ecr 943307889,nop,wscale 3], length 0 13:28:01.320692 IP 192.168.1.51.51473 > 192.168.1.132.5000: Flags [.], ack 1, win 8235, options [nop,nop,TS val 943307890 ecr 326480735], length 0 13:28:01.322219 IP 192.168.1.51.51473 > 192.168.1.132.5000: Flags [P.], seq 1:351, ack 1, win 8235, options [nop,nop,TS val 943307890 ecr 326480735], length 350 13:28:01.322336 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [.], ack 351, win 1944, options [nop,nop,TS val 326480736 ecr 943307890], length 0 13:28:01.322689 IP 192.168.1.51.51473 > 192.168.1.132.5000: Flags [P.], seq 351:353, ack 1, win 8235, options [nop,nop,TS val 943307890 ecr 326480735], length 2 13:28:01.322700 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [.], ack 353, win 1944, options [nop,nop,TS val 326480736 ecr 943307890], length 0 13:28:01.326307 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [P.], seq 1:18, ack 353, win 1944, options [nop,nop,TS val 326480737 ecr 943307890], length 17 13:28:01.326614 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [FP.], seq 18:684, ack 353, win 1944, options [nop,nop,TS val 326480737 ecr 943307890], length 666 13:28:01.326710 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [R.], seq 685, ack 353, win 1944, options [nop,nop,TS val 326480737 ecr 943307890], length 0 13:28:01.328499 IP 192.168.1.51.51473 > 192.168.1.132.5000: Flags [.], ack 18, win 8234, options [nop,nop,TS val 943307896 ecr 326480737], length 0 13:28:01.328509 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [R], seq 2524685737, win 0, length 0 13:28:01.328514 IP 192.168.1.51.51473 > 192.168.1.132.5000: Flags [.], ack 685, win 8192, options [nop,nop,TS val 943307896 ecr 326480737], length 0 13:28:01.328517 IP 192.168.1.132.5000 > 192.168.1.51.51473: Flags [R], seq 2524686404, win 0, length 0

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• How to read oom-killer syslog messages?

  - by Grant

  I have a Ubuntu 12.04 server which sometimes dies completely - no SSH, no ping, nothing until it is physically rebooted. After the reboot, I see in syslog that the oom-killer killed, well, pretty much everything. There's a lot of detailed memory usage information in them. How do I read these logs to see what caused the OOM issue? The server has far more memory than it needs, so it shouldn't be running out of memory. Oct 25 07:28:04 nldedip4k031 kernel: [87946.529511] oom_kill_process: 9 callbacks suppressed Oct 25 07:28:04 nldedip4k031 kernel: [87946.529514] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529516] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529518] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:04 nldedip4k031 kernel: [87946.529519] Call Trace: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529525] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529528] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529530] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529532] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529535] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529537] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529541] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529543] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529546] [] vfs_read+0x8c/0x160 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529548] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529550] [] sys_read+0x3d/0x70 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529554] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529555] Mem-Info: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529556] DMA per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529557] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529558] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529560] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529561] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529562] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529563] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529564] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529565] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529566] Normal per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529567] CPU 0: hi: 186, btch: 31 usd: 179 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529568] CPU 1: hi: 186, btch: 31 usd: 182 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529569] CPU 2: hi: 186, btch: 31 usd: 132 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529570] CPU 3: hi: 186, btch: 31 usd: 175 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529571] CPU 4: hi: 186, btch: 31 usd: 91 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529572] CPU 5: hi: 186, btch: 31 usd: 173 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529573] CPU 6: hi: 186, btch: 31 usd: 159 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529574] CPU 7: hi: 186, btch: 31 usd: 164 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529575] HighMem per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529576] CPU 0: hi: 186, btch: 31 usd: 165 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529577] CPU 1: hi: 186, btch: 31 usd: 183 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529578] CPU 2: hi: 186, btch: 31 usd: 185 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529579] CPU 3: hi: 186, btch: 31 usd: 138 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529580] CPU 4: hi: 186, btch: 31 usd: 155 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529581] CPU 5: hi: 186, btch: 31 usd: 104 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529582] CPU 6: hi: 186, btch: 31 usd: 133 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529583] CPU 7: hi: 186, btch: 31 usd: 170 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529586] active_anon:5523 inactive_anon:354 isolated_anon:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529586] active_file:2815 inactive_file:6849119 isolated_file:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529587] unevictable:0 dirty:449 writeback:10 unstable:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529587] free:1304125 slab_reclaimable:104672 slab_unreclaimable:3419 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529588] mapped:2661 shmem:138 pagetables:313 bounce:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529591] DMA free:4252kB min:780kB low:972kB high:1168kB active_anon:0kB inactive_anon:0kB active_file:4kB inactive_file:0kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15756kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:11564kB slab_unreclaimable:4kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:1 all_unreclaimable? yes Oct 25 07:28:04 nldedip4k031 kernel: [87946.529594] lowmem_reserve[]: 0 869 32460 32460 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529599] Normal free:44052kB min:44216kB low:55268kB high:66324kB active_anon:0kB inactive_anon:0kB active_file:616kB inactive_file:568kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:890008kB mlocked:0kB dirty:0kB writeback:0kB mapped:4kB shmem:0kB slab_reclaimable:407124kB slab_unreclaimable:13672kB kernel_stack:992kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:2083 all_unreclaimable? yes Oct 25 07:28:04 nldedip4k031 kernel: [87946.529602] lowmem_reserve[]: 0 0 252733 252733 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529606] HighMem free:5168196kB min:512kB low:402312kB high:804112kB active_anon:22092kB inactive_anon:1416kB active_file:10640kB inactive_file:27395920kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:32349872kB mlocked:0kB dirty:1796kB writeback:40kB mapped:10640kB shmem:552kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:1252kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Oct 25 07:28:04 nldedip4k031 kernel: [87946.529609] lowmem_reserve[]: 0 0 0 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529611] DMA: 6*4kB 6*8kB 6*16kB 5*32kB 5*64kB 4*128kB 2*256kB 1*512kB 0*1024kB 1*2048kB 0*4096kB = 4232kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529616] Normal: 297*4kB 180*8kB 119*16kB 73*32kB 67*64kB 47*128kB 35*256kB 13*512kB 5*1024kB 1*2048kB 1*4096kB = 44052kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529622] HighMem: 1*4kB 6*8kB 27*16kB 11*32kB 2*64kB 1*128kB 0*256kB 0*512kB 4*1024kB 1*2048kB 1260*4096kB = 5168196kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529627] 6852076 total pagecache pages Oct 25 07:28:04 nldedip4k031 kernel: [87946.529628] 0 pages in swap cache Oct 25 07:28:04 nldedip4k031 kernel: [87946.529629] Swap cache stats: add 0, delete 0, find 0/0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529630] Free swap = 3998716kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529631] Total swap = 3998716kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.571914] 8437743 pages RAM Oct 25 07:28:04 nldedip4k031 kernel: [87946.571916] 8209409 pages HighMem Oct 25 07:28:04 nldedip4k031 kernel: [87946.571917] 159556 pages reserved Oct 25 07:28:04 nldedip4k031 kernel: [87946.571917] 6862034 pages shared Oct 25 07:28:04 nldedip4k031 kernel: [87946.571918] 123540 pages non-shared Oct 25 07:28:04 nldedip4k031 kernel: [87946.571919] [ pid ] uid tgid total_vm rss cpu oom_adj oom_score_adj name Oct 25 07:28:04 nldedip4k031 kernel: [87946.571927] [ 421] 0 421 709 152 3 0 0 upstart-udev-br Oct 25 07:28:04 nldedip4k031 kernel: [87946.571929] [ 429] 0 429 773 326 5 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571931] [ 567] 0 567 772 224 4 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571932] [ 568] 0 568 772 231 7 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571934] [ 764] 0 764 712 103 1 0 0 upstart-socket- Oct 25 07:28:04 nldedip4k031 kernel: [87946.571936] [ 772] 103 772 815 164 5 0 0 dbus-daemon Oct 25 07:28:04 nldedip4k031 kernel: [87946.571938] [ 785] 0 785 1671 600 1 -17 -1000 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571940] [ 809] 101 809 7766 380 1 0 0 rsyslogd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571942] [ 869] 0 869 1158 213 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571943] [ 873] 0 873 1158 214 6 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571945] [ 911] 0 911 1158 215 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571947] [ 912] 0 912 1158 214 2 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571949] [ 914] 0 914 1158 213 1 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571950] [ 916] 0 916 618 86 1 0 0 atd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571952] [ 917] 0 917 655 226 3 0 0 cron Oct 25 07:28:04 nldedip4k031 kernel: [87946.571954] [ 948] 0 948 902 159 3 0 0 irqbalance Oct 25 07:28:04 nldedip4k031 kernel: [87946.571956] [ 993] 0 993 1145 363 3 0 0 master Oct 25 07:28:04 nldedip4k031 kernel: [87946.571957] [ 1002] 104 1002 1162 333 1 0 0 qmgr Oct 25 07:28:04 nldedip4k031 kernel: [87946.571959] [ 1016] 0 1016 730 149 2 0 0 mdadm Oct 25 07:28:04 nldedip4k031 kernel: [87946.571961] [ 1057] 0 1057 6066 2160 3 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571963] [ 1086] 0 1086 1158 213 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571965] [ 1088] 33 1088 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571967] [ 1089] 33 1089 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571969] [ 1090] 33 1090 6175 1451 3 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571971] [ 1091] 33 1091 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571972] [ 1092] 33 1092 6191 1451 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571974] [ 1109] 33 1109 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571976] [ 1151] 33 1151 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571978] [ 1201] 104 1201 1803 652 1 0 0 tlsmgr Oct 25 07:28:04 nldedip4k031 kernel: [87946.571980] [ 2475] 0 2475 2435 812 0 0 0 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571982] [ 2494] 0 2494 1745 839 1 0 0 bash Oct 25 07:28:04 nldedip4k031 kernel: [87946.571984] [ 2573] 0 2573 3394 1689 0 0 0 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571986] [ 2589] 0 2589 5014 457 3 0 0 rsync Oct 25 07:28:04 nldedip4k031 kernel: [87946.571988] [ 2590] 0 2590 7970 522 1 0 0 rsync Oct 25 07:28:04 nldedip4k031 kernel: [87946.571990] [ 2652] 104 2652 1150 326 5 0 0 pickup Oct 25 07:28:04 nldedip4k031 kernel: [87946.571992] Out of memory: Kill process 421 (upstart-udev-br) score 1 or sacrifice child Oct 25 07:28:04 nldedip4k031 kernel: [87946.572407] Killed process 421 (upstart-udev-br) total-vm:2836kB, anon-rss:156kB, file-rss:452kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.573107] init: upstart-udev-bridge main process (421) killed by KILL signal Oct 25 07:28:04 nldedip4k031 kernel: [87946.573126] init: upstart-udev-bridge main process ended, respawning Oct 25 07:28:34 nldedip4k031 kernel: [87976.461570] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461573] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461576] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:34 nldedip4k031 kernel: [87976.461578] Call Trace: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461585] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461588] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461591] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461595] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461599] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461602] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461606] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461609] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461613] [] vfs_read+0x8c/0x160 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461616] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461619] [] sys_read+0x3d/0x70 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461624] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461626] Mem-Info: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461628] DMA per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461629] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461631] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461633] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461634] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461636] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461638] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461639] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461641] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461642] Normal per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461644] CPU 0: hi: 186, btch: 31 usd: 61 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461646] CPU 1: hi: 186, btch: 31 usd: 49 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461647] CPU 2: hi: 186, btch: 31 usd: 8 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461649] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461651] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461652] CPU 5: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461654] CPU 6: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461656] CPU 7: hi: 186, btch: 31 usd: 30 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461657] HighMem per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461658] CPU 0: hi: 186, btch: 31 usd: 4 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461660] CPU 1: hi: 186, btch: 31 usd: 204 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461662] CPU 2: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461663] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461665] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461667] CPU 5: hi: 186, btch: 31 usd: 31 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461668] CPU 6: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461670] CPU 7: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461674] active_anon:5441 inactive_anon:412 isolated_anon:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461674] active_file:2668 inactive_file:6922842 isolated_file:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461675] unevictable:0 dirty:836 writeback:0 unstable:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461676] free:1231664 slab_reclaimable:105781 slab_unreclaimable:3399 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461677] mapped:2649 shmem:138 pagetables:313 bounce:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461682] DMA free:4248kB min:780kB low:972kB high:1168kB active_anon:0kB inactive_anon:0kB active_file:0kB inactive_file:4kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15756kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:11560kB slab_unreclaimable:4kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:5687 all_unreclaimable? yes Oct 25 07:28:34 nldedip4k031 kernel: [87976.461686] lowmem_reserve[]: 0 869 32460 32460 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461693] Normal free:44184kB min:44216kB low:55268kB high:66324kB active_anon:0kB inactive_anon:0kB active_file:20kB inactive_file:1096kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:890008kB mlocked:0kB dirty:4kB writeback:0kB mapped:4kB shmem:0kB slab_reclaimable:411564kB slab_unreclaimable:13592kB kernel_stack:992kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:1816 all_unreclaimable? yes Oct 25 07:28:34 nldedip4k031 kernel: [87976.461697] lowmem_reserve[]: 0 0 252733 252733 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461703] HighMem free:4878224kB min:512kB low:402312kB high:804112kB active_anon:21764kB inactive_anon:1648kB active_file:10652kB inactive_file:27690268kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:32349872kB mlocked:0kB dirty:3340kB writeback:0kB mapped:10592kB shmem:552kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:1252kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Oct 25 07:28:34 nldedip4k031 kernel: [87976.461708] lowmem_reserve[]: 0 0 0 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461711] DMA: 8*4kB 7*8kB 6*16kB 5*32kB 5*64kB 4*128kB 2*256kB 1*512kB 0*1024kB 1*2048kB 0*4096kB = 4248kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461719] Normal: 272*4kB 178*8kB 76*16kB 52*32kB 42*64kB 36*128kB 23*256kB 20*512kB 7*1024kB 2*2048kB 1*4096kB = 44176kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461727] HighMem: 1*4kB 45*8kB 31*16kB 24*32kB 5*64kB 3*128kB 1*256kB 2*512kB 4*1024kB 2*2048kB 1188*4096kB = 4877852kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461736] 6925679 total pagecache pages Oct 25 07:28:34 nldedip4k031 kernel: [87976.461737] 0 pages in swap cache Oct 25 07:28:34 nldedip4k031 kernel: [87976.461739] Swap cache stats: add 0, delete 0, find 0/0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461740] Free swap = 3998716kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461741] Total swap = 3998716kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.524951] 8437743 pages RAM Oct 25 07:28:34 nldedip4k031 kernel: [87976.524953] 8209409 pages HighMem Oct 25 07:28:34 nldedip4k031 kernel: [87976.524954] 159556 pages reserved Oct 25 07:28:34 nldedip4k031 kernel: [87976.524955] 6936141 pages shared Oct 25 07:28:34 nldedip4k031 kernel: [87976.524956] 124602 pages non-shared Oct 25 07:28:34 nldedip4k031 kernel: [87976.524957] [ pid ] uid tgid total_vm rss cpu oom_adj oom_score_adj name Oct 25 07:28:34 nldedip4k031 kernel: [87976.524966] [ 429] 0 429 773 326 5 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524968] [ 567] 0 567 772 224 4 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524971] [ 568] 0 568 772 231 7 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524973] [ 764] 0 764 712 103 3 0 0 upstart-socket- Oct 25 07:28:34 nldedip4k031 kernel: [87976.524976] [ 772] 103 772 815 164 2 0 0 dbus-daemon Oct 25 07:28:34 nldedip4k031 kernel: [87976.524979] [ 785] 0 785 1671 600 1 -17 -1000 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524981] [ 809] 101 809 7766 380 1 0 0 rsyslogd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524983] [ 869] 0 869 1158 213 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524986] [ 873] 0 873 1158 214 6 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524988] [ 911] 0 911 1158 215 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524990] [ 912] 0 912 1158 214 2 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524992] [ 914] 0 914 1158 213 1 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524995] [ 916] 0 916 618 86 1 0 0 atd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524997] [ 917] 0 917 655 226 3 0 0 cron Oct 25 07:28:34 nldedip4k031 kernel: [87976.524999] [ 948] 0 948 902 159 5 0 0 irqbalance Oct 25 07:28:34 nldedip4k031 kernel: [87976.525002] [ 993] 0 993 1145 363 3 0 0 master Oct 25 07:28:34 nldedip4k031 kernel: [87976.525004] [ 1002] 104 1002 1162 333 1 0 0 qmgr Oct 25 07:28:34 nldedip4k031 kernel: [87976.525007] [ 1016] 0 1016 730 149 2 0 0 mdadm Oct 25 07:28:34 nldedip4k031 kernel: [87976.525009] [ 1057] 0 1057 6066 2160 3 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525012] [ 1086] 0 1086 1158 213 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.525014] [ 1088] 33 1088 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525017] [ 1089] 33 1089 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525019] [ 1090] 33 1090 6175 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525021] [ 1091] 33 1091 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525024] [ 1092] 33 1092 6191 1451 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525026] [ 1109] 33 1109 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525029] [ 1151] 33 1151 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525031] [ 1201] 104 1201 1803 652 1 0 0 tlsmgr Oct 25 07:28:34 nldedip4k031 kernel: [87976.525033] [ 2475] 0 2475 2435 812 0 0 0 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.525036] [ 2494] 0 2494 1745 839 1 0 0 bash Oct 25 07:28:34 nldedip4k031 kernel: [87976.525038] [ 2573] 0 2573 3394 1689 3 0 0 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.525040] [ 2589] 0 2589 5014 457 3 0 0 rsync Oct 25 07:28:34 nldedip4k031 kernel: [87976.525043] [ 2590] 0 2590 7970 522 1 0 0 rsync Oct 25 07:28:34 nldedip4k031 kernel: [87976.525045] [ 2652] 104 2652 1150 326 5 0 0 pickup Oct 25 07:28:34 nldedip4k031 kernel: [87976.525048] [ 2847] 0 2847 709 89 0 0 0 upstart-udev-br Oct 25 07:28:34 nldedip4k031 kernel: [87976.525050] Out of memory: Kill process 764 (upstart-socket-) score 1 or sacrifice child Oct 25 07:28:34 nldedip4k031 kernel: [87976.525484] Killed process 764 (upstart-socket-) total-vm:2848kB, anon-rss:204kB, file-rss:208kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.526161] init: upstart-socket-bridge main process (764) killed by KILL signal Oct 25 07:28:34 nldedip4k031 kernel: [87976.526180] init: upstart-socket-bridge main process ended, respawning Oct 25 07:28:44 nldedip4k031 kernel: [87986.439671] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439674] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439676] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:44 nldedip4k031 kernel: [87986.439678] Call Trace: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439684] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439686] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439688] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439691] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439694] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439696] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439699] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439702] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439704] [] vfs_read+0x8c/0x160 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439707] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439709] [] sys_read+0x3d/0x70 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439712] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439714] Mem-Info: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439714] DMA per-cpu: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439716] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439717] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439718] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439719] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439720] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439721] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439722] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439723] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439724] Normal per-cpu: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439725] CPU 0: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439726] CPU 1: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439727] CPU 2: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439728] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439729] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:33:48 nldedip4k031 kernel: imklog 5.8.6, log source = /proc/kmsg started. Oct 25 07:33:48 nldedip4k031 rsyslogd: [origin software="rsyslogd" swVersion="5.8.6" x-pid="2880" x-info="http://www.rsyslog.com"] start Oct 25 07:33:48 nldedip4k031 rsyslogd: rsyslogd's groupid changed to 103 Oct 25 07:33:48 nldedip4k031 rsyslogd: rsyslogd's userid changed to 101 Oct 25 07:33:48 nldedip4k031 rsyslogd-2039: Could not open output pipe '/dev/xconsole' [try http://www.rsyslog.com/e/2039 ]

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• Sun Fire X4800 M2 Posts World Record x86 SPECjEnterprise2010 Result

  - by Brian

  Oracle's Sun Fire X4800 M2 using the Intel Xeon E7-8870 processor and Sun Fire X4470 M2 using the Intel Xeon E7-4870 processor, produced a world record single application server SPECjEnterprise2010 benchmark result of 27,150.05 SPECjEnterprise2010 EjOPS. The Sun Fire X4800 M2 server ran the application tier and the Sun Fire X4470 M2 server was used for the database tier. The Sun Fire X4800 M2 server demonstrated 63% better performance compared to IBM P780 server result of 16,646.34 SPECjEnterprise2010 EjOPS. The Sun Fire X4800 M2 server demonstrated 4% better performance than the Cisco UCS B440 M2 result, both results used the same number of processors. This result used Oracle WebLogic Server 12c, Java HotSpot(TM) 64-Bit Server 1.7.0_02, and Oracle Database 11g. This result was produced using Oracle Linux. Performance Landscape Complete benchmark results are at the SPEC website, SPECjEnterprise2010 Results. The table below compares against the best results from IBM and Cisco. SPECjEnterprise2010 Performance Chart as of 3/12/2012 Submitter EjOPS* Application Server Database Server Oracle 27,150.05 1x Sun Fire X4800 M2 8x 2.4 GHz Intel Xeon E7-8870 Oracle WebLogic 12c 1x Sun Fire X4470 M2 4x 2.4 GHz Intel Xeon E7-4870 Oracle Database 11g (11.2.0.2) Cisco 26,118.67 2x UCS B440 M2 Blade Server 4x 2.4 GHz Intel Xeon E7-4870 Oracle WebLogic 11g (10.3.5) 1x UCS C460 M2 Blade Server 4x 2.4 GHz Intel Xeon E7-4870 Oracle Database 11g (11.2.0.2) IBM 16,646.34 1x IBM Power 780 8x 3.86 GHz POWER 7 WebSphere Application Server V7 1x IBM Power 750 Express 4x 3.55 GHz POWER 7 IBM DB2 9.7 Workgroup Server Edition FP3a * SPECjEnterprise2010 EjOPS, bigger is better. Configuration Summary Application Server: 1 x Sun Fire X4800 M2 8 x 2.4 GHz Intel Xeon processor E7-8870 256 GB memory 4 x 10 GbE NIC 2 x FC HBA Oracle Linux 5 Update 6 Oracle WebLogic Server 11g Release 1 (10.3.5) Java HotSpot(TM) 64-Bit Server VM on Linux, version 1.7.0_02 (Java SE 7 Update 2) Database Server: 1 x Sun Fire X4470 M2 4 x 2.4 GHz Intel Xeon E7-4870 512 GB memory 4 x 10 GbE NIC 2 x FC HBA 2 x Sun StorageTek 2540 M2 4 x Sun Fire X4270 M2 4 x Sun Storage F5100 Flash Array Oracle Linux 5 Update 6 Oracle Database 11g Enterprise Edition Release 11.2.0.2 Benchmark Description SPECjEnterprise2010 is the third generation of the SPEC organization's J2EE end-to-end industry standard benchmark application. The SPECjEnterprise2010 benchmark has been designed and developed to cover the Java EE 5 specification's significantly expanded and simplified programming model, highlighting the major features used by developers in the industry today. This provides a real world workload driving the Application Server's implementation of the Java EE specification to its maximum potential and allowing maximum stressing of the underlying hardware and software systems. The workload consists of an end to end web based order processing domain, an RMI and Web Services driven manufacturing domain and a supply chain model utilizing document based Web Services. The application is a collection of Java classes, Java Servlets, Java Server Pages, Enterprise Java Beans, Java Persistence Entities (pojo's) and Message Driven Beans. The SPECjEnterprise2010 benchmark heavily exercises all parts of the underlying infrastructure that make up the application environment, including hardware, JVM software, database software, JDBC drivers, and the system network. The primary metric of the SPECjEnterprise2010 benchmark is jEnterprise Operations Per Second ("SPECjEnterprise2010 EjOPS"). This metric is calculated by adding the metrics of the Dealership Management Application in the Dealer Domain and the Manufacturing Application in the Manufacturing Domain. There is no price/performance metric in this benchmark. Key Points and Best Practices Sixteen Oracle WebLogic server instances were started using numactl, binding 2 instances per chip. Eight Oracle database listener processes were started, binding 2 instances per chip using taskset. Additional tuning information is in the report at http://spec.org. See Also Oracle Press Release -- SPECjEnterprise2010 Results Page Sun Fire X4800 M2 Server oracle.com OTN Sun Fire X4270 M2 Server oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Oracle Linux oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN WebLogic Suite oracle.com OTN Disclosure Statement SPEC and the benchmark name SPECjEnterprise are registered trademarks of the Standard Performance Evaluation Corporation. Sun Fire X4800 M2, 27,150.05 SPECjEnterprise2010 EjOPS; IBM Power 780, 16,646.34 SPECjEnterprise2010 EjOPS; Cisco UCS B440 M2, 26,118.67 SPECjEnterprise2010 EjOPS. Results from www.spec.org as of 3/27/2012.

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• BizTalk Server Monitoring &ndash; SharePoint Web Part

  - by SURESH GIRIRAJAN

  I have been worked with customers using BizTalk as shared infrastructure in the enterprise, where we have two or more BizTalk apps running on it for different Business groups. Also these customers are not using BizTalk ESB portal even though they are using BizTalk ESB exception framework. So main issue with all these Business groups are they don’t have visibility into the BizTalk apps running in prod, even though they are using SCOM and other monitoring stuff in place. So I am trying to address few issues I am going to list below and how I try to mitigate them, first one on the list is how to get visibility into prod, how to provision those access to the BizTalk resources with minimal activity and how can we take advantage of the resources we have today. So I was working on creating REST data services for BizTalk RFID a year ago and available on codeplex. I thought to extend that idea to take advantage of BizTalk Data Services available in codeplex. I extended the BizTalk data services I will upload the updated service soon. So let me start thru how my solution works, so first step I am using the BizTalk data service (REST service) which expose most of the BizTalk artifacts as resources such as Applications, Orchestrations, Send ports, Receive ports, Host instances and In process instances etc. BizTalk Server Monitoring – SharePoint Web Part I am hosting the BizTalk data service in IIS with application pool configured to run under BizTalk administrator credentials. So with this setup I am making the service to make accessible anonymous. Next step of this solution I have created a SharePoint Visual web part which consumes the BizTalk data service and display all the BizTalk Application and Platform settings in read only mode. Even though BizTalk data services offers to browse resources as well perform actions like starting, stopping Orchestrations, Send ports, Receive locations, Host instances etc. Host Instances BizTalk Applications BizTalk Running / Suspended Instances So having this BizTalk Monitoring SharePoint web part, will be added to the SharePoint. This eliminates the need for granting access to the BizTalk users explicitly, so when you have BizTalk contractor or BizTalk application user need to have access to the BizTalk environment all the need is have access to the SharePoint website. You can configure the web part point to different end point based on your environment. I am making this as read only as part of this to make easier for the users and in terms of provisioning. This removes the dependency of BizTalk admin at least for viewing the BizTalk application status and errors etc. If we need to make any changes to the BizTalk application then its application owner responsibility to co-ordinate with BizTalk admins. There are options like BizTalk ESB portal, BizTalk 360 etc… but this one of the approach to reduce number of steps required to give access to BizTalk application users and also to maximize the resource we have in enterprise today. Also you can expose this data service thru Azure Service Bus and access from other apps like mobile devices or create a web site hosted in Azure etc. One last thing I have tested only with BizTalk Server 2010 on x64 VM only, but it should work on other version. I will try to upload the code shortly with instructions how to setup etc.… I welcome thoughts and suggestions… Hope this helps….

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