Search Results

Search found 7865 results on 315 pages for 'high density'.

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

Page 3/315 | < Previous Page | 1 2 3 4 5 6 7 8 9 10 11 12  | Next Page >

  • Which programming languages aren't considered high-level?

    - by hilo
    In informatics theory I hear and read about high-level and low-level languages all time. Yet I don't understand why this is still relevant as there aren't any (relevant) low-level languages except assembler in use today. So you get: Low-level Assembler Definitely not low-level C BASIC FORTRAN COBOL ... High-level C++ Ruby Python PHP ... And if assembler is low-level, how could you put for example C into the same list. I mean: C is extremely high-level compared to assembler. Same even for COBOL, Fortran, etc. So why does everybody keep mentioning high and low-level languages if assembler is really the only low-level language.

    Read the article

  • About High Availability

    - by Invincible
    I guess my previous question was ambiguous. I am looking for High Availability architecture for system application like Database in particular. I know this is not perfect place to ask this question. Can anybody suggest some good resource or book on High-Availability? I want to learn as much as I can on high-availability before I start building my system. Thanks in advance!

    Read the article

  • High Linux loads on low CPU/memory usage

    - by user13323
    Hi. I have quite strange situation, where my CentOS 5.5 box loads are high, but the CPU and memory used are pretty low: top - 20:41:38 up 42 days, 6:14, 2 users, load average: 19.79, 21.25, 18.87 Tasks: 254 total, 1 running, 253 sleeping, 0 stopped, 0 zombie Cpu(s): 3.8%us, 0.3%sy, 0.1%ni, 95.0%id, 0.6%wa, 0.0%hi, 0.1%si, 0.0%st Mem: 4035284k total, 4008084k used, 27200k free, 38748k buffers Swap: 4208928k total, 242576k used, 3966352k free, 1465008k cached free -mt total used free shared buffers cached Mem: 3940 3910 29 0 37 1427 -/+ buffers/cache: 2445 1495 Swap: 4110 236 3873 Total: 8050 4147 3903 Iostat also shows good results: avg-cpu: %user %nice %system %iowait %steal %idle 3.83 0.13 0.41 0.58 0.00 95.05 Here is the ps aux output: USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND root 1 0.0 0.0 10348 80 ? Ss 2010 2:11 init [3] root 2 0.0 0.0 0 0 ? S< 2010 0:00 [migration/0] root 3 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/0] root 4 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/0] root 5 0.0 0.0 0 0 ? S< 2010 0:02 [migration/1] root 6 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/1] root 7 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/1] root 8 0.0 0.0 0 0 ? S< 2010 0:02 [migration/2] root 9 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/2] root 10 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/2] root 11 0.0 0.0 0 0 ? S< 2010 0:02 [migration/3] root 12 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/3] root 13 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/3] root 14 0.0 0.0 0 0 ? S< 2010 0:03 [migration/4] root 15 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/4] root 16 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/4] root 17 0.0 0.0 0 0 ? S< 2010 0:01 [migration/5] root 18 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/5] root 19 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/5] root 20 0.0 0.0 0 0 ? S< 2010 0:11 [migration/6] root 21 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/6] root 22 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/6] root 23 0.0 0.0 0 0 ? S< 2010 0:01 [migration/7] root 24 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/7] root 25 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/7] root 26 0.0 0.0 0 0 ? S< 2010 0:00 [migration/8] root 27 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/8] root 28 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/8] root 29 0.0 0.0 0 0 ? S< 2010 0:00 [migration/9] root 30 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/9] root 31 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/9] root 32 0.0 0.0 0 0 ? S< 2010 0:08 [migration/10] root 33 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/10] root 34 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/10] root 35 0.0 0.0 0 0 ? S< 2010 0:05 [migration/11] root 36 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/11] root 37 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/11] root 38 0.0 0.0 0 0 ? S< 2010 0:02 [migration/12] root 39 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/12] root 40 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/12] root 41 0.0 0.0 0 0 ? S< 2010 0:14 [migration/13] root 42 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/13] root 43 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/13] root 44 0.0 0.0 0 0 ? S< 2010 0:04 [migration/14] root 45 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/14] root 46 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/14] root 47 0.0 0.0 0 0 ? S< 2010 0:01 [migration/15] root 48 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/15] root 49 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/15] root 50 0.0 0.0 0 0 ? S< 2010 0:00 [events/0] root 51 0.0 0.0 0 0 ? S< 2010 0:00 [events/1] root 52 0.0 0.0 0 0 ? S< 2010 0:00 [events/2] root 53 0.0 0.0 0 0 ? S< 2010 0:00 [events/3] root 54 0.0 0.0 0 0 ? S< 2010 0:00 [events/4] root 55 0.0 0.0 0 0 ? S< 2010 0:00 [events/5] root 56 0.0 0.0 0 0 ? S< 2010 0:00 [events/6] root 57 0.0 0.0 0 0 ? S< 2010 0:00 [events/7] root 58 0.0 0.0 0 0 ? S< 2010 0:00 [events/8] root 59 0.0 0.0 0 0 ? S< 2010 0:00 [events/9] root 60 0.0 0.0 0 0 ? S< 2010 0:00 [events/10] root 61 0.0 0.0 0 0 ? S< 2010 0:00 [events/11] root 62 0.0 0.0 0 0 ? S< 2010 0:00 [events/12] root 63 0.0 0.0 0 0 ? S< 2010 0:00 [events/13] root 64 0.0 0.0 0 0 ? S< 2010 0:00 [events/14] root 65 0.0 0.0 0 0 ? S< 2010 0:00 [events/15] root 66 0.0 0.0 0 0 ? S< 2010 0:00 [khelper] root 107 0.0 0.0 0 0 ? S< 2010 0:00 [kthread] root 126 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/0] root 127 0.0 0.0 0 0 ? S< 2010 0:03 [kblockd/1] root 128 0.0 0.0 0 0 ? S< 2010 0:01 [kblockd/2] root 129 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/3] root 130 0.0 0.0 0 0 ? S< 2010 0:05 [kblockd/4] root 131 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/5] root 132 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/6] root 133 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/7] root 134 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/8] root 135 0.0 0.0 0 0 ? S< 2010 0:02 [kblockd/9] root 136 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/10] root 137 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/11] root 138 0.0 0.0 0 0 ? S< 2010 0:04 [kblockd/12] root 139 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/13] root 140 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/14] root 141 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/15] root 142 0.0 0.0 0 0 ? S< 2010 0:00 [kacpid] root 281 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/0] root 282 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/1] root 283 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/2] root 284 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/3] root 285 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/4] root 286 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/5] root 287 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/6] root 288 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/7] root 289 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/8] root 290 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/9] root 291 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/10] root 292 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/11] root 293 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/12] root 294 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/13] root 295 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/14] root 296 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/15] root 299 0.0 0.0 0 0 ? S< 2010 0:00 [khubd] root 301 0.0 0.0 0 0 ? S< 2010 0:00 [kseriod] root 490 0.0 0.0 0 0 ? S 2010 0:00 [khungtaskd] root 493 0.1 0.0 0 0 ? S< 2010 94:48 [kswapd1] root 494 0.0 0.0 0 0 ? S< 2010 0:00 [aio/0] root 495 0.0 0.0 0 0 ? S< 2010 0:00 [aio/1] root 496 0.0 0.0 0 0 ? S< 2010 0:00 [aio/2] root 497 0.0 0.0 0 0 ? S< 2010 0:00 [aio/3] root 498 0.0 0.0 0 0 ? S< 2010 0:00 [aio/4] root 499 0.0 0.0 0 0 ? S< 2010 0:00 [aio/5] root 500 0.0 0.0 0 0 ? S< 2010 0:00 [aio/6] root 501 0.0 0.0 0 0 ? S< 2010 0:00 [aio/7] root 502 0.0 0.0 0 0 ? S< 2010 0:00 [aio/8] root 503 0.0 0.0 0 0 ? S< 2010 0:00 [aio/9] root 504 0.0 0.0 0 0 ? S< 2010 0:00 [aio/10] root 505 0.0 0.0 0 0 ? S< 2010 0:00 [aio/11] root 506 0.0 0.0 0 0 ? S< 2010 0:00 [aio/12] root 507 0.0 0.0 0 0 ? S< 2010 0:00 [aio/13] root 508 0.0 0.0 0 0 ? S< 2010 0:00 [aio/14] root 509 0.0 0.0 0 0 ? S< 2010 0:00 [aio/15] root 665 0.0 0.0 0 0 ? S< 2010 0:00 [kpsmoused] root 808 0.0 0.0 0 0 ? S< 2010 0:00 [ata/0] root 809 0.0 0.0 0 0 ? S< 2010 0:00 [ata/1] root 810 0.0 0.0 0 0 ? S< 2010 0:00 [ata/2] root 811 0.0 0.0 0 0 ? S< 2010 0:00 [ata/3] root 812 0.0 0.0 0 0 ? S< 2010 0:00 [ata/4] root 813 0.0 0.0 0 0 ? S< 2010 0:00 [ata/5] root 814 0.0 0.0 0 0 ? S< 2010 0:00 [ata/6] root 815 0.0 0.0 0 0 ? S< 2010 0:00 [ata/7] root 816 0.0 0.0 0 0 ? S< 2010 0:00 [ata/8] root 817 0.0 0.0 0 0 ? S< 2010 0:00 [ata/9] root 818 0.0 0.0 0 0 ? S< 2010 0:00 [ata/10] root 819 0.0 0.0 0 0 ? S< 2010 0:00 [ata/11] root 820 0.0 0.0 0 0 ? S< 2010 0:00 [ata/12] root 821 0.0 0.0 0 0 ? S< 2010 0:00 [ata/13] root 822 0.0 0.0 0 0 ? S< 2010 0:00 [ata/14] root 823 0.0 0.0 0 0 ? S< 2010 0:00 [ata/15] root 824 0.0 0.0 0 0 ? S< 2010 0:00 [ata_aux] root 842 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_0] root 843 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_1] root 844 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_2] root 845 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_3] root 846 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_4] root 847 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_5] root 882 0.0 0.0 0 0 ? S< 2010 0:00 [kstriped] root 951 0.0 0.0 0 0 ? S< 2010 4:24 [kjournald] root 976 0.0 0.0 0 0 ? S< 2010 0:00 [kauditd] postfix 990 0.0 0.0 54208 2284 ? S 21:19 0:00 pickup -l -t fifo -u root 1013 0.0 0.0 12676 8 ? S<s 2010 0:00 /sbin/udevd -d root 1326 0.0 0.0 90900 3400 ? Ss 14:53 0:00 sshd: root@notty root 1410 0.0 0.0 53972 2108 ? Ss 14:53 0:00 /usr/libexec/openssh/sftp-server root 2690 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/0] root 2691 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/1] root 2692 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/2] root 2693 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/3] root 2694 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/4] root 2695 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/5] root 2696 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/6] root 2697 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/7] root 2698 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/8] root 2699 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/9] root 2700 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/10] root 2701 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/11] root 2702 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/12] root 2703 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/13] root 2704 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/14] root 2705 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/15] root 2706 0.0 0.0 0 0 ? S< 2010 0:00 [kmpath_handlerd] root 2755 0.0 0.0 0 0 ? S< 2010 4:35 [kjournald] root 2757 0.0 0.0 0 0 ? S< 2010 3:38 [kjournald] root 2759 0.0 0.0 0 0 ? S< 2010 4:10 [kjournald] root 2761 0.0 0.0 0 0 ? S< 2010 4:26 [kjournald] root 2763 0.0 0.0 0 0 ? S< 2010 3:15 [kjournald] root 2765 0.0 0.0 0 0 ? S< 2010 3:04 [kjournald] root 2767 0.0 0.0 0 0 ? S< 2010 3:02 [kjournald] root 2769 0.0 0.0 0 0 ? S< 2010 2:58 [kjournald] root 2771 0.0 0.0 0 0 ? S< 2010 0:00 [kjournald] root 3340 0.0 0.0 5908 356 ? Ss 2010 2:48 syslogd -m 0 root 3343 0.0 0.0 3804 212 ? Ss 2010 0:03 klogd -x root 3430 0.0 0.0 0 0 ? S< 2010 0:50 [kondemand/0] root 3431 0.0 0.0 0 0 ? S< 2010 0:54 [kondemand/1] root 3432 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/2] root 3433 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/3] root 3434 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/4] root 3435 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/5] root 3436 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/6] root 3437 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/7] root 3438 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/8] root 3439 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/9] root 3440 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/10] root 3441 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/11] root 3442 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/12] root 3443 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/13] root 3444 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/14] root 3445 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/15] root 3461 0.0 0.0 10760 284 ? Ss 2010 3:44 irqbalance rpc 3481 0.0 0.0 8052 4 ? Ss 2010 0:00 portmap root 3526 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/0] root 3527 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/1] root 3528 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/2] root 3529 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/3] root 3530 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/4] root 3531 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/5] root 3532 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/6] root 3533 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/7] root 3534 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/8] root 3535 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/9] root 3536 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/10] root 3537 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/11] root 3538 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/12] root 3539 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/13] root 3540 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/14] root 3541 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/15] root 3563 0.0 0.0 10160 8 ? Ss 2010 0:00 rpc.statd root 3595 0.0 0.0 55180 4 ? Ss 2010 0:00 rpc.idmapd dbus 3618 0.0 0.0 21256 28 ? Ss 2010 0:00 dbus-daemon --system root 3649 0.2 0.4 563084 18796 ? S<sl 2010 179:03 mfsmount /mnt/mfs -o rw,mfsmaster=web1.ovs.local root 3702 0.0 0.0 3800 8 ? Ss 2010 0:00 /usr/sbin/acpid 68 3715 0.0 0.0 31312 816 ? Ss 2010 3:14 hald root 3716 0.0 0.0 21692 28 ? S 2010 0:00 hald-runner 68 3726 0.0 0.0 12324 8 ? S 2010 0:00 hald-addon-acpi: listening on acpid socket /var/run/acpid.socket 68 3730 0.0 0.0 12324 8 ? S 2010 0:00 hald-addon-keyboard: listening on /dev/input/event0 root 3773 0.0 0.0 62608 332 ? Ss 2010 0:00 /usr/sbin/sshd ganglia 3786 0.0 0.0 24704 988 ? Ss 2010 14:26 /usr/sbin/gmond root 3843 0.0 0.0 54144 300 ? Ss 2010 1:49 /usr/libexec/postfix/master postfix 3855 0.0 0.0 54860 1060 ? S 2010 0:22 qmgr -l -t fifo -u root 3877 0.0 0.0 74828 708 ? Ss 2010 1:15 crond root 3891 1.4 1.9 326960 77704 ? S<l 2010 896:59 mfschunkserver root 4122 0.0 0.0 18732 176 ? Ss 2010 0:10 /usr/sbin/atd root 4193 0.0 0.8 129180 35984 ? Ssl 2010 11:04 /usr/bin/ruby /usr/sbin/puppetd root 4223 0.0 0.0 18416 172 ? S 2010 0:10 /usr/sbin/smartd -q never root 4227 0.0 0.0 3792 8 tty1 Ss+ 2010 0:00 /sbin/mingetty tty1 root 4230 0.0 0.0 3792 8 tty2 Ss+ 2010 0:00 /sbin/mingetty tty2 root 4231 0.0 0.0 3792 8 tty3 Ss+ 2010 0:00 /sbin/mingetty tty3 root 4233 0.0 0.0 3792 8 tty4 Ss+ 2010 0:00 /sbin/mingetty tty4 root 4234 0.0 0.0 3792 8 tty5 Ss+ 2010 0:00 /sbin/mingetty tty5 root 4236 0.0 0.0 3792 8 tty6 Ss+ 2010 0:00 /sbin/mingetty tty6 root 5596 0.0 0.0 19368 20 ? Ss 2010 0:00 DarwinStreamingServer qtss 5597 0.8 0.9 166572 37408 ? Sl 2010 523:02 DarwinStreamingServer root 8714 0.0 0.0 0 0 ? S Jan31 0:33 [pdflush] root 9914 0.0 0.0 65612 968 pts/1 R+ 21:49 0:00 ps aux root 10765 0.0 0.0 76792 1080 ? Ss Jan24 0:58 SCREEN root 10766 0.0 0.0 66212 872 pts/3 Ss Jan24 0:00 /bin/bash root 11833 0.0 0.0 63852 1060 pts/3 S+ 17:17 0:00 /bin/sh ./launch.sh root 11834 437 42.9 4126884 1733348 pts/3 Sl+ 17:17 1190:50 /usr/bin/java -Xms128m -Xmx512m -XX:+UseConcMarkSweepGC -jar /JavaCore/JavaCore.jar root 13127 4.7 1.1 110564 46876 ? Ssl 17:18 12:55 /JavaCore/fetcher.bin root 19392 0.0 0.0 90108 3336 ? Rs 20:35 0:00 sshd: root@pts/1 root 19401 0.0 0.0 66216 1640 pts/1 Ss 20:35 0:00 -bash root 20567 0.0 0.0 90108 412 ? Ss Jan16 1:58 sshd: root@pts/0 root 20569 0.0 0.0 66084 912 pts/0 Ss Jan16 0:00 -bash root 21053 0.0 0.0 63856 28 ? S Jan30 0:00 /bin/sh /usr/bin/WowzaMediaServerd /usr/local/WowzaMediaServer/bin/setenv.sh /var/run/WowzaM root 21054 2.9 10.3 2252652 418468 ? Sl Jan30 314:25 java -Xmx1200M -server -Djava.net.preferIPv4Stack=true -Dcom.sun.management.jmxremote=true - root 21915 0.0 0.0 0 0 ? S Feb01 0:00 [pdflush] root 29996 0.0 0.0 76524 1004 pts/0 S+ 14:41 0:00 screen -x Any idea what could this be, or where I should look for more diagnostic information? Thanks.

    Read the article

  • High Server Load cannot figure out why

    - by Tim Bolton
    My server is currently running CentOS 5.2, with WHM 11.34. Currently, we're at 6.43 to 12 for a load average. The sites that we're hosting are taking a lot time to respond and resolve. top doesn't show anything out of the ordinary and iftop doesn't show a lot of traffic. We have many resellers, and some not so good at writing code, how can we find the culprit? vmstat output: vmstat procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu------ r b swpd free buff cache si so bi bo in cs us sy id wa st 0 2 84 78684 154916 1021080 0 0 72 274 0 14 6 3 80 12 0 top output (ordered by %CPU) top - 21:44:43 up 5 days, 10:39, 3 users, load average: 3.36, 4.18, 4.73 Tasks: 222 total, 3 running, 219 sleeping, 0 stopped, 0 zombie Cpu(s): 5.8%us, 2.3%sy, 0.2%ni, 79.6%id, 11.8%wa, 0.0%hi, 0.2%si, 0.0%st Mem: 2074580k total, 1863044k used, 211536k free, 174828k buffers Swap: 2040212k total, 84k used, 2040128k free, 987604k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 15930 mysql 15 0 138m 46m 4380 S 4 2.3 1:45.87 mysqld 21772 igniteth 17 0 23200 7152 3932 R 4 0.3 0:00.02 php 1586 root 10 -5 0 0 0 S 2 0.0 11:45.19 kjournald 21759 root 15 0 2416 1024 732 R 2 0.0 0:00.01 top 1 root 15 0 2156 648 560 S 0 0.0 0:26.31 init 2 root RT 0 0 0 0 S 0 0.0 0:00.35 migration/0 3 root 34 19 0 0 0 S 0 0.0 0:00.32 ksoftirqd/0 4 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/0 5 root RT 0 0 0 0 S 0 0.0 0:02.00 migration/1 6 root 34 19 0 0 0 S 0 0.0 0:00.11 ksoftirqd/1 7 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/1 8 root RT 0 0 0 0 S 0 0.0 0:01.29 migration/2 9 root 34 19 0 0 0 S 0 0.0 0:00.26 ksoftirqd/2 10 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/2 11 root RT 0 0 0 0 S 0 0.0 0:00.90 migration/3 12 root 34 19 0 0 0 R 0 0.0 0:00.20 ksoftirqd/3 13 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/3 top output (ordered by CPU time) top - 21:46:12 up 5 days, 10:41, 3 users, load average: 2.88, 3.82, 4.55 Tasks: 217 total, 1 running, 216 sleeping, 0 stopped, 0 zombie Cpu(s): 3.7%us, 2.0%sy, 2.0%ni, 67.2%id, 25.0%wa, 0.0%hi, 0.1%si, 0.0%st Mem: 2074580k total, 1959516k used, 115064k free, 183116k buffers Swap: 2040212k total, 84k used, 2040128k free, 1090308k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ TIME COMMAND 32367 root 16 0 215m 212m 1548 S 0 10.5 62:03.63 62:03 tailwatchd 1586 root 10 -5 0 0 0 S 0 0.0 11:45.27 11:45 kjournald 1576 root 10 -5 0 0 0 S 0 0.0 2:37.86 2:37 kjournald 27722 root 16 0 2556 1184 800 S 0 0.1 1:48.94 1:48 top 15930 mysql 15 0 138m 46m 4380 S 4 2.3 1:48.63 1:48 mysqld 2932 root 34 19 0 0 0 S 0 0.0 1:41.05 1:41 kipmi0 226 root 10 -5 0 0 0 S 0 0.0 1:34.33 1:34 kswapd0 2671 named 25 0 74688 7400 2116 S 0 0.4 1:23.58 1:23 named 3229 root 15 0 10300 3348 2724 S 0 0.2 0:40.85 0:40 sshd 1580 root 10 -5 0 0 0 S 0 0.0 0:30.62 0:30 kjournald 1 root 17 0 2156 648 560 S 0 0.0 0:26.32 0:26 init 2616 root 15 0 1816 576 480 S 0 0.0 0:23.50 0:23 syslogd 1584 root 10 -5 0 0 0 S 0 0.0 0:18.67 0:18 kjournald 4342 root 34 19 27692 11m 2116 S 0 0.5 0:18.23 0:18 yum-updatesd 8044 bollingp 15 0 3456 2036 740 S 1 0.1 0:15.56 0:15 imapd 26 root 10 -5 0 0 0 S 0 0.0 0:14.18 0:14 kblockd/1 7989 gmailsit 16 0 3196 1748 736 S 0 0.1 0:10.43 0:10 imapd iostat -xtk 1 10 output [root@server1 tmp]# iostat -xtk 1 10 Linux 2.6.18-53.el5 12/18/2012 Time: 09:51:06 PM avg-cpu: %user %nice %system %iowait %steal %idle 5.83 0.19 2.53 11.85 0.00 79.60 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 1.37 118.83 18.70 54.27 131.47 692.72 22.59 4.90 67.19 3.10 22.59 sdb 0.35 39.33 20.33 61.43 158.79 403.22 13.75 5.23 63.93 3.77 30.80 Time: 09:51:07 PM avg-cpu: %user %nice %system %iowait %steal %idle 1.50 0.00 0.50 24.00 0.00 74.00 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 25.00 2.00 2.00 128.00 108.00 118.00 0.03 7.25 4.00 1.60 sdb 0.00 16.00 41.00 145.00 200.00 668.00 9.33 107.92 272.72 5.38 100.10 Time: 09:51:08 PM avg-cpu: %user %nice %system %iowait %steal %idle 2.00 0.00 1.50 29.50 0.00 67.00 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 95.00 3.00 33.00 12.00 480.00 27.33 0.07 1.72 1.31 4.70 sdb 0.00 14.00 1.00 228.00 4.00 960.00 8.42 143.49 568.01 4.37 100.10 Time: 09:51:09 PM avg-cpu: %user %nice %system %iowait %steal %idle 13.28 0.00 2.76 21.30 0.00 62.66 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 21.00 1.00 19.00 16.00 192.00 20.80 0.06 3.55 1.30 2.60 sdb 0.00 36.00 28.00 181.00 124.00 884.00 9.65 121.16 617.31 4.79 100.10 Time: 09:51:10 PM avg-cpu: %user %nice %system %iowait %steal %idle 4.74 0.00 1.50 25.19 0.00 68.58 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 20.00 3.00 15.00 12.00 136.00 16.44 0.17 7.11 3.11 5.60 sdb 0.00 0.00 103.00 60.00 544.00 248.00 9.72 52.35 545.23 6.14 100.10 Time: 09:51:11 PM avg-cpu: %user %nice %system %iowait %steal %idle 1.24 0.00 1.24 25.31 0.00 72.21 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 75.00 4.00 28.00 16.00 416.00 27.00 0.08 3.72 2.03 6.50 sdb 2.00 9.00 124.00 17.00 616.00 104.00 10.21 3.73 213.73 7.10 100.10 Time: 09:51:12 PM avg-cpu: %user %nice %system %iowait %steal %idle 1.00 0.00 0.75 24.31 0.00 73.93 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 24.00 1.00 9.00 4.00 132.00 27.20 0.01 1.20 1.10 1.10 sdb 4.00 40.00 103.00 48.00 528.00 212.00 9.80 105.21 104.32 6.64 100.20 Time: 09:51:13 PM avg-cpu: %user %nice %system %iowait %steal %idle 2.50 0.00 1.75 23.25 0.00 72.50 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 125.74 3.96 46.53 15.84 689.11 27.92 0.20 4.06 2.41 12.18 sdb 2.97 0.00 91.09 84.16 419.80 471.29 10.17 85.85 590.78 5.66 99.11 Time: 09:51:14 PM avg-cpu: %user %nice %system %iowait %steal %idle 0.75 0.00 0.50 24.94 0.00 73.82 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 88.00 1.00 7.00 4.00 380.00 96.00 0.04 4.38 3.00 2.40 sdb 3.00 7.00 111.00 44.00 540.00 208.00 9.65 18.58 581.79 6.46 100.10 Time: 09:51:15 PM avg-cpu: %user %nice %system %iowait %steal %idle 11.03 0.00 3.26 26.57 0.00 59.15 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 145.00 7.00 53.00 28.00 792.00 27.33 0.15 2.50 1.55 9.30 sdb 1.00 0.00 155.00 0.00 800.00 0.00 10.32 2.85 18.63 6.46 100.10 [root@server1 tmp]# MySQL Show Full Processlist mysql> show full processlist; +------+---------------+-----------+-----------------------+----------------+------+----------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Id | User | Host | db | Command | Time | State | Info | +------+---------------+-----------+-----------------------+----------------+------+----------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | 1 | DB_USER_ONE | localhost | DB_ONE | Query | 3 | waiting for handler insert | INSERT DELAYED INTO defers (mailtime,msgid,email,transport_method,message,host,ip,router,deliveryuser,deliverydomain) VALUES(FROM_UNIXTIME('1355879748'),'1TivwL-0003y8-8l','[email protected]','remote_smtp','SMTP error from remote mail server after initial connection: host mx1.mail.tw.yahoo.com [203.188.197.119]: 421 4.7.0 [TS01] Messages from 75.125.90.146 temporarily deferred due to user complaints - 4.16.55.1; see http://postmaster.yahoo.com/421-ts01.html','mx1.mail.tw.yahoo.com','203.188.197.119','lookuphost','','') | | 2 | DELAYED | localhost | DB_ONE | Delayed insert | 52 | insert | | | 3 | DELAYED | localhost | DB_ONE | Delayed insert | 68 | insert | | | 911 | DELAYED | localhost | DB_ONE | Delayed insert | 99 | Waiting for INSERT | | | 993 | DB_USER_TWO | localhost | DB_TWO | Sleep | 832 | | NULL | | 994 | DB_USER_ONE | localhost | DB_ONE | Query | 185 | Locked | delete from failures where FROM_UNIXTIME(UNIX_TIMESTAMP(NOW())-1296000) > mailtime | | 1102 | DB_USER_THREE | localhost | DB_THREE | Query | 29 | NULL | commit | | 1249 | DB_USER_FOUR | localhost | DB_FOUR | Query | 13 | NULL | commit | | 1263 | root | localhost | DB_FIVE | Query | 0 | NULL | show full processlist | | 1264 | DB_USER_SIX | localhost | DB_SIX | Query | 3 | NULL | commit | +------+---------------+-----------+-----------------------+----------------+------+----------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ 10 rows in set (0.00 sec)

    Read the article

  • High Load mysql on Debian server

    - by Oleg Abrazhaev
    I have Debian server with 32 gb memory. And there is apache2, memcached and nginx on this server. Memory load always on maximum. Only 500m free. Most memory leak do MySql. Apache only 70 clients configured, other services small memory usage. When mysql use all memory it stops. And nothing works, need mysql reboot. Mysql configured use maximum 24 gb memory. I have hight weight InnoDB bases. (400000 rows, 30 gb). And on server multithread daemon, that makes many inserts in this tables, thats why InnoDB. There is my mysql config. [mysqld] # # * Basic Settings # default-time-zone = "+04:00" user = mysql pid-file = /var/run/mysqld/mysqld.pid socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp language = /usr/share/mysql/english skip-external-locking default-time-zone='Europe/Moscow' # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. # # * Fine Tuning # #low_priority_updates = 1 concurrent_insert = ALWAYS wait_timeout = 600 interactive_timeout = 600 #normal key_buffer_size = 2024M #key_buffer_size = 1512M #70% hot cache key_cache_division_limit= 70 #16-32 max_allowed_packet = 32M #1-16M thread_stack = 8M #40-50 thread_cache_size = 50 #orderby groupby sort sort_buffer_size = 64M #same myisam_sort_buffer_size = 400M #temp table creates when group_by tmp_table_size = 3000M #tables in memory max_heap_table_size = 3000M #on disk open_files_limit = 10000 table_cache = 10000 join_buffer_size = 5M # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #myisam_use_mmap = 1 max_connections = 200 thread_concurrency = 8 # # * Query Cache Configuration # #more ignored query_cache_limit = 50M query_cache_size = 210M #on query cache query_cache_type = 1 # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. #log = /var/log/mysql/mysql.log # # Error logging goes to syslog. This is a Debian improvement :) # # Here you can see queries with especially long duration log_slow_queries = /var/log/mysql/mysql-slow.log long_query_time = 1 log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log server-id = 1 log-bin = /var/lib/mysql/mysql-bin #replicate-do-db = gate log-bin-index = /var/lib/mysql/mysql-bin.index log-error = /var/lib/mysql/mysql-bin.err relay-log = /var/lib/mysql/relay-bin relay-log-info-file = /var/lib/mysql/relay-bin.info relay-log-index = /var/lib/mysql/relay-bin.index binlog_do_db = 24avia expire_logs_days = 10 max_binlog_size = 100M read_buffer_size = 4024288 innodb_buffer_pool_size = 5000M innodb_flush_log_at_trx_commit = 2 innodb_thread_concurrency = 8 table_definition_cache = 2000 group_concat_max_len = 16M #binlog_do_db = gate #binlog_ignore_db = include_database_name # # * BerkeleyDB # # Using BerkeleyDB is now discouraged as its support will cease in 5.1.12. #skip-bdb # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # You might want to disable InnoDB to shrink the mysqld process by circa 100MB. #skip-innodb # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 500M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 32M key_buffer_size = 512M # # * NDB Cluster # # See /usr/share/doc/mysql-server-*/README.Debian for more information. # # The following configuration is read by the NDB Data Nodes (ndbd processes) # not from the NDB Management Nodes (ndb_mgmd processes). # # [MYSQL_CLUSTER] # ndb-connectstring=127.0.0.1 # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ Please, help me make it stable. Memory used /etc/mysql # free total used free shared buffers cached Mem: 32930800 32766424 164376 0 139208 23829196 -/+ buffers/cache: 8798020 24132780 Swap: 33553328 44660 33508668 Maybe my problem not in memory, but MySQL stops every day. As you can see, cache memory free 24 gb. Thank to Michael Hampton? for correction. Load overage on server 3.5. Maybe hdd or another problem? Maybe my config not optimal for 30gb InnoDB ?

    Read the article

  • RDP for High DPI Monitors?

    - by Joey
    A client is having some problems with their laptop. They use RDP to remote into their work PC, but the laptop they are using is a small 13" Sony Vaio laptop, but with 1920x1080 resolution. Everything is pretty small on the laptop anyway, but the problem is much worse after connecting with RDP, where everything is almost unreadable. I have done the obvious with changing the resolution on the server, the RDP size, forced scaling on the terminal server etc, but nothing has worked. Something else which I would normally do is change the laptop resolution to something a little lower, but the laptop only has 2 resolution settings, the big one, and a 1024x768 (wrong ratio). Any ideas?

    Read the article

  • Old CRT screen's high resolution doesn't work anymore on windows 7

    - by Mixxiphoid
    One year ago I decided to switch from Windows XP to Windows 7. I had a 17" CRT monitor with a screen resolution of 1600x1200 which worked fine on Windows XP. While installing Windows 7 everything went well until Windows 7 was going to install the video card its driver. Windows 7 puts the screen to its recommended resolution and my screen became black. I waited a few minutes to be sure the installation was finished. I turned off the computer by hand and restarted the computer on a resolution of 800x640. When windows 7 was done installing I went to screen resolutions and the resolution of 1600x1200 was on the top of the list with '(recommended)' next to it. I tried putting it on 1600x1200 but again my screen went black. I installed all windows 7 updates including the video card driver from the NVidia site (NOT from Windows 7). I tried about everything to make it work on 1600x1200 but with no succes. The highest resolution I got with the crt monitor was 1280x1024. I had a TFT screen which had 1280x1024 as max resolution and had better colors, so I used that one till today. My video card is 9600GT and my power supply is beyond sufficient. I even tried to install the driver I had on XP to see if it worked, but no results. I tried classic mode on windows 7, changed the dpi, the frequentie and the monitor settings, but nothing worked. I really like a vertical resolution of 1200, but it seems today I'm bound to all those standard monitors with a resolution of 1980x1024... Can anybody explain to me what the cause is that it worked on Windows XP but not on Windows 7? And maybe a solution to the problem (I actually gave up on getting it fixed...) Thanks a lot in advance. SOLUTION I downloaded the according monitor driver and installed it. Next I rebooted my computer on low resolution (800x640) and connected the CRT monitor. When Windows 7 booted successfully I went to computer management and 'update the driver' of my monitor. I manually selected 'Generic PnP monitor' and made that one active. I want to advanced settings at 'Screen resolution' and selected the mode '1600x1200 (32-bit) 80 Hertz (95 Hertz did not work). Now I had my resolution on 1600x1200. I repeated the earlier step to select the original monitor again instead of the Generic monitor. Quite a way to solve this problem, but it worked! Thanks a lot you all.

    Read the article

  • OpenVPN multiple servers on the same subnet, high availability

    - by andre
    Hey everyone. Let me start by saying that my Linux experience isn't super awesome but I can usually find my way around things easily. Over at work we have an OpenVPN setup that's been due for some improvement for a while now. The main server (tap mode) runs in our office, behind a rather slow DSL connection. The main problem is that, since I'm usually out of the office, every time I want to access something on the virtual network I have to go through that server to get anywhere else. We have two servers up on 100 Mbit connections that we use for development and production purposes, about 3 more servers in the office (one of them behind a different T1 line for VOIP) and about two dozen clients who use the network on a daily basis from various locations. We've had situations where network routing (outside of our control) would not allow people to reach our main OpenVPN server whilst the other locations were connectable. Also any time someone outside the office wants to fetch something from any of the servers (say, a 500 MB code repository), a whopping 20 KB/s download speed is just unacceptable these days (did I mention slow DSL? ok). We had to implement traffic shaping on this server since maxing out this connection was fairly trivial. I had the thought of running two (or more) OpenVPN servers in the network. These would have to have the same subnet though, as our application relies on virtual network's IP addresses for some of its core functionality. The clients would also preferably retain the same IP addresses but that's not vital. For simplicity, lets call the current server office and the second server I'm setting up, cloud. Call the server on the T1 phone. This proved to be rather complex because as soon as I connect to cloud, I cannot see office. Any routes to a server that would go through office also do not work while I'm connected to cloud (no ping, nothing) and vice-versa. There's no rules for iptables that would be blocking the traffic either. Recently I came across this article on linuxjournal but the solution they provide seems to only cover the use of two servers and somewhat outdated (can't even find much documentation, their wiki is offline). They also state that adding more servers would be a complex task. Ideally I would like to keep the existing server office running the virtual network and also run the OpenVPN daemon on the cloud and phone servers (100 Mbit and very reliable connection, respectively) so that we're on safe ground in case of a hardware failure, DSL failure, etc. So, in essence, I'm looking for a highly available OpenVPN solution (fix, patch, hack, tweak, whatever you want to call it) that will accept connections on multiple hosts (2 or more) whilst keeping the same IP address subnet regardless of the server to which you connect to. Thanks for reading and sorry for the long post, I hope it gets the point across :P

    Read the article

  • High availability for databases (DRBD + GFS)?

    - by EvanAlm
    Does it work to have like an MySQL (or any other relational database) on the GFS (with DRBD) and have multiple nodes reading and writing to it? Is that the "best" way of providing a HA database/application setup if so? Is RHEL (cluster suite) a good way to set up this? (or centos)

    Read the article

  • SAN/NAS with high availability?

    - by netvope
    I have two servers that I plan to use for storage. Each of them has a few SATA disks directly attached. I want the storage to be available even if one of the storage servers is down (preferably the clients wouldn't even notice that the fail-over, although I'm not sure if this is possible). The clients may access the storage via NFS and samba, but this is not a must; I could use something else if needed. I found this guide, Installing and Configuring Openfiler with DRBD and Heartbeat, which apparently does the thing I want. It relies on three components, Openfiler, DRBD, and Heartbeat, and all three of them need to be configured separately. I'm wondering are there simpler solutions? Is using DRBD+Heartbeat the best practice for a situation like mine? I'm also interested to know if there are alternatives that don't depend on DRBD.

    Read the article

  • High Load average threshold in linux

    - by user2481010
    My one of friend said that his server load average sometime goes above 500-1000, for me it is strange value because I never saw load average more than 10. I asked him give me some snapshot of top and memory usages, he gave following details: TOP USAGES top - 06:06:03 up 117 days, 23:02, 2 users, load average: 147.37, 44.57, 15.95 Tasks: 116 total, 2 running, 113 sleeping, 0 stopped, 1 zombie Cpu(s): 16.6%us, 6.9%sy, 0.0%ni, 9.2%id, 66.5%wa, 0.0%hi, 0.8%si, 0.0%st Mem: 8161648k total, 7779528k used, 382120k free, 3296k buffers Swap: 5242872k total, 1293072k used, 3949800k free, 168660k cached Free $ free -gt total used free shared buffers cached Mem: 7 6 1 0 0 4 -/+ buffers/cache: 1 5 Swap: 4 0 4 Total: 12 6 6 Total cpu $ nproc 8 my question is it possible load average more than 100 on 8 core,12 GB mem Server? because I read many tutorial,article on load average, it said that thumb rule is "number of cores = max load" according to thumb rule here is max load average 16 then how his server running with 147.37 load server? he said that it is least value (147.37) some time goes more than 500.

    Read the article

  • 2 servers, high availability and faster response

    - by user17886
    I recently bought a second webserver because I worry about hardware failure of my old server. Now that I have that second server I wish to do a little more then just have one server standby and replicate all day. As long as it's there I might as well get some advantage our of it ! I have a website powered by ubuntu 12.04, nginx, php-fpm, apc, mysql (5.5) and couchdb. Im currently testing configurations where i can achieve failover AND make good use of the extra harware for faster responses / distributed load. The setup I am testing nowinvolves heartbeat for ip failover and two identical servers. Of the two servers only one has a public ip adress. If one server crashes the other server takes over the public ip adress. On an incoming request nginx forwards the request tot php-fpm to either server a of server b (50/50 if both servers are alive). Once the request has been send to php-fpm both servers look at localhost for the mysql server. I use master-master mysql replication for this. The file system is synced with lsyncd. This works pretty well but Im reading it's discouraged by the (mysql) community. Another option I could think of is to use one server as a mysql master and one server as a web/php server. The servers would still sync their filesystem, would still run the same duplicate software (nginx,mysql) but master slave mysql replication could be used. As long as bother servers are alive I could just prefer nginx to listen to ip a and mysql to ip b. If one server is down, the other server could take over the task of the other server, simply by ip switching. But im completely new at this so I would greatly value your expert advice. Is either of the two setups any good ? If you have any thoughts on this please let me know ! PS, virtualisation, hosting on different locations or active/passive setups are not solutions im looking for. I find virtual server either too slow or too expensive. I already have a passive failover on another location. But in case of a crash I found the site was still unreachable for too long due to dns caching.

    Read the article

  • As a programmer, should I know low and high-level programming languages?

    - by job
    I been contacted to do some work remote controlling LEDs displays over TCP/IP, but my experience and preparation is mostly about high-level programming language. I said that to the person who contact me about the work and he told me that: "if you call yourself a programmer you should know all these things" Should a programmer really know the details of low-level programming? Or can I treat it as a black box concept, as theoretical knowledge but not necessarily doing it or implementing low level language solutions, having in mind that low-level programming is not my expertise?

    Read the article

  • Books or resources for high-loaded sites.

    - by Alex
    Currently I'm developing high-loaded financial portal(we use LAMP to run our project). There are great number of incoming data to be processed and stored. So optimization tasks become very important for us. Could you suggest books, articles or resources, that discover optimization questions (especially bboks). NOTE: At the moment I'm reading great book High Performance MySQL, but besides I want to know other facilities of optimization.

    Read the article

  • About High Availabiltity

    - by Invincible
    I know this is not perfect place to ask this question. Can anybody suggest some good resource or book on High-Availability? I want to learn as much as I can on high-availability before start building my system. Thanks in advance!

    Read the article

  • IIS 7 SSO stops working during high CPU load? [migrated]

    - by DanB
    On our IIS7 site (Windows 2008 Server), we have set up single sign-on (SSO). It seems to work fine most of the time, but when the CPU load becomes high, SSO authentication completely stops working. I did some research and tried this suggestion to increase the max number of worker processes in the default app pool, but the increase did not help. Some details: The site is a WordPress blog. The server has plenty of RAM (2 GB) and free disk space. SSO is achieved by putting a copy of the WordPress login page (wp-login.php) into a subfolder below the root that has anonymous authentication disabled, and then redirecting the browser to it. This was the recommendation of Microsoft given to our consultants. To increase CPU load for testing, I have three scripts hit the home page simultaneously, over and over. This drives CPU to 100%. When these scripts are running, SSO authentication simply doesn't happen. As soon as I stop the scripts, SSO works again. (I should mention that the SSO problem also happens when many users visit the site at once....) The WordPress database process (mysqld) is not stressed at all by the scripts. I would be happy to provide further diagnostics. Any help appreciated!

    Read the article

  • Why is Python used for high-performance/scientific computing (but Ruby isn't)?

    - by Cyclops
    There's a quote from a PyCon 2011 talk that goes: At least in our shop (Argonne National Laboratory) we have three accepted languages for scientific computing. In this order they are C/C++, Fortran in all its dialects, and Python. You’ll notice the absolute and total lack of Ruby, Perl, Java. It was in the more general context of high-performance computing. Granted the quote is only from one shop, but another question about languages for HPC, also lists Python as one to learn (and not Ruby). Now, I can understand C/C++ and Fortran being used in that problem-space (and Perl/Java not being used). But I'm surprised that there would be a major difference in Python and Ruby use for HPC, given that they are fairly similar. (Note - I'm a fan of Python, but have nothing against Ruby). Is there some specific reason why the one language took off? Is it about the libraries available? Some specific language features? The community? Or maybe just historical contigency, and it could have gone the other way?

    Read the article

  • The downsides of using nginx as a primary web server?

    - by FractalizeR
    Hello. I've seen millions of websites using nginx as a proxifying webserver working together with Apache. But I've seen very few servers running nginx only as their default webserver. What are the main downsides of such config? I can see some: Inability to use per-directory config files like .htaccess so every configuration change should be done to main server config file and requires server reload. But pecl htscanner can compensate them for php settings Unavailability of mod_php for nginx, which can be compensated by php-fpm for example. What are others? Why don't people just drop Apache and move to nginx or any other lightweight solution? May be, there are some special reasons?

    Read the article

  • Insufficient channel capacity of 1GBit

    - by Roman S
    There is a Caching Server (Varnish): it receives data from Amazon S3 on request, saves it for some time and gives it to the client. We have encountered the problem of insufficient channel capacity of 1GBit. Peak load within 4 hours completely chokes the channel. Server performance is sufficient for now. Approximately 4.5TB of data are transmitted per day. More than 100TB are accumulated per month. The first thought that comes to mind is simply to add one more 1GBit port and sleep peacefully until 2GBit are not enough (it may happen quite quickly) or one server is not able to handle it. And then we just need to add new Caching Servers. But now we need a Load Balancer, which will send requests on one and the same URL, always on one and the same server (to avoid multiple copies of the same cached objects). Here are the questions: Does a Balancer need a band equal to sum of all bands of Caching Servers? What shall we do in case there are no ports in a Balancer? Should we add more Balancers or solve the problem by means of Round robin DNS? What are the standard approaches to such problems? Can anyone advise hosting-companies, which can solve this problem? We are interested in American and European markets.

    Read the article

  • High PageIOLatch_SH Waits with High Drive Idle times

    - by Marty Trenouth
    We are experiencing high volume of PageIOLatch_SH waits on our database (row counts in the Billions). However it seems that our drive Idle time Percentage hovers around 50-60 percent. CPU usage is nill. The Database Tuning Advisor gives no suggestions for optimization. The query plan (actual) from the single stored procedure used on the database puts the majority of the expense on index seek (yeah I know these should be optimial) operations. Anyone have suggestions of how to increase throughput?

    Read the article

  • Normalize or Denormalize in high traffic websites

    - by Inam Jameel
    what is the best practice for database design for high traffic websites like this one stackoverflow? should one must use normalize database for record keeping or normalized technique or combination of both? is it sensible to design normalize database as main database for record keeping to reduce redundancy and at the same time maintain another denormalized form of database for fast searching? or main database should be denormalize and one can make normalized views in the application level for fast database operations? or beside above mentioned approach? what is the best practice of designing high traffic websites???

    Read the article

  • Is your team is a high-performing team?

    As a child I can remember looking out of the car window as my father drove along the Interstate in Florida while seeing prisoners wearing bright orange jump suits and prison guards keeping a watchful eye on them. The prisoners were taking part in a prison road gang. These road gangs were formed to help the state maintain the state highway infrastructure. The prisoner’s primary responsibilities are to pick up trash and debris from the roadway. This is a prime example of a work group or working group used by most prison systems in the United States. Work groups or working groups can be defined as a collection of individuals or entities working together to achieve a specific goal or accomplish a specific set of tasks. Typically these groups are only established for a short period of time and are dissolved once the desired outcome has been achieved. More often than not group members usually feel as though they are expendable to the group and some even dread that they are even in the group. "A team is a small number of people with complementary skills who are committed to a common purpose, performance goals, and approach for which they are mutually accountable." (Katzenbach and Smith, 1993) So how do you determine that a team is a high-performing team?  This can be determined by three base line criteria that include: consistently high quality output, the promotion of personal growth and well being of all team members, and most importantly the ability to learn and grow as a unit. Initially, a team can successfully create high-performing output without meeting all three criteria, however this will erode over time because team members will feel detached from the group or that they are not growing then the quality of the output will decline. High performing teams are similar to work groups because they both utilize a collection of individuals or entities to accomplish tasks. What distinguish a high-performing team from a work group are its characteristics. High-performing teams contain five core characteristics. These characteristics are what separate a group from a team. The five characteristics of a high-performing team include: Purpose, Performance Measures, People with Tasks and Relationship Skills, Process, and Preparation and Practice. A high-performing team is much more than a work group, and typically has a life cycle that can vary from team to team. The standard team lifecycle consists of five states and is comparable to a human life cycle. The five states of a high-performing team lifecycle include: Formulating, Storming, Normalizing, Performing, and Adjourning. The Formulating State of a team is first realized when the team members are first defined and roles are assigned to all members. This initial stage is very important because it can set the tone for the team and can ultimately determine its success or failure. In addition, this stage requires the team to have a strong leader because team members are normally unclear about specific roles, specific obstacles and goals that my lay ahead of them.  Finally, this stage is where most team members initially meet one another prior to working as a team unless the team members already know each other. The Storming State normally arrives directly after the formulation of a new team because there are still a lot of unknowns amongst the newly formed assembly. As a general rule most of the parties involved in the team are still getting used to the workload, pace of work, deadlines and the validity of various tasks that need to be performed by the group.  In this state everything is questioned because there are so many unknowns. Items commonly questioned include the credentials of others on the team, the actual validity of a project, and the leadership abilities of the team leader.  This can be exemplified by looking at the interactions between animals when they first meet.  If we look at a scenario where two people are walking directly toward each other with their dogs. The dogs will automatically enter the Storming State because they do not know the other dog. Typically in this situation, they attempt to define which is more dominating via play or fighting depending on how the dogs interact with each other. Once dominance has been defined and accepted by both dogs then they will either want to play or leave depending on how the dogs interacted and other environmental variables. Once the Storming State has been realized then the Normalizing State takes over. This state is entered by a team once all the questions of the Storming State have been answered and the team has been tested by a few tasks or projects.  Typically, participants in the team are filled with energy, and comradery, and a strong alliance with team goals and objectives.  A high school football team is a perfect example of the Normalizing State when they start their season.  The player positions have been assigned, the depth chart has been filled and everyone is focused on winning each game. All of the players encourage and expect each other to perform at the best of their abilities and are united by competition from other teams. The Performing State is achieved by a team when its history, working habits, and culture solidify the team as one working unit. In this state team members can anticipate specific behaviors, attitudes, reactions, and challenges are seen as opportunities and not problems. Additionally, each team member knows their role in the team’s success, and the roles of others. This is the most productive state of a group and is where all the time invested working together really pays off. If you look at an Olympic figure skating team skate you can easily see how the time spent working together benefits their performance. They skate as one unit even though it is comprised of two skaters. Each skater has their routine completely memorized as well as their partners. This allows them to anticipate each other’s moves on the ice makes their skating look effortless. The final state of a team is the Adjourning State. This state is where accomplishments by the team and each individual team member are recognized. Additionally, this state also allows for reflection of the interactions between team members, work accomplished and challenges that were faced. Finally, the team celebrates the challenges they have faced and overcome as a unit. Currently in the workplace teams are divided into two different types: Co-located and Distributed Teams. Co-located teams defined as the traditional group of people working together in an office, according to Andy Singleton of Assembla. This traditional type of a team has dominated business in the past due to inadequate technology, which forced workers to primarily interact with one another via face to face meetings.  Team meetings are primarily lead by the person with the highest status in the company. Having personally, participated in meetings of this type, usually a select few of the team members dominate the flow of communication which reduces the input of others in group discussions. Since discussions are dominated by a select few individuals the discussions and group discussion are skewed in favor of the individuals who communicate the most in meetings. In addition, Team members might not give their full opinions on a topic of discussion in part not to offend or create controversy amongst the team and can alter decision made in meetings towards those of the opinions of the dominating team members. Distributed teams are by definition spread across an area or subdivided into separate sections. That is exactly what distributed teams when compared to a more traditional team. It is common place for distributed teams to have team members across town, in the next state, across the country and even with the advances in technology over the last 20 year across the world. These teams allow for more diversity compared to the other type of teams because they allow for more flexibility regarding location. A team could consist of a 30 year old male Italian project manager from New York, a 50 year old female Hispanic from California and a collection of programmers from India because technology allows them to communicate as if they were standing next to one another.  In addition, distributed team members consult with more team members prior to making decisions compared to traditional teams, and take longer to come to decisions due to the changes in time zones and cultural events. However, team members feel more empowered to speak out when they do not agree with the team and to notify others of potential issues regarding the work that the team is doing. Virtual teams which are a subset of the distributed team type is changing organizational strategies due to the fact that a team can now in essence be working 24 hrs a day because of utilizing employees in various time zones and locations.  A primary example of this is with customer services departments, a company can have multiple call centers spread across multiple time zones allowing them to appear to be open 24 hours a day while all a employees work from 9AM to 5 PM every day. Virtual teams also allow human resources departments to go after the best talent for the company regardless of where the potential employee works because they will be a part of a virtual team all that is need is the proper technology to be setup to allow everyone to communicate. In addition to allowing employees to work from home, the company can save space and resources by not having to provide a desk for every team member. In fact, those team members that randomly come into the office can actually share one desk amongst multiple people. This is definitely a cost cutting plus given the current state of the economy. One thing that can turn a team into a high-performing team is leadership. High-performing team leaders need to focus on investing in ongoing personal development, provide team members with direction, structure, and resources needed to accomplish their work, make the right interventions at the right time, and help the team manage boundaries between the team and various external parties involved in the teams work. A team leader needs to invest in ongoing personal development in order to effectively manage their team. People have said that attitude is everything; this is very true about leaders and leadership. A team takes on the attitudes and behaviors of its leaders. This can potentially harm the team and the team’s output. Leaders must concentrate on self-awareness, and understanding their team’s group dynamics to fully understand how to lead them. In addition, always learning new leadership techniques from other effective leaders is also very beneficial. Providing team members with direction, structure, and resources that they need to accomplish their work collectively sounds easy, but it is not.  Leaders need to be able to effectively communicate with their team on how their work helps the company reach for its organizational vision. Conversely, the leader needs to allow his team to work autonomously within specific guidelines to turn the company’s vision into a reality.  This being said the team must be appropriately staffed according to the size of the team’s tasks and their complexity. These tasks should be clear, and be meaningful to the company’s objectives and allow for feedback to be exchanged with the leader and the team member and the leader and upper management. Now if the team is properly staffed, and has a clear and full understanding of what is to be done; the company also must supply the workers with the proper tools to achieve the tasks that they are asked to do. No one should be asked to dig a hole without being given a shovel.  Finally, leaders must reward their team members for accomplishments that they achieve. Awards could range from just a simple congratulatory email, a party to close the completion of a large project, or other monetary rewards. Managing boundaries is very important for team leaders because it can alter attitudes of team members and can add undue stress to the team which will force them to loose focus on the tasks at hand for the group. Team leaders should promote communication between team members so that burdens are shared amongst the team and solutions can be derived from hearing the opinions of multiple sources. This also reinforces team camaraderie and working as a unit. Team leaders must manage the type and timing of interventions as to not create an even bigger mess within the team. Poorly timed interventions can really deflate team members and make them question themselves. This could really increase further and undue interventions by the team leader. Typically, the best time for interventions is when the team is just starting to form so that all unproductive behaviors are removed from the team and that it can retain focus on its agenda. If an intervention is effectively executed the team will feel energized about the work that they are doing, promote communication and interaction amongst the group and improve moral overall. High-performing teams are very import to organizations because they consistently produce high quality output and develop a collective purpose for their work. This drive to succeed allows team members to utilize specific talents allowing for growth in these areas.  In addition, these team members usually take on a sense of ownership with their projects and feel that the other team members are irreplaceable. References: http://blog.assembla.com/assemblablog/tabid/12618/bid/3127/Three-ways-to-organize-your-team-co-located-outsourced-or-global.aspx Katzenbach, J.R. & Smith, D.K. (1993). The Wisdom of Teams: Creating the High-performance Organization. Boston: Harvard Business School.

    Read the article

  • hosting a high traffic facebook app (game)

    - by z3cko
    we are currently developing a high traffic facebook application. all the traffic will be within one month, where there are 500.000 to 1.000.000 expected users. after that month, the game is over and we have a winner - so the app will be archived. we are currently planning to develop the application with ruby on rails and searching for hosting options that can deal with the traffic. the problem is not so much the users, but the peak values: we will have around 500.000 requests coming daily within a short timeframe (lets say within 3 minutes in the worst case) we are expecting 500.000 to 1.000.000 users of the application, with peaks at 1:00pm (timezone GMT+1), where most (up to 80% of the users) will send most of the requests. the requests are from 11th of june to 11.july - after that, the app/game is closed/over. we are currently developing an aggressive caching mechanism - currently we are thinking about 2 or 3 small apps/webservices, that will handle the load. the load is distributed as follows: a) main application, cached data (11 screens, 200k each) b) voting: every day until 1:00pm (timezone GMT+1) - every user votes with about 10k data sent, high concurrent peak values! questions: is there any specific application setup that is recommendable? are there any hosting partners that can be recommended? thanks!

    Read the article

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

< Previous Page | 1 2 3 4 5 6 7 8 9 10 11 12  | Next Page >