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• Why load increase ,ssd iops increase but cpu iowait decrease?

  - by mq44944

  There is a strange thing on my server which has a mysql running on it. The QPS is more than 4000 but TPS is less than 20. The server load is more than 80 and cpu usr is more than 86% but iowait is less than 8%. The disk iops is more than 16000 and util of disk is more than 99%. When the QPS decreases, the load decreases, the cpu iowait increases. I can't catch this! root@mypc # dmidecode | grep "Product Name" Product Name: PowerEdge R510 Product Name: 084YMW root@mypc # megacli -PDList -aALL |grep "Inquiry Data" Inquiry Data: SEAGATE ST3600057SS ES656SL316PT Inquiry Data: SEAGATE ST3600057SS ES656SL30THV Inquiry Data: ATA INTEL SSDSA2CW300362CVPR201602A6300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR2044037K300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR204402PX300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR204403WN300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR202000HU300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR202001E7300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR204402WE300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR204404E5300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR204401QF300EGN Inquiry Data: ATA INTEL SSDSA2CW300362CVPR20450001300EGN the mysql data files lie on the ssd disks which are organizaed using RAID 10. root@mypc # megacli -LDInfo -L1 -a0 Adapter 0 -- Virtual Drive Information: Virtual Disk: 1 (Target Id: 1) Name: RAID Level: Primary-1, Secondary-0, RAID Level Qualifier-0 Size:1427840MB State: Optimal Stripe Size: 64kB Number Of Drives:2 Span Depth:5 Default Cache Policy: WriteThrough, ReadAheadNone, Direct, No Write Cache if Bad BBU Current Cache Policy: WriteThrough, ReadAheadNone, Direct, No Write Cache if Bad BBU Access Policy: Read/Write Disk Cache Policy: Disk's Default Exit Code: 0x00 -------- -----load-avg---- ---cpu-usage--- ---swap--- -------------------------io-usage----------------------- -QPS- -TPS- -Hit%- time | 1m 5m 15m |usr sys idl iow| si so| r/s w/s rkB/s wkB/s queue await svctm %util| ins upd del sel iud| lor hit| 09:05:29|79.80 64.49 42.00| 82 7 6 5| 0 0|16421.1 10.6262705.9 85.2 8.3 0.5 0.1 99.5| 0 0 0 3968 0| 495482 96.58| 09:05:30|79.80 64.49 42.00| 79 7 8 6| 0 0|15907.4 230.6254409.7 6357.5 8.4 0.5 0.1 98.5| 0 0 0 4195 0| 496434 96.68| 09:05:31|81.34 65.07 42.31| 81 7 7 5| 0 0|16198.7 8.6259029.2 99.8 8.1 0.5 0.1 99.3| 0 0 0 4220 0| 508983 96.70| 09:05:32|81.34 65.07 42.31| 82 7 5 5| 0 0|16746.6 8.7267853.3 92.4 8.5 0.5 0.1 99.4| 0 0 0 4084 0| 503834 96.54| 09:05:33|81.34 65.07 42.31| 81 7 6 5| 0 0|16498.7 9.6263856.8 92.3 8.0 0.5 0.1 99.3| 0 0 0 4030 0| 507051 96.60| 09:05:34|81.34 65.07 42.31| 80 8 7 6| 0 0|16328.4 11.5261101.6 95.8 8.1 0.5 0.1 98.3| 0 0 0 4119 0| 504409 96.63| 09:05:35|81.31 65.33 42.52| 82 7 6 5| 0 0|16374.0 8.7261921.9 92.5 8.1 0.5 0.1 99.7| 0 0 0 4127 0| 507279 96.66| 09:05:36|81.31 65.33 42.52| 81 8 6 5| 0 0|16496.2 8.6263832.0 84.5 8.5 0.5 0.1 99.2| 0 0 0 4100 0| 505054 96.59| 09:05:37|81.31 65.33 42.52| 82 8 6 4| 0 0|16239.4 9.6259768.8 84.3 8.0 0.5 0.1 99.1| 0 0 0 4273 0| 510621 96.72| 09:05:38|81.31 65.33 42.52| 81 7 6 5| 0 0|16349.6 8.7261439.2 81.4 8.2 0.5 0.1 98.9| 0 0 0 4171 0| 510145 96.67| 09:05:39|81.31 65.33 42.52| 82 7 6 5| 0 0|16116.8 8.7257667.6 96.5 8.0 0.5 0.1 99.1| 0 0 0 4348 0| 513093 96.74| 09:05:40|79.60 65.24 42.61| 79 7 7 7| 0 0|16154.2 242.9258390.4 6388.4 8.5 0.5 0.1 99.0| 0 0 0 4033 0| 507244 96.70| 09:05:41|79.60 65.24 42.61| 79 7 8 6| 0 0|16583.1 21.2265129.6 173.5 8.2 0.5 0.1 99.1| 0 0 0 3995 0| 501474 96.57| 09:05:42|79.60 65.24 42.61| 81 8 6 5| 0 0|16281.0 9.7260372.2 69.5 8.3 0.5 0.1 98.7| 0 0 0 4221 0| 509322 96.70| 09:05:43|79.60 65.24 42.61| 80 7 7 6| 0 0|16355.3 8.7261515.5 104.3 8.2 0.5 0.1 99.6| 0 0 0 4087 0| 502052 96.62| -------- -----load-avg---- ---cpu-usage--- ---swap--- -------------------------io-usage----------------------- -QPS- -TPS- -Hit%- time | 1m 5m 15m |usr sys idl iow| si so| r/s w/s rkB/s wkB/s queue await svctm %util| ins upd del sel iud| lor hit| 09:05:44|79.60 65.24 42.61| 83 7 5 4| 0 0|16469.4 11.6263387.0 138.8 8.2 0.5 0.1 98.7| 0 0 0 4292 0| 509979 96.65| 09:05:45|79.07 65.37 42.77| 80 7 6 6| 0 0|16659.5 9.7266478.7 85.0 8.4 0.5 0.1 98.5| 0 0 0 3899 0| 496234 96.54| 09:05:46|79.07 65.37 42.77| 78 7 7 8| 0 0|16752.9 8.7267921.8 97.1 8.4 0.5 0.1 98.9| 0 0 0 4126 0| 508300 96.57| 09:05:47|79.07 65.37 42.77| 82 7 6 5| 0 0|16657.2 9.6266439.3 84.3 8.3 0.5 0.1 98.9| 0 0 0 4086 0| 502171 96.57| 09:05:48|79.07 65.37 42.77| 79 8 6 6| 0 0|16814.5 8.7268924.1 77.6 8.5 0.5 0.1 99.0| 0 0 0 4059 0| 499645 96.52| 09:05:49|79.07 65.37 42.77| 81 7 6 5| 0 0|16553.0 6.8264708.6 42.5 8.3 0.5 0.1 99.4| 0 0 0 4249 0| 501623 96.60| 09:05:50|79.63 65.71 43.01| 79 7 7 7| 0 0|16295.1 246.9260475.0 6442.4 8.7 0.5 0.1 99.1| 0 0 0 4231 0| 511032 96.70| 09:05:51|79.63 65.71 43.01| 80 7 6 6| 0 0|16568.9 8.7264919.7 104.7 8.3 0.5 0.1 99.7| 0 0 0 4272 0| 517177 96.68| 09:05:53|79.63 65.71 43.01| 79 7 7 6| 0 0|16539.0 8.6264502.9 87.6 8.4 0.5 0.1 98.9| 0 0 0 3992 0| 496728 96.52| 09:05:54|79.63 65.71 43.01| 79 7 7 7| 0 0|16527.5 11.6264363.6 92.6 8.5 0.5 0.1 98.8| 0 0 0 4045 0| 502944 96.59| 09:05:55|79.63 65.71 43.01| 80 7 7 6| 0 0|16374.7 12.5261687.2 134.9 8.6 0.5 0.1 99.2| 0 0 0 4143 0| 507006 96.66| 09:05:56|76.05 65.20 42.96| 77 8 8 8| 0 0|16464.9 9.6263314.3 111.9 8.5 0.5 0.1 98.9| 0 0 0 4250 0| 505417 96.64| 09:05:57|76.05 65.20 42.96| 79 7 6 7| 0 0|16460.1 8.8263283.2 93.4 8.3 0.5 0.1 98.8| 0 0 0 4294 0| 508168 96.66| 09:05:58|76.05 65.20 42.96| 80 7 7 7| 0 0|16176.5 9.6258762.1 127.3 8.3 0.5 0.1 98.9| 0 0 0 4160 0| 509349 96.72| 09:05:59|76.05 65.20 42.96| 75 7 9 10| 0 0|16522.0 10.7264274.6 93.1 8.6 0.5 0.1 97.5| 0 0 0 4034 0| 492623 96.51| -------- -----load-avg---- ---cpu-usage--- ---swap--- -------------------------io-usage----------------------- -QPS- -TPS- -Hit%- time | 1m 5m 15m |usr sys idl iow| si so| r/s w/s rkB/s wkB/s queue await svctm %util| ins upd del sel iud| lor hit| 09:06:00|76.05 65.20 42.96| 79 7 7 7| 0 0|16369.6 21.2261867.3 262.5 8.4 0.5 0.1 98.9| 0 0 0 4305 0| 494509 96.59| 09:06:01|75.33 65.23 43.09| 73 6 9 12| 0 0|15864.0 209.3253685.4 6238.0 10.0 0.6 0.1 98.7| 0 0 0 3913 0| 483480 96.62| 09:06:02|75.33 65.23 43.09| 73 7 8 12| 0 0|15854.7 12.7253613.2 93.6 11.0 0.7 0.1 99.0| 0 0 0 4271 0| 483771 96.64| 09:06:03|75.33 65.23 43.09| 75 7 9 9| 0 0|16074.8 8.7257104.3 81.7 8.1 0.5 0.1 98.5| 0 0 0 4060 0| 480701 96.55| 09:06:04|75.33 65.23 43.09| 76 7 8 9| 0 0|16221.7 9.7259500.1 139.4 8.1 0.5 0.1 97.6| 0 0 0 3953 0| 486774 96.56| 09:06:05|74.98 65.33 43.24| 78 7 8 8| 0 0|16330.7 8.7261166.5 85.3 8.2 0.5 0.1 98.5| 0 0 0 3957 0| 481775 96.53| 09:06:06|74.98 65.33 43.24| 75 7 9 9| 0 0|16093.7 11.7257436.1 93.7 8.2 0.5 0.1 99.2| 0 0 0 3938 0| 489251 96.60| 09:06:07|74.98 65.33 43.24| 75 7 5 13| 0 0|15758.9 19.2251989.4 188.2 14.7 0.9 0.1 99.7| 0 0 0 4140 0| 494738 96.70| 09:06:08|74.98 65.33 43.24| 69 7 10 15| 0 0|16166.3 8.7258474.9 81.2 8.9 0.5 0.1 98.7| 0 0 0 3993 0| 487162 96.58| 09:06:09|74.98 65.33 43.24| 74 7 9 10| 0 0|16071.0 8.7257010.9 93.3 8.2 0.5 0.1 99.2| 0 0 0 4098 0| 491557 96.61| 09:06:10|70.98 64.66 43.14| 71 7 9 12| 0 0|15549.6 216.1248701.1 6188.7 8.3 0.5 0.1 97.8| 0 0 0 3879 0| 480832 96.66| 09:06:11|70.98 64.66 43.14| 71 7 10 13| 0 0|16233.7 22.4259568.1 257.1 8.2 0.5 0.1 99.2| 0 0 0 4088 0| 493200 96.62| 09:06:12|70.98 64.66 43.14| 78 7 8 7| 0 0|15932.4 10.6254779.5 108.1 8.1 0.5 0.1 98.6| 0 0 0 4168 0| 489838 96.63| 09:06:13|70.98 64.66 43.14| 71 8 9 12| 0 0|16255.9 11.5259902.3 103.9 8.3 0.5 0.1 98.0| 0 0 0 3874 0| 481246 96.52| 09:06:14|70.98 64.66 43.14| 60 6 16 18| 0 0|15621.0 9.7249826.1 81.9 8.0 0.5 0.1 99.3| 0 0 0 3956 0| 480278 96.65|

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• Does Zend application server provide any sort of pushed-based messaging architecture support?

  - by Alex

  Does Zend application server provide any sort of pushed-based messaging architecture support?I mean some different message-oriented middlewares that can be used for the push-based architecture or email support?There is a need in provision of the non web-based interface for certain users of the website who would get regular messages notifying them of different special offers in their field of interest(it should be push-based)

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• How to force two process to run on the same CPU?

  - by kovan

  Context: I'm programming a software system that consists of multiple processes. It is programmed in C++ under Linux. and they communicate among them using Linux shared memory. Usually, in software development, is in the final stage when the performance optimization is made. Here I came to a big problem. The software has high performance requirements, but in machines with 4 or 8 CPU cores (usually with more than one CPU), it was only able to use 3 cores, thus wasting 25% of the CPU power in the first ones, and more than 60% in the second ones. After many research, and having discarded mutex and lock contention, I found out that the time was being wasted on shmdt/shmat calls (detach and attach to shared memory segments). After some more research, I found out that these CPUs, which usually are AMD Opteron and Intel Xeon, use a memory system called NUMA, which basically means that each processor has its fast, "local memory", and accessing memory from other CPUs is expensive. After doing some tests, the problem seems to be that the software is designed so that, basically, any process can pass shared memory segments to any other process, and to any thread in them. This seems to kill performance, as process are constantly accessing memory from other processes. Question: Now, the question is, is there any way to force pairs of processes to execute in the same CPU?. I don't mean to force them to execute always in the same processor, as I don't care in which one they are executed, altough that would do the job. Ideally, there would be a way to tell the kernel: If you schedule this process in one processor, you must also schedule this "brother" process (which is the process with which it communicates through shared memory) in that same processor, so that performance is not penalized.

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• When using Direct3D, how much math is being done on the CPU?

  - by zirgen

  Context: I'm just starting out. I'm not even touching the Direct3D 11 API, and instead looking at understanding the pipeline, etc. From looking at documentation and information floating around the web, it seems like some calculations are being handled by the application. That, is, instead of simply presenting matrices to multiply to the GPU, the calculations are being done by a math library that operates on the CPU. I don't have any particular resources to point to, although I guess I can point to the XNA Math Library or the samples shipped in the February DX SDK. When you see code like mViewProj = mView * mProj;, that projection is being calculated on the CPU. Or am I wrong? If you were writing a program, where you can have 10 cubes on the screen, where you can move or rotate cubes, as well as viewpoint, what calculations would you do on the CPU? I think I would store the geometry for the a single cube, and then transform matrices representing the actual instances. And then it seems I would use the XNA math library, or another of my choosing, to transform each cube in model space. Then get the coordinates in world space. Then push the information to the GPU. That's quite a bit of calculation on the CPU. Am I wrong? Am I reaching conclusions based on too little information and understanding? What terms should I Google for, if the answer is STFW? Or if I am right, why aren't these calculations being pushed to the GPU as well?

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• Why would more CPU cores on virtual machine slow compile times?

  - by Sid

  [edit#2] If anyone from VMWare can hit me up with a copy of VMWare Fusion, I'd be more than happy to do the same as a VirtualBox vs VMWare comparison. Somehow I suspect the VMWare hypervisor will be better tuned for hyperthreading (see my answer too) I'm seeing something curious. As I increase the number of cores on my Windows 7 x64 virtual machine, the overall compile time increases instead of decreasing. Compiling is usually very well suited for parallel processing as in the middle part (post dependency mapping) you can simply call a compiler instance on each of your .c/.cpp/.cs/whatever file to build partial objects for the linker to take over. So I would have imagined that compiling would actually scale very well with # of cores. But what I'm seeing is: 8 cores: 1.89 sec 4 cores: 1.33 sec 2 cores: 1.24 sec 1 core: 1.15 sec Is this simply a design artifact due to a particular vendor's hypervisor implementation (type2:virtualbox in my case) or something more pervasive across more VMs to make hypervisor implementations more simpler? With so many factors, I seem to be able to make arguments both for and against this behavior - so if someone knows more about this than me, I'd be curious to read your answer. Thanks Sid [edit:addressing comments] @MartinBeckett: Cold compiles were discarded. @MonsterTruck: Couldn't find an opensource project to compile directly. Would be great but can't screwup my dev env right now. @Mr Lister, @philosodad: Have 8 hw threads, using VirtualBox, so should be 1:1 mapping without emulation @Thorbjorn: I have 6.5GB for the VM and a smallish VS2012 project - it's quite unlikely that I'm swapping in/out trashing the page file. @All: If someone can point to an open source VS2010/VS2012 project, that might be a better community reference than my (proprietary) VS2012 project. Orchard and DNN seem to need environment tweaking to compile in VS2012. I really would like to see if someone with VMWare Fusion also sees this (for VMWare vs VirtualBox compartmentalization) Test details: Hardware: Macbook Pro Retina CPU : Core i7 @ 2.3Ghz (quad core, hyper threaded = 8 cores in windows task manager) Memory : 16 GB Disk : 256GB SSD Host OS: Mac OS X 10.8 VM type: VirtualBox 4.1.18 (type 2 hypervisor) Guest OS: Windows 7 x64 SP1 Compiler: VS2012 compiling a solution with 3 C# Azure projects Compile times measure by VS2012 plugin called 'VSCommands' All tests run 5 times, first 2 runs discarded, last 3 averaged

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• Adatbázis szerver konszolidáció Oracle technológiákkal - eroforrás allokálás

  - by Lajos Sárecz

  Szerver konszolidációnál alapmegoldás a virtualizáció, pedig az Oracle Database rendelkezik olyan képességekkel, melyekkel a virtualizáció elonyeit élvezhetjük, ám teljesítményben felülmúljuk azt. Több adatbázis konszolidációját meg lehet oldani egy nagy szerveren, vagy egy több szerverbol álló klaszteren. Bármelyik megoldást is választjuk (ezek elonyeivel és hátrányaival most nem foglalkozok), az egyik legfontosabb megoldandó probléma, hogy biztonsággal el tudjuk oket szeparálni akár adatbiztonsági, akár eroforrás kezelési szempontból. A szoftveres és hardveres virtualizációk lehetové teszik, hogy a szerver eroforrásait több virtuális szerver között felosszuk, ezáltal elszeparálhatók a párhuzamosan futó adatbázis példányok. Ezek a megoldások általában költségesek, plusz adminisztrációt jelentenek és teljesítmény csökkenést okoznak. Az alábbiakban röviden összeszedem, hogy az Oracle Database milyen eroforrás szeparációs technológiákkal rendelkezik, melyek jól használhatók adatbázis konszolidáció esetén: Adatbázis szolgáltatások: Azt talán minden Oracle adatbázis-kezelovel foglalkozó szakérto tudja, hogy akliensek az adatbázist az adatbázis szolgáltatás nevével érik el. Alapértelmezetten minden adatbázis egyetlen szolgáltatással rendelkezik, mely automatikusan a 'global database name' paraméterrel megegyezo nevet kapja az adatbázis létrehozásakor. Ugyanakkor egy adatbázishoz több szolgáltatás név is rendelheto. A szolgáltatásokkal csoportosíthatók a különbözo feladatokat végrehajtó kliensek, és a szolgáltatásokhoz rendelhetjük hogy melyik kliens csoportnak mennyi rendszer eroforrást allokálunk. Klaszteres adatbázisok (RAC) esetén egy szolgáltatás több adatbázis példányhoz (szerverhez) kapcsolódhat, amivel valós terheléstol függo terhelés elosztás valósítható meg (itt már szerepet kap egyébként a Resource Manager is, lásd késobb). Az alkalmazás számára irrelevánssá válik, hogy az adott szolgáltatást mely szerver szolgálja ki. A szolgáltatásokhoz kapcsolódó eroforrások menet közben dinamikusan bovíthetok, de kezelik a kieso eroforrások hiányát is (failover). Database Resource Manager: Az Oracle Database Resource Manager az adatbázis szintjén kezeli az eroforrásokat, a CPU használatot szabályozza az adatbázis terhelés kontrolljával. A Resource Manager egy CPU-n adott pillanatban csak egyetlen Oracle processz futtatását engedélyezi, miközben a többit várakoztatja (ahogy az egy operációs rendszer ütemezojében is muködik). A Resource Manager csak akkor lép muködésbe, amikor a CPU terhelése eléri a 100%-ot. Ekkor a Resource Plan-nek megfeleloen korlátozhatja az egyes eroforrás csoportok számára elérheto eroforrás (CPU) mennyiségét. Instance Caging: A Resource Manager részeként az Oracle Database 11gR2-tol elérheto Instance Caging technológiával virtualizáció és operációs rendszer szintu eroforrás felosztás nélkül az adatbázis példány szintjén lehet szabályozni az allokált CPU számot. Erre akkor lehet szükség, ha egy szerveren több példány futtatására van szükség. A Resource Manager bekapcsolásával és a cpu_count paraméter beállításával lehet adatbázis példányonként aktiválni az Instance Caging funkcionalitást. A cpu_count egy dinamikus paraméter, célszeru arra az értékre állítani, ahány CPU-t az adott adatbázis példány maximálisan igényelhet. Lehetoség van túlméretezni a példányok számára rendelkezésre álló processzorok számát. Például egy 4 CPUs- szerver esetében ha van 3 példányunk, mindháromnak adhatunk 3 CPU-t. Azonban ha mindegyik terhelés alatt van, akkor a példány számára maximum allokált CPU szám osztva összes allokált CPU számmal arányban részesül a processzorból, ami a példában 33,33%, azaz 1,33 CPU. Input Output Resource Manager (IORM):Nem csak a processzorok használatát szabályozhatjuk, lehetoség van a megosztott storage eroforrásainak felosztására is. Az Input Output Resorce Manager (IORM) alkalmazásával storage szinten tudjuk szabályozni az adatbázisok közötti és azokon belüli minimális I/O szinteket. Database Vault: Ugyanazon adatbázisba konszolidált alkalmazások esetén a rendszergazda szerepkörök szeparálása lehetséges az Oracle Database Vault technológiával. Ezzel elérheto az, hogy biztonságosan konszolidáljuk adatbázisainkat úgy, hogy minden adminisztrátor csak a hozzá tartozó adatokat, objektumokat lássa, módosíthassa.

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• When to increase AWS RDS MySQL Server instance to larger CPU/RAM?

  - by rksprst

  I'm wondering at what stage do I need to increase the image for the RDS MySQL server to a larger CPU/RAM instance. The CPU utilization graph is near 0. The Avg Free Memory is around 150MB. The Avg Swap Usage is 420MB. Read Latency is 0-20ms/op it spikes up randomly. Avg write latency is on average 5ms/op but spikes up to 10-20ms/op. Are there some common rules here that I should follow? Thanks!

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• Guest Blog: Secure your applications based on your business model, not your application architecture, by Yaldah Hakim

  - by Darin Pendergraft

  Today’s businesses are looking for new ways to engage their customers, embrace mobile applications, while staying in compliance, improving security and driving down costs.  For many, the solution to that problem is to host their applications with a Cloud Services provider, but concerns that a hosted application will be less secure continue to cause doubt. Oracle is recognized by Gartner as a leader in the User Provisioning and Identity and Access Governance magic quadrants, and has helped thousands of companies worldwide to secure their enterprise applications and identities.  Now those same world class IDM capabilities are available as a managed service, both for enterprise applications, as well has Oracle hosted applications. --- Listen to our IDM in the cloud podcast to hear Yvonne Wilson, Director of the IDM Practice in Cloud Service, explain how Oracle Managed Services provides IDM as a service ---Selecting OracleManaged Cloud Services to deploy and manage Oracle Identity Management Services is a smart business decision for a variety of reasons. Oracle hosted Identity Management infrastructure is deployed securely, resilient to failures, and supported by Oracle experts. In addition, Oracle  Managed Cloud Services monitors customer solutions from several perspectives to ensure they continue to work smoothly over time. Customers gain the benefit of Oracle Identity Management expertise to achieve predictable and effective results for their organization.Customers can select Oracle to host and manage any number of Oracle IDM products as a service as well as other Oracle’s security products, providing a flexible, cost effective alternative to onsite hardware and software costs.Security is a major concern for all organizations- making it increasingly important to partner with a company like Oracle to ensure consistency and a layered approach to security and compliance when selecting a cloud provider.  Oracle Cloud Service makes this possible for our customers by taking away the headache and complexity of managing Identity management infrastructure and other security solutions. For more information:http://www.oracle.com/us/solutions/cloud/managed-cloud-services/overview/index.htmlTwitter-https://twitter.com/OracleCloudZoneFacebook - http://www.facebook.com/OracleCloudComputing

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• Architecture for Social Graph data that has a Time Frame Associated?

  - by Jay Stevens

  I am adding some "social" type features to an existing application. There are a limited # of node & edge types. Overall the data itself is relatively small (50,000 - 70,000 for each type of node) there will be a number of edges (relationships) between them (almost all directional). This, I know, is relatively easy to represent with an SDF store (such as BrightstarDB) or something like Microsoft's Trinity (or really many of the noSQL options). The thing that, I think, makes this a unique use case is that each relationship will have a timeframe associated with it (start and end dates). Right now, I'm thinking of just storing this in a relational structure and dealing with the headaches of "traversing the graph", but I'm looking for suggestions on a better approach (both in terms of data structure and server): Column ================ From_Node_ID Relationship To_Node_ID StartDate EndDate Any suggestions or thoughts are welcomed.

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• AWStats on Plesk consumes all of CPU and crashes server - how do you disable plesk.

  - by columbo

  Hello, I have Plesk 9.0.1 running on a Red Hat server. Every week or so at about 4:10am the server locks up. At this time the server CPU usage shhots from 4% to 90% at the same time as a mass of awstats.pl processes start (I can't see how many as my datat only shows the top 30 processes, but all of these are awstats.pl). I turned off awstats through the Plesk control panel for all but 5 domains but I still get 90% CPU usage and at least 30 instances of awstats.pl happening at 4:10am as usual. Does anyone know why this may be? Does anyone know how to disable awstats (I have stats covered using piwik)? Thanks

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• How do I install Cacti 8.7i with PIA 3.1(Plug In Architecture) for 12.04 Server LTS?

  - by Pininy

  I am planning to upgrade my current 9.04 server version to 12.04LTS server. I've successfully backup and restore my Cacti version 8.7d to 8.7i that comes with the distribution. However, the plugin patch installation for PIA 3.1 it is not working for only ubuntu. Can you assist? or it's there a way to include Cacti 8.8a which is a stable version which comes with PIA 3.1 preinstalled. regards, thomas

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• How to convert a MKV video to a less CPU intensive video format?

  - by marco.ragogna

  I have a couple of videos at 1920x800 that use the MKV format (4.7 GB). A friend of mine has an old PC that has some problems playing them; the CPU is working at nearly 100%. Is it possible to convert these videos to a less CPU intensive video format? The final size is not a problem, it can also double or more. Into which format should I convert it and which software for Windows should I use (better if free)? Thank you in advance.

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• Architecture Standards &ndash; BPMN vs. BPEL for Business Process Management

  - by pat.shepherd

  I get asked often which business process standard an organization should use; BPMN or BPEL?  As I explain to folks, they both have strengths.  Here is a great article that helps understand the benefits of both and where to use them.  The good news is that, with Oracle SOA Suite and BPM suite, you have the option and flexibility to use both in the same SCA model and runtime container.  Good stuff. Here is the great article that Mark Nelson wrote: The right tool for the right job BPEL and BPMN are both ‘languages’ or ‘notations’ for describing and executing business processes. Both are open standards. Most business process engines will support one or the other of these languages. Oracle however has chosen to support both and treat them as equals. This means that you have the freedom to choose which language to use on a process by process basis. And you can freely mix and match, even within a single composite. (A composite is the deployment unit in an SCA environment.) So why support both? Well it turns out that BPEL is really well suited to modeling some kinds of processes and BPMN is really well suited to modeling other kinds of processes. Of course there is a pretty significant overlap where either will do a great job What BPM adds to SOA Suite | RedStack

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• SQL Server 2008 CPU usage goes to 100% - troubleshooting help needed?

  - by Ali

  I have a fairly powerful database server having SQL Server 2008 R2 installed. There is only one database on it which is being accessed from 2 servers (around 5/6 applications). The problem is as soon as applications start pointing to the database, system's CPU usage goes upto 100% with sqlserver itself using 95+%. I have checked profiler, there aren't any heavy queries running there. I have checked active connections, they are hardly 150. Still CPU usage is around 100% and applications are experiencing slow response/connection to database server are getting refused. Database grus, I really need some ideas here. Thanks.

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• Organization &amp; Architecture UNISA Studies &ndash; Chap 6

  - by MarkPearl

  Learning Outcomes Discuss the physical characteristics of magnetic disks Describe how data is organized and accessed on a magnetic disk Discuss the parameters that play a role in the performance of magnetic disks Describe different optical memory devices Magnetic Disk The way data is stored on and retried from magnetic disks Data is recorded on and later retrieved form the disk via a conducting coil named the head (in many systems there are two heads) The writ mechanism exploits the fact that electricity flowing through a coil produces a magnetic field. Electric pulses are sent to the write head, and the resulting magnetic patterns are recorded on the surface below with different patterns for positive and negative currents The physical characteristics of a magnetic disk   Summarize from book   The factors that play a role in the performance of a disk Seek time – the time it takes to position the head at the track Rotational delay / latency – the time it takes for the beginning of the sector to reach the head Access time – the sum of the seek time and rotational delay Transfer time – the time it takes to transfer data RAID The rate of improvement in secondary storage performance has been considerably less than the rate for processors and main memory. Thus secondary storage has become a bit of a bottleneck. RAID works on the concept that if one disk can be pushed so far, additional gains in performance are to be had by using multiple parallel components. Points to note about RAID… RAID is a set of physical disk drives viewed by the operating system as a single logical drive Data is distributed across the physical drives of an array in a scheme known as striping Redundant disk capacity is used to store parity information, which guarantees data recoverability in case of a disk failure (not supported by RAID 0 or RAID 1) Interesting to note that the increase in the number of drives, increases the probability of failure. To compensate for this decreased reliability RAID makes use of stored parity information that enables the recovery of data lost due to a disk failure.   The RAID scheme consists of 7 levels…   Category Level Description Disks Required Data Availability Large I/O Data Transfer Capacity Small I/O Request Rate Striping 0 Non Redundant N Lower than single disk Very high Very high for both read and write Mirroring 1 Mirrored 2N Higher than RAID 2 – 5 but lower than RAID 6 Higher than single disk Up to twice that of a signle disk for read Parallel Access 2 Redundant via Hamming Code N + m Much higher than single disk Highest of all listed alternatives Approximately twice that of a single disk Parallel Access 3 Bit interleaved parity N + 1 Much higher than single disk Highest of all listed alternatives Approximately twice that of a single disk Independent Access 4 Block interleaved parity N + 1 Much higher than single disk Similar to RAID 0 for read, significantly lower than single disk for write Similar to RAID 0 for read, significantly lower than single disk for write Independent Access 5 Block interleaved parity N + 1 Much higher than single disk Similar to RAID 0 for read, lower than single disk for write Similar to RAID 0 for read, generally  lower than single disk for write Independent Access 6 Block interleaved parity N + 2 Highest of all listed alternatives Similar to RAID 0 for read; lower than RAID 5 for write Similar to RAID 0 for read, significantly lower than RAID 5  for write   Read page 215 – 221 for detailed explanation on RAID levels Optical Memory There are a variety of optical-disk systems available. Read through the table on page 222 – 223 Some of the devices include… CD CD-ROM CD-R CD-RW DVD DVD-R DVD-RW Blue-Ray DVD Magnetic Tape Most modern systems use serial recording – data is lade out as a sequence of bits along each track. The typical recording used in serial is referred to as serpentine recording. In this technique when data is being recorded, the first set of bits is recorded along the whole length of the tape. When the end of the tape is reached the heads are repostioned to record a new track, and the tape is again recorded on its whole length, this time in the opposite direction. That process continued back and forth until the tape is full. To increase speed, the read-write head is capable of reading and writing a number of adjacent tracks simultaneously. Data is still recorded serially along individual tracks, but blocks in sequence are stored on adjacent tracks as suggested. A tape drive is a sequential access device. Magnetic tape was the first kind of secondary memory. It is still widely used as the lowest-cost, slowest speed member of the memory hierarchy.

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• Why is cpu power management not working in Server 2012 with Hyper-V?

  - by Roland

  We've been using Server2008R2 with Hyper-V for a couple of years now and chose it at the time because of its ability to make use of Intel SpeedStep and AMD PowerNow! Now with Server 2012 and Hyper-V V3, all power management abilities seem to be gone. The CPUs are always at full speed and our servers need twice the energy as before while idling. (Yes, the CPU P-states are enabled in the BIOS) Is this by design? Is there a workaround to enable cpu power management again? Despite the great new features of Hyper-V 3, this would be a show-stopper for us since we are very concerned about energy consumption.

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• At which architecture level are you running BDD tests (e.g. Cucumber)

  - by Pete

  I have in the last year gotten quite fond of using SpecFlow (which is a .NET port of Cucumber) I have used it both to test a ASP.NET MVC application at the web layer, i.e. using browser automation, but also at the controller layer. The first gives me a higher confidence in the correctness of the application, because JavaScript is tested, and improper controller configuration is also caught. But those tests are slower to execute, and more complex to implement, than those just testing on the controller layer. My tests are full functional tests, i.e. they exercise all layers of the application, all the way down to the database. So the first thing before any scenario is that the database is cleared of data, allowing the test to assume that only data specified in the "Given" block exists. Then I see example on how to use it, where they test just exercise the model layer. So what are your experiences with these tools? Which layer of the application do you test?

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• How do I cross-compile my application for Ubuntu 12.04 armhf architecture on a Ubuntu 12.04 i386 host?

  - by Jonathan Cave

  I have a large application I have written. I can successfully compile the application in the following scenarios: in a native compilation for the i386 host running Ubuntu 12.04 natively on a PandaBoard running Ubuntu 12.04 (this takes a long time) using Qemu and a chroot on the host PC for the armhf PandaBoard target (this takes a very long time) I would like to cross-compile the application on the i386 host to run on a target such as the PandaBoard to complete builds in a timely fashion. So far attempts made using the arm-linux-gnueabihf tool chain in the repositories has produced binaries that do not run correctly. At this stage, I have no plans to package the software. What is the recommended way to achieve a successful cross-compile?

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• Best practice on Linux servers and CPU/power throttling?

  - by Valentin

  I am running a couple of Debian 6 (2.6.32) and 7 (3.2) Linux servers and all of them have energy saving settings enabled in their BIOS. Furthermore Linux shows that the CPUs are throttled if the servers are idling. I wonder if this could cause any harm - could there be e.g. performance impacts because Linux would not be able to handle throttling correctly? Is there a best practice for Linux servers and power/CPU throttling? Do you guys switch your energy profiles to "performance" or do you leave both the BIOS and the OS with their default settings? The reason I am asking is that I encountered several performance issues on physical Dell servers although all values (CPU/load, memory, I/O, network etc.) seemed to be normal. After changing the BIOS power settings to "performance" in those specific cases, I was able to get rid of the performance issues.

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• How to model interentity membership in entity-component architecture?

  - by croxis

  I'm falling in love with simple grace of entity-component design, although I still have issues breaking from MVC and OOP practices. Some of my game entities have membership relationships with each other (ex: a player is a member of a city, a city is a member of a nation), and I am unsure on the best way to implement it. My initial reaction is to have a a MemberOfCity component that points to the appropriate city component, but components are suppose to have no references to each other. My other option is to have a System do it, but that would require the system to persist data outside of a component. Is there a clean way to do this in an entity-component design, or am I trying to use a hammer on a screw and should use a hybrid/another approach?

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• Organization &amp; Architecture UNISA Studies &ndash; Chap 4

  - by MarkPearl

  Learning Outcomes Explain the characteristics of memory systems Describe the memory hierarchy Discuss cache memory principles Discuss issues relevant to cache design Describe the cache organization of the Pentium Computer Memory Systems There are key characteristics of memory… Location – internal or external Capacity – expressed in terms of bytes Unit of Transfer – the number of bits read out of or written into memory at a time Access Method – sequential, direct, random or associative From a users perspective the two most important characteristics of memory are… Capacity Performance – access time, memory cycle time, transfer rate The trade off for memory happens along three axis… Faster access time, greater cost per bit Greater capacity, smaller cost per bit Greater capacity, slower access time This leads to people using a tiered approach in their use of memory   As one goes down the hierarchy, the following occurs… Decreasing cost per bit Increasing capacity Increasing access time Decreasing frequency of access of the memory by the processor The use of two levels of memory to reduce average access time works in principle, but only if conditions 1 to 4 apply. A variety of technologies exist that allow us to accomplish this. Thus it is possible to organize data across the hierarchy such that the percentage of accesses to each successively lower level is substantially less than that of the level above. A portion of main memory can be used as a buffer to hold data temporarily that is to be read out to disk. This is sometimes referred to as a disk cache and improves performance in two ways… Disk writes are clustered. Instead of many small transfers of data, we have a few large transfers of data. This improves disk performance and minimizes processor involvement. Some data designed for write-out may be referenced by a program before the next dump to disk. In that case the data is retrieved rapidly from the software cache rather than slowly from disk. Cache Memory Principles Cache memory is substantially faster than main memory. A caching system works as follows.. When a processor attempts to read a word of memory, a check is made to see if this in in cache memory… If it is, the data is supplied, If it is not in the cache, a block of main memory, consisting of a fixed number of words is loaded to the cache. Because of the phenomenon of locality of references, when a block of data is fetched into the cache, it is likely that there will be future references to that same memory location or to other words in the block. Elements of Cache Design While there are a large number of cache implementations, there are a few basic design elements that serve to classify and differentiate cache architectures… Cache Addresses Cache Size Mapping Function Replacement Algorithm Write Policy Line Size Number of Caches Cache Addresses Almost all non-embedded processors support virtual memory. Virtual memory in essence allows a program to address memory from a logical point of view without needing to worry about the amount of physical memory available. When virtual addresses are used the designer may choose to place the cache between the MMU (memory management unit) and the processor or between the MMU and main memory. The disadvantage of virtual memory is that most virtual memory systems supply each application with the same virtual memory address space (each application sees virtual memory starting at memory address 0), which means the cache memory must be completely flushed with each application context switch or extra bits must be added to each line of the cache to identify which virtual address space the address refers to. Cache Size We would like the size of the cache to be small enough so that the overall average cost per bit is close to that of main memory alone and large enough so that the overall average access time is close to that of the cache alone. Also, larger caches are slightly slower than smaller ones. Mapping Function Because there are fewer cache lines than main memory blocks, an algorithm is needed for mapping main memory blocks into cache lines. The choice of mapping function dictates how the cache is organized. Three techniques can be used… Direct – simplest technique, maps each block of main memory into only one possible cache line Associative – Each main memory block to be loaded into any line of the cache Set Associative – exhibits the strengths of both the direct and associative approaches while reducing their disadvantages For detailed explanations of each approach – read the text book (page 148 – 154) Replacement Algorithm For associative and set associating mapping a replacement algorithm is needed to determine which of the existing blocks in the cache must be replaced by a new block. There are four common approaches… LRU (Least recently used) FIFO (First in first out) LFU (Least frequently used) Random selection Write Policy When a block resident in the cache is to be replaced, there are two cases to consider If no writes to that block have happened in the cache – discard it If a write has occurred, a process needs to be initiated where the changes in the cache are propagated back to the main memory. There are several approaches to achieve this including… Write Through – all writes to the cache are done to the main memory as well at the point of the change Write Back – when a block is replaced, all dirty bits are written back to main memory The problem is complicated when we have multiple caches, there are techniques to accommodate for this but I have not summarized them. Line Size When a block of data is retrieved and placed in the cache, not only the desired word but also some number of adjacent words are retrieved. As the block size increases from very small to larger sizes, the hit ratio will at first increase because of the principle of locality, which states that the data in the vicinity of a referenced word are likely to be referenced in the near future. As the block size increases, more useful data are brought into cache. The hit ratio will begin to decrease as the block becomes even bigger and the probability of using the newly fetched information becomes less than the probability of using the newly fetched information that has to be replaced. Two specific effects come into play… Larger blocks reduce the number of blocks that fit into a cache. Because each block fetch overwrites older cache contents, a small number of blocks results in data being overwritten shortly after they are fetched. As a block becomes larger, each additional word is farther from the requested word and therefore less likely to be needed in the near future. The relationship between block size and hit ratio is complex, and no set approach is judged to be the best in all circumstances.   Pentium 4 and ARM cache organizations The processor core consists of four major components: Fetch/decode unit – fetches program instruction in order from the L2 cache, decodes these into a series of micro-operations, and stores the results in the L2 instruction cache Out-of-order execution logic – Schedules execution of the micro-operations subject to data dependencies and resource availability – thus micro-operations may be scheduled for execution in a different order than they were fetched from the instruction stream. As time permits, this unit schedules speculative execution of micro-operations that may be required in the future Execution units – These units execute micro-operations, fetching the required data from the L1 data cache and temporarily storing results in registers Memory subsystem – This unit includes the L2 and L3 caches and the system bus, which is used to access main memory when the L1 and L2 caches have a cache miss and to access the system I/O resources

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• How can I debug Cisco Firewall ASA "Dispatch Unit" very high CPU utilisation from ASDM?

  - by Andy

  I have recently had my first firewall installed so I am very new to this whole situation. I am finding that Dispatch unit is becoming overloaded and it would appear to be the reason I get serious bouts of lag on my server. The firewall has had little configuration apart from me blocking all the ports in "Access Rules" and allowing only the ones the server needs and from where it needs them. I guess what I am after is assistance with locating the issues causing "Dispatch Unit" to take up all the CPU Regards --Edit-- With ASDM statistics I found that packets inbound (peak of 70-100k/sec from <1k/sec normal), traffic inbound (peak of 40-50kbits/sec from <1kbits/sec normal) and CPU all peak at the same time so I am pretty sure it is an attack of some sort but as a beginner with ASA I am not sure how to resolve

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• Firefox (on windows) constantly consuming 10% CPU - is there an add-in to find the rogue tab?

  - by tbone

  I often have many Firefox windows open, each with many tabs. Now and then one of the tabs will be running a web page that for some reason consumes lots of resources. Right now, I have a tab somewhere that is constantly consuming 10% of the CPU...which would be fine as my computer can easily handle that (see specs below...all other apps are responsive), but it seems to slow Firefox down....everything, everywhere is extremely laggy in Firefox, I can see pauses while I type this. Is there: - a way I can isolate separate instances (or even tabs) in FF into a separate process, so one rogue tab doesn't bog down FF across the entire system? - maybe an add-in that can either identify tabs consuming lots of CPU, or maybe a way to "shut down" activity on tabs you haven't used in a while? Firefox 3.6.10 Windows 7 Ultimate 64 i7 920 @ 3.6 GHz 12 GB Ram

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• windows VPS running apache and mysql, php scripts running slow.. but cpu usage is 1-3%..

  - by Roeland

  So every night I run some cron jobs. It requires probably about 20 min to process all the records. I gather the script does something like 10,000 sql queries. I figure this task was just that intense and needs time to complete, but I looked at CPU and memory usage, and it is super low. Cpu usage is between 1-3% and once in a while will bounce to 50ish for 2-3 seconds. This VPS is running windows 2003 server with Apache and MySQL. Does this sound right?

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• If most of team can't follow the architecture, what do you do?

  - by Chris

  Hi all, I'm working on a greenfields project with two other developers. We're all contractors, and myself and one other just started working on the project while the orginal one has been doing most of the basic framework coding. In the past month, my fellow programmer and I have been just frustrated by the design descisions done by our co-worker. Here's a little background information: The application at face value appeared to be your standard n-layered web application using C# on the 3.5 framework. We have a data layer, business layer and a web interface. But as we got deeper into the project we found some very interesting things that have caused us some troubles. There is a custom data access sqlHelper type base which only accepts dictionary key/valued entries and returns only data tables. There are no entity objects, but there are some massive objects which do everything and then are tossed into session for persitance. The general idea is that the pages (.aspx) don't do anything, while the controls (.ascx) do everything. The general flow is that a client clicks on a button, which goes to a user control base which passes a process request to the 'BLL' class which goes to the page processor, which then goes to a getControlProcessor, which at last actually processes the request. The request itself is made up of a dictionary which is passing a string valued method name, stored procedure name, a control name and possibly a value. All switching of the processing is done by comparing the string values of the control names and method names. Pages are linked together via a common header control that uses a combination of javascript and tables to create a hyperlink effect. And as I found out yesterday, a simple hyperlink between one page and another does not work because of the need to have quite a bit of information in session to determine which control to display on a page. My fellow programmer and I both believe that this is a strange and uncommon approach to web application development. Both of us have been in this business for over five years and neither of us have seen this approach. My question is this, how would we approach our co-worker and voice our concerns and what should we do if he does not want to accept the criteic? We both do not want to insult the work that has been done, but feel that going forward will create a nightmare for development. Thanks for your comments.

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