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  • Finegrain Performance Reporting on svchost.exe

    - by Randolpho
    This is something that's always bothered me, so I'll ask the serverfault community. I love me some Process Explorer for keeping track of more than just the high-level tasks you get in the Task Manager. But I constantly want to know which of those dozen services hosted in a single process under svchost is making my processor spike. So... is there any non-intrusive way to find this information out?

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  • FreeBSD: Samba performance over GBit-Ethernet

    - by Axel Gneiting
    I'm using a FreeBSD NAS with RAID-Z. I can read ~300MB/s from the ZFS disks to /dev/null on the box, but only get about 50MB/s over GBit-Ethernet with SMB to Windows 7 (Samba 3.5.6). Both systems have Intel-PCIe-NICs and are connected directly. Samba is configured to use AIO and I already tried to tune TCP/IP: kern.ipc.maxsockbuf=16777216 net.inet.tcp.sendspace=1048576 net.inet.tcp.recvspace=1048576 net.inet.tcp.sendbuf_max=8388608 net.inet.tcp.recvbuf_max=8388608 net.inet.tcp.delayed_ack=0 Any ideas what's causing the bottleneck? I think the link should handle 100 MB/s easily.

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  • monitoring TCP/IP performance on Solaris

    - by Andy Faibishenko
    I am trying to tune a high message traffic system running on Solaris. The architecture is a large number (600) of clients which connect via TCP to a big Solaris server and then send/receive relatively small messages (.5 to 1K payload) at high rates. The goal is to minimize the latency of each message processed. I suspect that the TCP stack of the server is getting overwhelmed by all the traffic. What are some commands/metrics that I can use to confirm this, and in case this is true, what is the best way to alleviate this bottleneck?

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  • NAS Performance issues

    - by Markus
    I bought a NAS from Conceptronic CH3MNAS and built in two Western Digital 1,5TB Green Drives. I only get a write speed of 6mb/s in LAN The configuration of the drives is as follows: - Raid 0 - EXT2 Is that a normal speed?

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  • Vista startup performance

    - by PeterMmm
    After 2 years my Vista (32-bit) machine now boots quite slowly. The event viewer tells me two programs comming up slow: explorer.exe and svchost.exe. Fine. But what can i do that these programs comes up as quickly as before ?

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  • Webserver: Performance impact when storing session files on /dev/shm

    - by GetFree
    I have a website runing on a typical setup: Linux, Apache, PHP, MySQL. However, what's not typical about it, is that it's getting tons of traffic (400,000+ visits a day) and so, efficiency is becoming more and more important to me. I'm constantly looking for things I could optimize and, right now, my attention is focused on PHP's session files. There's a hell lot of session files constantly being read and created on the /tmp directory. So my question is: Is it a good idea to store the session files in /dev/shm (tmpfs) in order to speed things up a little bit??

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  • Methodologies for performance-testing a WAN link

    - by Chopper3
    We have a pair of new diversely-routed 1Gbps Ethernet links between locations about 200 miles apart. The 'client' is a new reasonably-powerful machine (HP DL380 G6, dual E56xx Xeons, 48GB DDR3, R1 pair of 300GB 10krpm SAS disks, W2K8R2-x64) and the 'server' is a decent enough machine too (HP BL460c G6, dual E55xx Xeons, 72GB, R1 pair of 146GB 10krpm SAS disks, dual-port Emulex 4Gbps FC HBA linked to dual Cisco MDS9509s then onto dedicated HP EVA 8400 with 128 x 450GB 15krpm FC disks, RHEL 5.3-x64). Using SFTP from the client we're only seeing about 40Kbps of throughput using large (2GB) files. We've performed server to 'other local server' tests and see around 500Mbps through the local switches (Cat 6509s), we're going to do the same on the client side but that's a day or so away. What other testing methods would you use to prove to the link providers that the problem is theirs?

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  • Google bots are severely affecting site performance

    - by Lynn
    I have an aggregate site on a linux server that pulls in feeds from a universe of about 2,000 blogs. It's in Wordpress 3.4.2 and I have a cron job that is staggered to run five times an hour on another server to pull in the stories and then publish them to the front page of this site. This is so I didn't put too much pressure all on one server. However, the Google bots, which visit a few times every hour bring the server to its knees in the morning and evenings when there is an increase in traffic on the site. The bots have something like 30,000 links to follow at this point. How do I throttle the bots to simply grab the new stories off the front page and stop there? EDIT- Details of my server configuration: The way we have this set up is the server that handles all the publishing is an unmanaged instance via AWS. It mounts the NFS server and connects to the RDS to update content, etc. You get to this publishing instance via a plugin that detects the wp-admin link and then redirects you into there. The front end app server also mounts the NFS and requests data from the RDS. It is the only one that has the WP Super Cache on it.... The OS is Ubuntu on the App server and the NFS runs CentOs. The front end is Nginx and the publishing server is Apache.

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  • Solaris TCP/IP performance tuning

    - by Andy Faibishenko
    I am trying to tune a high message traffic system running on Solaris. The architecture is a large number (600) of clients which connect via TCP to a big Solaris server and then send/receive relatively small messages (.5 to 1K payload) at high rates. The goal is to minimize the latency of each message processed. I suspect that the TCP stack of the server is getting overwhelmed by all the traffic. What are some commands/metrics that I can use to confirm this, and in case this is true, what is the best way to alleviate this bottleneck? PS I posted this on StackOverflow originally. One person suggested snoop and dtrace. dtrace seems pretty general - are there any additional pointers on how to use it to diagnose TCP issues?

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  • apache and ajp performance

    - by user12145
    I have an apache sitting in front of two tomcat app servers(one on the same physical server, the other on a different one) that does time consuming work(0.5 sec to 10sec per request). The apache http server is getting killed by an average of 1 to 2 concurrent requests per second. both Server spec is about 2GB of RAM. Is there a way to optimize apache to handle the load? any advise is welcome. BalancerMember ajp://localhost:8009/xxxxxx BalancerMember ajp://XXX.XX.XXX.XX:8009/xxxxxx I keep getting the following in apache2.2 log: [Mon Dec 28 00:31:02 2009] [error] ajp_read_header: ajp_ilink_receive failed [Mon Dec 28 00:31:02 2009] [error] (120006)APR does not understand this error code: proxy: read response failed from 127.0.0.1:8009 (localhost)

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  • poor performance when deleteing many files

    - by choppy
    I've got two machines: The first is IBM Blade with 24 cores 96GB RAM and single local hard drive with 278GB divided to 4 partitions: 1. c: - 40GB; 3GB free 2. d: - 40GB; 37GB free 3. e: - 198322GB; 198.1 free 4. 100MB (EFI system Partition) Formatted with GPT The other is pizza server with 4 cores 8GB RAM and single local hard drive with 273GB divided to 3 partitions: 1. c: - 136.81; 20GB free 2. d: - 88.74GB; 87.91 free 3. e: - 47.85GB; 46.91 free Formatted with MBR I have two scripts, the first creates 20,000 files in one directory, each file size is 192KB, the second delete the folder (recursive) and prints how much time it toke to delete all files. The problem is on the first server (blade) it takes about 2 minutes to delete all 20,000 files while on the second (pizza) it takes about 4 seconds!? Both servers have clean windows server 2008R2 with no special application running on background. Any ideas what is going on?

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  • SamFS performance problem on file creation

    - by Gregor Longariva
    I have two samfs filesystems (samfs1 and samfs2), both on the same 6130, both with the same config/watermarks/timeouts etc. creating a file on samfs2 works as it should, on samfs1 not. A little simple script shows up, that every while and then the file creation needs between 11 and 28 seconds: stan 12:32 [scratch]# while ( 1 ) while? echo - while? time echo test file while? time mv file file2 while? echo + while? sleep 1 while? end 0.00u 0.00s 0:00.01 0.0% 0.00u 0.00s 0:00.00 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.03 0.0% + 0.00u 0.00s 0:23.71 0.0% 0.00u 0.00s 0:00.14 0.0% + 0.00u 0.00s 0:00.18 0.0% 0.00u 0.00s 0:00.13 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.05 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.06 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.05 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.05 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.05 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.04 0.0% + 0.00u 0.00s 0:00.04 0.0% 0.00u 0.00s 0:00.05 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.01 0.0% + 0.00u 0.00s 0:26.05 0.0% 0.00u 0.00s 0:00.50 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.06 0.0% + 0.00u 0.00s 0:00.00 0.0% 0.00u 0.00s 0:00.12 0.0% + Any idea where the problem could be?

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  • Getting More Performance out of a MacBook Pro

    - by 5arx
    So I've got a mid-2009 MacBook Pro 13". Integrated GPU so not a games machine but fast enough for doing .Net development in VMs. I love the little thing and wanted to give it a Christmas present so thought I'd mod it up a bit and give it a boost. I'm thinking of swapping out the stock 5400rpm HD with a faster hybrid drive (has 4GB RAM and spins at 7200rpm) but was wondering if any of you had tried or knew of anything else I could change/upgrade/mod to squeeze more out of my laptop. Before you answer though, please be aware that I'm not sure I can run to putting in the 8GB of RAM Apple have suggested :-( Thanks in advance.

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  • refresh windows network performance counters in command line

    - by michalv82
    I am testing a USB device connected to a windows PC. When the device is connected then windows has another network interface going through the device. I need to get the bytes transffered for that specific interface, basically I need the data shown in the networking tab in the task manager for my interface adapter. I found this question which helped to get this info: ms windows network activity bytes send and receive in command line However I have a problem when I run multiple tests - each time I disconnect and connect the device there's another line for the interface, like below. In the task manager networking tab I only see one record for my interface but I don't know how I can know from command line which is the lastest and current instance (it's not like the first line or last line is always the current interface, I noticed it's not consistent): wmic path Win32_PerfRawData_Tcpip_NetworkInterface Get Name,PacketsReceivedPerSec,PacketsSentPerSec,BytesReceivedPersec,BytesSentPersec BytesReceivedPersec BytesSentPersec Name PacketsReceivedPersec PacketsSentPersec 422666370 6317989292 Intel[R] 82579LM Gigabit Network Connection 2715169 8109643 49150 375973 My USB Device 432 568 0 0 My USB Device _2 0 0 0 0 My USB Device _3 0 0 0 0 My USB Device _6 0 0 0 0 Local Area Connection* 9 0 0

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  • monitoring TCP/IP performance on Solaris

    - by Andy Faibishenko
    I am trying to tune a high message traffic system running on Solaris. The architecture is a large number (600) of clients which connect via TCP to a big Solaris server and then send/receive relatively small messages (.5 to 1K payload) at high rates. The goal is to minimize the latency of each message processed. I suspect that the TCP stack of the server is getting overwhelmed by all the traffic. What are some commands/metrics that I can use to confirm this, and in case this is true, what is the best way to alleviate this bottleneck?

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  • SSD performance

    - by Tom
    I recently upgraded to a Kingston Hyper-X 120GB SSD, when I run Crystaldiskmark my scores look really slow, my MB (gigabyte 775) does not have an option for ACHI in the BIOS, I'm wondering if that's an issue. The scores were: Seq read -233 write-176.8 512K-224 write-175.8 4K-25 write-80 4K-23 write-102 This drive is rated for over 500, Any help or input would be greatly appreciated..

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  • Joomla performance problems on AWS

    - by Bobby Jack
    I'm running a site on AWS with the following setup: Single m1.small instance (web server) Single RDS m1.small db Joomla 1.5 Generally, the site is performant, but is fairly low-traffic - say around 50-100 visits / hour. However, at peak time, we see about double that traffic. During peak time, pretty much every day: CPU usage on the web server slowly climbs to 100% CPU usage on the RDS server climbs quite quickly to about 30%, from an average of about 15 Database connections shoot up to about 140, from a normal average of about 2 or 3 The site is then occasionally unreachable, certainly according to pingdom monitoring. Does anyone recognise this behaviour? Can you point me in the right direction to begin investigating? Of course, RDS makes it difficult to do things like slow query logging, so I've started by regularly dumping the mysql process list into a file to see if there's anything I can spot there, but it would be good to have something more concrete to investigate. UPDATE At least, can someone confirm that I'm definitely right in saying that the level of traffic implies the problem must be a specific type of query taking way longer than it should to execute? This would happen if a table gets locked, and many queries need to write to it, right? For this very reason, I've already changed the __session table type to InnoDB.

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  • Fixing predicated NSFetchedResultsController/NSFetchRequest performance with SQLite backend?

    - by Jaanus
    I have a series of NSFetchedResultsControllers powering some table views, and their performance on device was abysmal, on the order of seconds. Since it all runs on main thread, it's blocking my app at startup, which is not great. I investigated and turns out the predicate is the problem: NSPredicate *somePredicate = [NSPredicate predicateWithFormat:@"ANY somethings == %@", something]; [fetchRequest setPredicate:somePredicate]; I.e the fetch entity, call it "things", has a many-to-many relation with entity "something". This predicate is a filter that limits the results to only things that have a relation with a particular "something". When I removed the predicate for testing, fetch time (the initial performFetch: call) dropped (for some extreme cases) from 4 seconds to around 100ms or less, which is acceptable. I am troubled by this, though, as it negates a lot of the benefit I was hoping to gain with Core Data and NSFRC, which otherwise seems like a powerful tool. So, my question is, how can I optimize this performance? Am I using the predicate wrong? Should I modify the model/schema somehow? And what other ways there are to fix this? Is this kind of degraded performance to be expected? (There are on the order of hundreds of <1KB objects.) EDIT WITH DETAILS: Here's the code: [fetchRequest setFetchLimit:200]; NSLog(@"before fetch"); BOOL success = [frc performFetch:&error]; if (!success) { NSLog(@"Fetch request error: %@", error); } NSLog(@"after fetch"); Updated logs (previously, I had some application inefficiencies degrading the performance here. These are the updated logs that should be as close to optimal as you can get under my current environment): 2010-02-05 12:45:22.138 Special Ppl[429:207] before fetch 2010-02-05 12:45:22.144 Special Ppl[429:207] CoreData: sql: SELECT DISTINCT 0, t0.Z_PK, t0.Z_OPT, <model fields> FROM ZTHING t0 LEFT OUTER JOIN Z_1THINGS t1 ON t0.Z_PK = t1.Z_2THINGS WHERE t1.Z_1SOMETHINGS = ? ORDER BY t0.ZID DESC LIMIT 200 2010-02-05 12:45:22.663 Special Ppl[429:207] CoreData: annotation: sql connection fetch time: 0.5094s 2010-02-05 12:45:22.668 Special Ppl[429:207] CoreData: annotation: total fetch execution time: 0.5240s for 198 rows. 2010-02-05 12:45:22.706 Special Ppl[429:207] after fetch If I do the same fetch without predicate (by commenting out the two lines in the beginning of the question): 2010-02-05 12:44:10.398 Special Ppl[414:207] before fetch 2010-02-05 12:44:10.405 Special Ppl[414:207] CoreData: sql: SELECT 0, t0.Z_PK, t0.Z_OPT, <model fields> FROM ZTHING t0 ORDER BY t0.ZID DESC LIMIT 200 2010-02-05 12:44:10.426 Special Ppl[414:207] CoreData: annotation: sql connection fetch time: 0.0125s 2010-02-05 12:44:10.431 Special Ppl[414:207] CoreData: annotation: total fetch execution time: 0.0262s for 200 rows. 2010-02-05 12:44:10.457 Special Ppl[414:207] after fetch 20-fold difference in times. 500ms is not that great, and there does not seem to be a way to do it in background thread or otherwise optimize that I can think of. (Apart from going to a binary store where this becomes a non-issue, so I might do that. Binary store performance is consistently ~100ms for the above 200-object predicated query.) (I nested another question here previously, which I now moved away).

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  • How can a single disk in a hardware SATA RAID-10 array bring the entire array to a screeching halt?

    - by Stu Thompson
    Prelude: I'm a code-monkey that's increasingly taken on SysAdmin duties for my small company. My code is our product, and increasingly we provide the same app as SaaS. About 18 months ago I moved our servers from a premium hosting centric vendor to a barebones rack pusher in a tier IV data center. (Literally across the street.) This ment doing much more ourselves--things like networking, storage and monitoring. As part the big move, to replace our leased direct attached storage from the hosting company, I built a 9TB two-node NAS based on SuperMicro chassises, 3ware RAID cards, Ubuntu 10.04, two dozen SATA disks, DRBD and . It's all lovingly documented in three blog posts: Building up & testing a new 9TB SATA RAID10 NFSv4 NAS: Part I, Part II and Part III. We also setup a Cacit monitoring system. Recently we've been adding more and more data points, like SMART values. I could not have done all this without the awesome boffins at ServerFault. It's been a fun and educational experience. My boss is happy (we saved bucket loads of $$$), our customers are happy (storage costs are down), I'm happy (fun, fun, fun). Until yesterday. Outage & Recovery: Some time after lunch we started getting reports of sluggish performance from our application, an on-demand streaming media CMS. About the same time our Cacti monitoring system sent a blizzard of emails. One of the more telling alerts was a graph of iostat await. Performance became so degraded that Pingdom began sending "server down" notifications. The overall load was moderate, there was not traffic spike. After logging onto the application servers, NFS clients of the NAS, I confirmed that just about everything was experiencing highly intermittent and insanely long IO wait times. And once I hopped onto the primary NAS node itself, the same delays were evident when trying to navigate the problem array's file system. Time to fail over, that went well. Within 20 minuts everything was confirmed to be back up and running perfectly. Post-Mortem: After any and all system failures I perform a post-mortem to determine the cause of the failure. First thing I did was ssh back into the box and start reviewing logs. It was offline, completely. Time for a trip to the data center. Hardware reset, backup an and running. In /var/syslog I found this scary looking entry: Nov 15 06:49:44 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_00], 6 Currently unreadable (pending) sectors Nov 15 06:49:44 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_07], SMART Prefailure Attribute: 1 Raw_Read_Error_Rate changed from 171 to 170 Nov 15 06:49:45 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_10], 16 Currently unreadable (pending) sectors Nov 15 06:49:45 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_10], 4 Offline uncorrectable sectors Nov 15 06:49:45 umbilo smartd[2827]: Num Test_Description Status Remaining LifeTime(hours) LBA_of_first_error Nov 15 06:49:45 umbilo smartd[2827]: # 1 Short offline Completed: read failure 90% 6576 3421766910 Nov 15 06:49:45 umbilo smartd[2827]: # 2 Short offline Completed: read failure 90% 6087 3421766910 Nov 15 06:49:45 umbilo smartd[2827]: # 3 Short offline Completed: read failure 10% 5901 656821791 Nov 15 06:49:45 umbilo smartd[2827]: # 4 Short offline Completed: read failure 90% 5818 651637856 Nov 15 06:49:45 umbilo smartd[2827]: So I went to check the Cacti graphs for the disks in the array. Here we see that, yes, disk 7 is slipping away just like syslog says it is. But we also see that disk 8's SMART Read Erros are fluctuating. There are no messages about disk 8 in syslog. More interesting is that the fluctuating values for disk 8 directly correlate to the high IO wait times! My interpretation is that: Disk 8 is experiencing an odd hardware fault that results in intermittent long operation times. Somehow this fault condition on the disk is locking up the entire array Maybe there is a more accurate or correct description, but the net result has been that the one disk is impacting the performance of the whole array. The Question(s) How can a single disk in a hardware SATA RAID-10 array bring the entire array to a screeching halt? Am I being naïve to think that the RAID card should have dealt with this? How can I prevent a single misbehaving disk from impacting the entire array? Am I missing something?

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  • EPM Infrastructure Tuning Guide v11.1.2.2 / 11.1.2.3

    - by Ahmed Awan
    Applies To: This edition applies to only 11.1.2.2, 11.1.2.3. One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle EPM System performance, all components need to be monitored, analyzed, and tuned. This guide describe the techniques used to monitor performance and the techniques for optimizing the performance of EPM components. TOP TUNING RECOMMENDATIONS FOR EPM SYSTEM: Performance tuning Oracle Hyperion EPM system is a complex and iterative process. To get you started, we have created a list of recommendations to help you optimize your Oracle Hyperion EPM system performance. This chapter includes the following sections that provide a quick start for performance tuning Oracle EPM products. Note these performance tuning techniques are applicable to nearly all Oracle EPM products such as Financial PM Applications, Essbase, Reporting and Foundation services. 1. Tune Operating Systems parameters. 2. Tune Oracle WebLogic Server (WLS) parameters. 3. Tune 64bit Java Virtual Machines (JVM). 4. Tune 32bit Java Virtual Machines (JVM). 5. Tune HTTP Server parameters. 6. Tune HTTP Server Compression / Caching. 7. Tune Oracle Database Parameters. 8. Tune Reporting And Analysis Framework (RAF) Services. 9. Tune Oracle ADF parameters. Click to Download the EPM 11.1.2.3 Infrastructure Tuning Whitepaper (Right click or option-click the link and choose "Save As..." to download this pdf file)

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  • EPM 11.1.2 - EPM Infrastructure Tuning Guide v11.1.2.1

    - by Ahmed Awan
    Applies To: This edition applies to only 11.1.2, 11.1.2 (PS1). One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle EPM System performance, all components need to be monitored, analyzed, and tuned. This guide describe the techniques used to monitor performance and the techniques for optimizing the performance of EPM components. TOP TUNING RECOMMENDATIONS FOR EPM SYSTEM: Performance tuning Oracle Hyperion EPM system is a complex and iterative process. To get you started, we have created a list of recommendations to help you optimize your Oracle Hyperion EPM system performance. This chapter includes the following sections that provide a quick start for performance tuning Oracle EPM products. Note these performance tuning techniques are applicable to nearly all Oracle EPM products such as Financial PM Applications, Essbase, Reporting and Foundation services. 1. Tune Operating Systems parameters. 2. Tune Oracle WebLogic Server (WLS) parameters. 3. Tune 64bit Java Virtual Machines (JVM). 4. Tune 32bit Java Virtual Machines (JVM). 5. Tune HTTP Server parameters. 6. Tune HTTP Server Compression / Caching. 7. Tune Oracle Database Parameters. 8. Tune Reporting And Analysis Framework (RAF) Services. Click to Download the EPM 11.1.2.1 Infrastructure Tuning Whitepaper (Right click or option-click the link and choose "Save As..." to download this pdf file)

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  • ASP.NET Frameworks and Raw Throughput Performance

    - by Rick Strahl
    A few days ago I had a curious thought: With all these different technologies that the ASP.NET stack has to offer, what's the most efficient technology overall to return data for a server request? When I started this it was mere curiosity rather than a real practical need or result. Different tools are used for different problems and so performance differences are to be expected. But still I was curious to see how the various technologies performed relative to each just for raw throughput of the request getting to the endpoint and back out to the client with as little processing in the actual endpoint logic as possible (aka Hello World!). I want to clarify that this is merely an informal test for my own curiosity and I'm sharing the results and process here because I thought it was interesting. It's been a long while since I've done any sort of perf testing on ASP.NET, mainly because I've not had extremely heavy load requirements and because overall ASP.NET performs very well even for fairly high loads so that often it's not that critical to test load performance. This post is not meant to make a point  or even come to a conclusion which tech is better, but just to act as a reference to help understand some of the differences in perf and give a starting point to play around with this yourself. I've included the code for this simple project, so you can play with it and maybe add a few additional tests for different things if you like. Source Code on GitHub I looked at this data for these technologies: ASP.NET Web API ASP.NET MVC WebForms ASP.NET WebPages ASMX AJAX Services  (couldn't get AJAX/JSON to run on IIS8 ) WCF Rest Raw ASP.NET HttpHandlers It's quite a mixed bag, of course and the technologies target different types of development. What started out as mere curiosity turned into a bit of a head scratcher as the results were sometimes surprising. What I describe here is more to satisfy my curiosity more than anything and I thought it interesting enough to discuss on the blog :-) First test: Raw Throughput The first thing I did is test raw throughput for the various technologies. This is the least practical test of course since you're unlikely to ever create the equivalent of a 'Hello World' request in a real life application. The idea here is to measure how much time a 'NOP' request takes to return data to the client. So for this request I create the simplest Hello World request that I could come up for each tech. Http Handler The first is the lowest level approach which is an HTTP handler. public class Handler : IHttpHandler { public void ProcessRequest(HttpContext context) { context.Response.ContentType = "text/plain"; context.Response.Write("Hello World. Time is: " + DateTime.Now.ToString()); } public bool IsReusable { get { return true; } } } WebForms Next I added a couple of ASPX pages - one using CodeBehind and one using only a markup page. The CodeBehind page simple does this in CodeBehind without any markup in the ASPX page: public partial class HelloWorld_CodeBehind : System.Web.UI.Page { protected void Page_Load(object sender, EventArgs e) { Response.Write("Hello World. Time is: " + DateTime.Now.ToString() ); Response.End(); } } while the Markup page only contains some static output via an expression:<%@ Page Language="C#" AutoEventWireup="false" CodeBehind="HelloWorld_Markup.aspx.cs" Inherits="AspNetFrameworksPerformance.HelloWorld_Markup" %> Hello World. Time is <%= DateTime.Now %> ASP.NET WebPages WebPages is the freestanding Razor implementation of ASP.NET. Here's the simple HelloWorld.cshtml page:Hello World @DateTime.Now WCF REST WCF REST was the token REST implementation for ASP.NET before WebAPI and the inbetween step from ASP.NET AJAX. I'd like to forget that this technology was ever considered for production use, but I'll include it here. Here's an OperationContract class: [ServiceContract(Namespace = "")] [AspNetCompatibilityRequirements(RequirementsMode = AspNetCompatibilityRequirementsMode.Allowed)] public class WcfService { [OperationContract] [WebGet] public Stream HelloWorld() { var data = Encoding.Unicode.GetBytes("Hello World" + DateTime.Now.ToString()); var ms = new MemoryStream(data); // Add your operation implementation here return ms; } } WCF REST can return arbitrary results by returning a Stream object and a content type. The code above turns the string result into a stream and returns that back to the client. ASP.NET AJAX (ASMX Services) I also wanted to test ASP.NET AJAX services because prior to WebAPI this is probably still the most widely used AJAX technology for the ASP.NET stack today. Unfortunately I was completely unable to get this running on my Windows 8 machine. Visual Studio 2012  removed adding of ASP.NET AJAX services, and when I tried to manually add the service and configure the script handler references it simply did not work - I always got a SOAP response for GET and POST operations. No matter what I tried I always ended up getting XML results even when explicitly adding the ScriptHandler. So, I didn't test this (but the code is there - you might be able to test this on a Windows 7 box). ASP.NET MVC Next up is probably the most popular ASP.NET technology at the moment: MVC. Here's the small controller: public class MvcPerformanceController : Controller { public ActionResult Index() { return View(); } public ActionResult HelloWorldCode() { return new ContentResult() { Content = "Hello World. Time is: " + DateTime.Now.ToString() }; } } ASP.NET WebAPI Next up is WebAPI which looks kind of similar to MVC. Except here I have to use a StringContent result to return the response: public class WebApiPerformanceController : ApiController { [HttpGet] public HttpResponseMessage HelloWorldCode() { return new HttpResponseMessage() { Content = new StringContent("Hello World. Time is: " + DateTime.Now.ToString(), Encoding.UTF8, "text/plain") }; } } Testing Take a minute to think about each of the technologies… and take a guess which you think is most efficient in raw throughput. The fastest should be pretty obvious, but the others - maybe not so much. The testing I did is pretty informal since it was mainly to satisfy my curiosity - here's how I did this: I used Apache Bench (ab.exe) from a full Apache HTTP installation to run and log the test results of hitting the server. ab.exe is a small executable that lets you hit a URL repeatedly and provides counter information about the number of requests, requests per second etc. ab.exe and the batch file are located in the \LoadTests folder of the project. An ab.exe command line  looks like this: ab.exe -n100000 -c20 http://localhost/aspnetperf/api/HelloWorld which hits the specified URL 100,000 times with a load factor of 20 concurrent requests. This results in output like this:   It's a great way to get a quick and dirty performance summary. Run it a few times to make sure there's not a large amount of varience. You might also want to do an IISRESET to clear the Web Server. Just make sure you do a short test run to warm up the server first - otherwise your first run is likely to be skewed downwards. ab.exe also allows you to specify headers and provide POST data and many other things if you want to get a little more fancy. Here all tests are GET requests to keep it simple. I ran each test: 100,000 iterations Load factor of 20 concurrent connections IISReset before starting A short warm up run for API and MVC to make sure startup cost is mitigated Here is the batch file I used for the test: IISRESET REM make sure you add REM C:\Program Files (x86)\Apache Software Foundation\Apache2.2\bin REM to your path so ab.exe can be found REM Warm up ab.exe -n100 -c20 http://localhost/aspnetperf/MvcPerformance/HelloWorldJsonab.exe -n100 -c20 http://localhost/aspnetperf/api/HelloWorldJson ab.exe -n100 -c20 http://localhost/AspNetPerf/WcfService.svc/HelloWorld ab.exe -n100000 -c20 http://localhost/aspnetperf/handler.ashx > handler.txt ab.exe -n100000 -c20 http://localhost/aspnetperf/HelloWorld_CodeBehind.aspx > AspxCodeBehind.txt ab.exe -n100000 -c20 http://localhost/aspnetperf/HelloWorld_Markup.aspx > AspxMarkup.txt ab.exe -n100000 -c20 http://localhost/AspNetPerf/WcfService.svc/HelloWorld > Wcf.txt ab.exe -n100000 -c20 http://localhost/aspnetperf/MvcPerformance/HelloWorldCode > Mvc.txt ab.exe -n100000 -c20 http://localhost/aspnetperf/api/HelloWorld > WebApi.txt I ran each of these tests 3 times and took the average score for Requests/second, with the machine otherwise idle. I did see a bit of variance when running many tests but the values used here are the medians. Part of this has to do with the fact I ran the tests on my local machine - result would probably more consistent running the load test on a separate machine hitting across the network. I ran these tests locally on my laptop which is a Dell XPS with quad core Sandibridge I7-2720QM @ 2.20ghz and a fast SSD drive on Windows 8. CPU load during tests ran to about 70% max across all 4 cores (IOW, it wasn't overloading the machine). Ideally you can try running these tests on a separate machine hitting the local machine. If I remember correctly IIS 7 and 8 on client OSs don't throttle so the performance here should be Results Ok, let's cut straight to the chase. Below are the results from the tests… It's not surprising that the handler was fastest. But it was a bit surprising to me that the next fastest was WebForms and especially Web Forms with markup over a CodeBehind page. WebPages also fared fairly well. MVC and WebAPI are a little slower and the slowest by far is WCF REST (which again I find surprising). As mentioned at the start the raw throughput tests are not overly practical as they don't test scripting performance for the HTML generation engines or serialization performances of the data engines. All it really does is give you an idea of the raw throughput for the technology from time of request to reaching the endpoint and returning minimal text data back to the client which indicates full round trip performance. But it's still interesting to see that Web Forms performs better in throughput than either MVC, WebAPI or WebPages. It'd be interesting to try this with a few pages that actually have some parsing logic on it, but that's beyond the scope of this throughput test. But what's also amazing about this test is the sheer amount of traffic that a laptop computer is handling. Even the slowest tech managed 5700 requests a second, which is one hell of a lot of requests if you extrapolate that out over a 24 hour period. Remember these are not static pages, but dynamic requests that are being served. Another test - JSON Data Service Results The second test I used a JSON result from several of the technologies. I didn't bother running WebForms and WebPages through this test since that doesn't make a ton of sense to return data from the them (OTOH, returning text from the APIs didn't make a ton of sense either :-) In these tests I have a small Person class that gets serialized and then returned to the client. The Person class looks like this: public class Person { public Person() { Id = 10; Name = "Rick"; Entered = DateTime.Now; } public int Id { get; set; } public string Name { get; set; } public DateTime Entered { get; set; } } Here are the updated handler classes that use Person: Handler public class Handler : IHttpHandler { public void ProcessRequest(HttpContext context) { var action = context.Request.QueryString["action"]; if (action == "json") JsonRequest(context); else TextRequest(context); } public void TextRequest(HttpContext context) { context.Response.ContentType = "text/plain"; context.Response.Write("Hello World. Time is: " + DateTime.Now.ToString()); } public void JsonRequest(HttpContext context) { var json = JsonConvert.SerializeObject(new Person(), Formatting.None); context.Response.ContentType = "application/json"; context.Response.Write(json); } public bool IsReusable { get { return true; } } } This code adds a little logic to check for a action query string and route the request to an optional JSON result method. To generate JSON, I'm using the same JSON.NET serializer (JsonConvert.SerializeObject) used in Web API to create the JSON response. WCF REST   [ServiceContract(Namespace = "")] [AspNetCompatibilityRequirements(RequirementsMode = AspNetCompatibilityRequirementsMode.Allowed)] public class WcfService { [OperationContract] [WebGet] public Stream HelloWorld() { var data = Encoding.Unicode.GetBytes("Hello World " + DateTime.Now.ToString()); var ms = new MemoryStream(data); // Add your operation implementation here return ms; } [OperationContract] [WebGet(ResponseFormat=WebMessageFormat.Json,BodyStyle=WebMessageBodyStyle.WrappedRequest)] public Person HelloWorldJson() { // Add your operation implementation here return new Person(); } } For WCF REST all I have to do is add a method with the Person result type.   ASP.NET MVC public class MvcPerformanceController : Controller { // // GET: /MvcPerformance/ public ActionResult Index() { return View(); } public ActionResult HelloWorldCode() { return new ContentResult() { Content = "Hello World. Time is: " + DateTime.Now.ToString() }; } public JsonResult HelloWorldJson() { return Json(new Person(), JsonRequestBehavior.AllowGet); } } For MVC all I have to do for a JSON response is return a JSON result. ASP.NET internally uses JavaScriptSerializer. ASP.NET WebAPI public class WebApiPerformanceController : ApiController { [HttpGet] public HttpResponseMessage HelloWorldCode() { return new HttpResponseMessage() { Content = new StringContent("Hello World. Time is: " + DateTime.Now.ToString(), Encoding.UTF8, "text/plain") }; } [HttpGet] public Person HelloWorldJson() { return new Person(); } [HttpGet] public HttpResponseMessage HelloWorldJson2() { var response = new HttpResponseMessage(HttpStatusCode.OK); response.Content = new ObjectContent<Person>(new Person(), GlobalConfiguration.Configuration.Formatters.JsonFormatter); return response; } } Testing and Results To run these data requests I used the following ab.exe commands:REM JSON RESPONSES ab.exe -n100000 -c20 http://localhost/aspnetperf/Handler.ashx?action=json > HandlerJson.txt ab.exe -n100000 -c20 http://localhost/aspnetperf/MvcPerformance/HelloWorldJson > MvcJson.txt ab.exe -n100000 -c20 http://localhost/aspnetperf/api/HelloWorldJson > WebApiJson.txt ab.exe -n100000 -c20 http://localhost/AspNetPerf/WcfService.svc/HelloWorldJson > WcfJson.txt The results from this test run are a bit interesting in that the WebAPI test improved performance significantly over returning plain string content. Here are the results:   The performance for each technology drops a little bit except for WebAPI which is up quite a bit! From this test it appears that WebAPI is actually significantly better performing returning a JSON response, rather than a plain string response. Snag with Apache Benchmark and 'Length Failures' I ran into a little snag with Apache Benchmark, which was reporting failures for my Web API requests when serializing. As the graph shows performance improved significantly from with JSON results from 5580 to 6530 or so which is a 15% improvement (while all others slowed down by 3-8%). However, I was skeptical at first because the WebAPI test reports showed a bunch of errors on about 10% of the requests. Check out this report: Notice the Failed Request count. What the hey? Is WebAPI failing on roughly 10% of requests when sending JSON? Turns out: No it's not! But it took some sleuthing to figure out why it reports these failures. At first I thought that Web API was failing, and so to make sure I re-ran the test with Fiddler attached and runiisning the ab.exe test by using the -X switch: ab.exe -n100 -c10 -X localhost:8888 http://localhost/aspnetperf/api/HelloWorldJson which showed that indeed all requests where returning proper HTTP 200 results with full content. However ab.exe was reporting the errors. After some closer inspection it turned out that the dates varying in size altered the response length in dynamic output. For example: these two results: {"Id":10,"Name":"Rick","Entered":"2012-09-04T10:57:24.841926-10:00"} {"Id":10,"Name":"Rick","Entered":"2012-09-04T10:57:24.8519262-10:00"} are different in length for the number which results in 68 and 69 bytes respectively. The same URL produces different result lengths which is what ab.exe reports. I didn't notice at first bit the same is happening when running the ASHX handler with JSON.NET result since it uses the same serializer that varies the milliseconds. Moral: You can typically ignore Length failures in Apache Benchmark and when in doubt check the actual output with Fiddler. Note that the other failure values are accurate though. Another interesting Side Note: Perf drops over Time As I was running these tests repeatedly I was finding that performance steadily dropped from a startup peak to a 10-15% lower stable level. IOW, with Web API I'd start out with around 6500 req/sec and in subsequent runs it keeps dropping until it would stabalize somewhere around 5900 req/sec occasionally jumping lower. For these tests this is why I did the IIS RESET and warm up for individual tests. This is a little puzzling. Looking at Process Monitor while the test are running memory very quickly levels out as do handles and threads, on the first test run. Subsequent runs everything stays stable, but the performance starts going downwards. This applies to all the technologies - Handlers, Web Forms, MVC, Web API - curious to see if others test this and see similar results. Doing an IISRESET then resets everything and performance starts off at peak again… Summary As I stated at the outset, these were informal to satiate my curiosity not to prove that any technology is better or even faster than another. While there clearly are differences in performance the differences (other than WCF REST which was by far the slowest and the raw handler which was by far the highest) are relatively minor, so there is no need to feel that any one technology is a runaway standout in raw performance. Choosing a technology is about more than pure performance but also about the adequateness for the job and the easy of implementation. The strengths of each technology will make for any minor performance difference we see in these tests. However, to me it's important to get an occasional reality check and compare where new technologies are heading. Often times old stuff that's been optimized and designed for a time of less horse power can utterly blow the doors off newer tech and simple checks like this let you compare. Luckily we're seeing that much of the new stuff performs well even in V1.0 which is great. To me it was very interesting to see Web API perform relatively badly with plain string content, which originally led me to think that Web API might not be properly optimized just yet. For those that caught my Tweets late last week regarding WebAPI's slow responses was with String content which is in fact considerably slower. Luckily where it counts with serialized JSON and XML WebAPI actually performs better. But I do wonder what would make generic string content slower than serialized code? This stresses another point: Don't take a single test as the final gospel and don't extrapolate out from a single set of tests. Certainly Twitter can make you feel like a fool when you post something immediate that hasn't been fleshed out a little more <blush>. Egg on my face. As a result I ended up screwing around with this for a few hours today to compare different scenarios. Well worth the time… I hope you found this useful, if not for the results, maybe for the process of quickly testing a few requests for performance and charting out a comparison. Now onwards with more serious stuff… Resources Source Code on GitHub Apache HTTP Server Project (ab.exe is part of the binary distribution)© Rick Strahl, West Wind Technologies, 2005-2012Posted in ASP.NET  Web Api   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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