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  • Providing high availability and failover using MySQL on EC2

    - by crb
    I would like to have a highly-available MySQL system, with automatic failover, running on Amazon EC2 instances. The standard approach to solving this is problem Heartbeat + DRBD, but I've found a lot of posts suggesting DRBD doesn't work on EC2, though none saying exactly why. Obviously, a serial heartbeat or distinct network is out of the question in the virtualised environment. It would also be good to have the different servers be in different availability zones, but we're getting into a much harder problem there. What are peoples' opinion on having a high uptime solution in "the cloud"? Note: This question was asked before RDS with multi-AZ was announced, which is the nice automatic answer for today's modern IT professional. :)

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  • High Lock Wait ratio in MySQL

    - by FunkyChicken
    on my site I log every pageview (date,ip,referrer,page,etc) in a simple mysql table. This table gets very little selects (3 per minute), but a lot of inserts. (about 100 per second) Today I changed this table from an InnoDB table to a MEMORY table, this made sense to me to prevent unnecessary hard disk IO. I also prune this table once per minute, to make sure it never get's too big. -- Performance wise, things are running fine. But I noticed that while running tuning-primer, that my Current Lock Wait ratio is quite high. Current Lock Wait ratio = 1 : 561 My question: Should I worry about this Lock Wait Ratio? And is there something I can change in my my.cnf to improve things so that the lock wait ratio isn't so high?

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  • Logging hurts MySQL performance - but, why?

    - by jimbo
    I'm quite surprised that I can't see an answer to this anywhere on the site already, nor in the MySQL documentation (section 5.2 seems to have logging otherwise well covered!) If I enable binlogs, I see a small performance hit (subjectively), which is to be expected with a little extra IO -- but when I enable a general query log, I see an enormous performance hit (double the time to run queries, or worse), way in excess of what I see with binlogs. Of course I'm now logging every SELECT as well as every UPDATE/INSERT, but, other daemons record their every request (Apache, Exim) without grinding to a halt. Am I just seeing the effects of being close to a performance "tipping point" when it comes to IO, or is there something fundamentally difficult about logging queries that causes this to happen? I'd love to be able to log all queries to make development easier, but I can't justify the kind of hardware it feels like we'd need to get performance back up with general query logging on. I do, of course, log slow queries, and there's negligible improvement in general usage if I disable this. (All of this is on Ubuntu 10.04 LTS, MySQLd 5.1.49, but research suggests this is a fairly universal issue)

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  • Looking for a short term solution to improve website performance with additional server

    - by Tanim Mirza
    I am working with a small team to run an internal website running with PHP 5.3.9, MySQL 5.0.77. All the files and database are hosted on a dedicated Linux machine with the following configuration: Intel Xeon E5450 8 CPU cores @3.00GHz, 2992.498 MHz, Cache 6148 KB, Cent OS – Red Hat Enterprise Linux Server release 5.4 We started small and then the database got bigger and now the website performance degraded significantly. We often get server space overrun, mysql overloaded with too many calls, etc. We don't have much experience dealing with these issues. We recently got another server that we were thinking to use to improve performance. Since it has better configuration, some of us wanted to completely move everything to the new machine. But I am trying to find out how we can utilize both machine for optimized performance. I found options such as MySQL clustering, Load balancer, etc. I was wondering if I could get any suggestion for this situation "How to utilize two machines in short term for best performance", that would be great. By short term we are looking for something that we can deploy in a month or so. Thanks in advance for your time.

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  • Improving browser performance while using lots of tabs?

    - by Andrew
    My browsing habits cause me to open lots of windows and tabs, either related to different projects I'm working on or things I may want to read later. I use OSX and use about 5 spaces with multiple windows in each space. The problem is eventually I'll have around 200 or more tabs open (spread over 15-20 windows) that I don't want to close. Needless to say, my computer's performance starts to degrade. As I write this on my mobile, Safari on my laptop is locking up the computer. I used to use Chrome but found better performance with Safari. What I'd like to know, is there a graph of browser performance based on tab usage? I don't need a browser that keeps all tabs active. It would be great if the browser could increase performance by "putting tabs to sleep". Or if there was some sort of tool for saving a "workspace" of tabs that you could reactivate the next time you are working on that project. What sort of solution can you recommend to solve this problem?

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  • Linux Tuning for High Traffic JBoss Server with LDAP Binds

    - by Levi Stanley
    I'm configuring a high traffic Linux server (RedHat) and running into a limit I haven't been able to track down. I need to be able to handle sustained 300 requests per second throughput using Nginx and JBoss. The point of this server is to run checks on a user's account when that user signs in. Each request goes through Nginx to JBoss (specifically Torquebox with JBoss A7 with a Sinatra app) and then makes an LDAP request to bind that user and retrieve several attributes. It is during the bind that these errors occur. I'm able to reproduce this going directly to JBoss, so that rules out Nginx at least. I get a variety of error messages, though oddly JBoss stopped writing to the log file recently. It used to report errors about creating native threads. Now I just see "java.net.SocketException: Connection reset" and "org.apache.http.conn.HttpHostConnectException: Connection to http://my.awesome.server:8080 refused" as responses in jmeter. To the best of my knowledge, I have plenty of available file handles, processes, sockets, and ports, yet the issue persists. Unfortunately, I have very little experience tuning servers. I've found a couple useful documents - Ipsysctl tutorial 1.0.4 and Linux Tuning - but those documents are a bit over my head (and just entering the the configuration described in Linux Tuning doesn't fix my issue. Here are the configuration changes I've tried (webproxy is the user that runs Nginx and JBoss): /etc/security/limits.conf webproxy soft nofile 65536 webproxy hard nofile 65536 webproxy soft nproc 65536 webproxy hard nproc 65536 root soft nofile 65536 root hard nofile 65536 root soft nproc 65536 root hard nofile 65536 First attempt /etc/sysctl.conf sysctl net.core.somaxconn = 8192 sysctl net.ipv4.ip_local_port_range = 32768 65535 sysctl net.ipv4.tcp_fin_timeout = 15 sysctl net.ipv4.tcp_keepalive_time = 1800 sysctl net.ipv4.tcp_keepalive_intvl = 35 sysctl net.ipv4.tcp_tw_recycle = 1 sysctl net.ipv4.tcp_tw_reuse = 1 Second attempt /etc/sysctl.conf net.core.rmem_max = 16777216 net.core.wmem_max = 16777216 net.ipv4.tcp_rmem = 4096 87380 16777216 net.ipv4.tcp_wmem = 4096 65536 16777216 net.core.netdev_max_backlog = 30000 net.ipv4.tcp_congestion_control=htcp net.ipv4.tcp_mtu_probing=1 Any ideas what might be happening here? Or better yet, are there some good documentation resources designed for beginners?

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  • Large, high performance object or key/value store for HTTP serving on Linux

    - by Tommy
    I have a service that serves images to end users at a very high rate using plain HTTP. The images vary between 4 and 64kbytes, and there are 1.300.000.000 of them in total. The dataset is about 30TiB in size and changes (new objects, updates, deletes) make out less than 1% of the requests. The number of requests pr. second vary from 240 to 9000 and is dispersed pretty much all over, with few objects being especially "hot". As of now, these images are files on a ext3 filesystem distributed read only across a large amount of mid range servers. This poses several problems: Using a fileysystem is very inefficient since the metadata size is large, the inode/dentry cache is volatile on linux and some daemons tend to stat()/readdir() it's way through the directory structure, which in my case becomes very expensive. Updating the dataset is very time consuming and requires remounting between set A and B. The only reasonable handling is operating on the block device for backup, copying, etc. What I would like is a deamon that: speaks HTTP (get, put, delete and perhaps update) stores data it in an efficient structure. The index should remain in memory, and considering the amount of objects, the overhead must be small. The software should be able to handle massive connections with slow (if any) time needed to ramp up. Index should be read in memory at startup. Statistics would be nice, but not mandatory. I have experimented a bit with riak, redis, mongodb, kyoto and varnish with persistent storage, but I haven't had the chance to dig in really deep yet.

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  • Load and Web Performance Testing using Visual Studio Ultimate 2010-Part 3

    - by Tarun Arora
    Welcome back once again, in Part 1 of Load and Web Performance Testing using Visual Studio 2010 I talked about why Performance Testing the application is important, the test tools available in Visual Studio Ultimate 2010 and various test rig topologies, in Part 2 of Load and Web Performance Testing using Visual Studio 2010 I discussed the details of web performance & load tests as well as why it’s important to follow a goal based pattern while performance testing your application. In part 3 I’ll be discussing Test Result Analysis, Test Result Drill through, Test Report Generation, Test Run Comparison, Asp.net Profiler and some closing thoughts. Test Results – I see some creepy worms! In Part 2 we put together a web performance test and a load test, lets run the test to see load test to see how the Web site responds to the load simulation. While the load test is running you will be able to see close to real time analysis in the Load Test Analyser window. You can use the Load Test Analyser to conduct load test analysis in three ways: Monitor a running load test - A condensed set of the performance counter data is maintained in memory. To prevent the results memory requirements from growing unbounded, up to 200 samples for each performance counter are maintained. This includes 100 evenly spaced samples that span the current elapsed time of the run and the most recent 100 samples.         After the load test run is completed - The test controller spools all collected performance counter data to a database while the test is running. Additional data, such as timing details and error details, is loaded into the database when the test completes. The performance data for a completed test is loaded from the database and analysed by the Load Test Analyser. Below you can see a screen shot of the summary view, this provides key results in a format that is compact and easy to read. You can also print the load test summary, this is generated after the test has completed or been stopped.         Analyse the load test results of a previously run load test – We’ll see this in the section where i discuss comparison between two test runs. The performance counters can be plotted on the graphs. You also have the option to highlight a selected part of the test and view details, drill down to the user activity chart where you can hover over to see more details of the test run.   Generate Report => Test Run Comparisons The level of reports you can generate using the Load Test Analyser is astonishing. You have the option to create excel reports and conduct side by side analysis of two test results or to track trend analysis. The tools also allows you to export the graph data either to MS Excel or to a CSV file. You can view the ASP.NET profiler report to conduct further analysis as well. View Data and Diagnostic Attachments opens the Choose Diagnostic Data Adapter Attachment dialog box to select an adapter to analyse the result type. For example, you can select an IntelliTrace adapter, click OK and open the IntelliTrace summary for the test agent that was used in the load test.   Compare results This creates a set of reports that compares the data from two load test results using tables and bar charts. I have taken these screen shots from the MSDN documentation, I would highly recommend exploring the wealth of knowledge available on MSDN. Leaving Thoughts While load testing the application with an excessive load for a longer duration of time, i managed to bring the IIS to its knees by piling up a huge queue of requests waiting to be processed. This clearly means that the IIS had run out of threads as all the threads were busy processing existing request, one easy way of fixing this is by increasing the default number of allocated threads, but this might escalate the problem. The better suggestion is to try and drill down to the actual root cause of the problem. When ever the garbage collection runs it stops processing any pages so all requests that come in during that period are queued up, but realistically the garbage collection completes in fraction of a a second. To understand this better lets look at the .net heap, it is divided into large heap and small heap, anything greater than 85kB in size will be allocated to the Large object heap, the Large object heap is non compacting and remember large objects are expensive to move around, so if you are allocating something in the large object heap, make sure that you really need it! The small object heap on the other hand is divided into generations, so all objects that are supposed to be short-lived are suppose to live in Gen-0 and the long living objects eventually move to Gen-2 as garbage collection goes through.  As you can see in the picture below all < 85 KB size objects are first assigned to Gen-0, when Gen-0 fills up and a new object comes in and finds Gen-0 full, the garbage collection process is started, the process checks for all the dead objects and assigns them as the valid candidate for deletion to free up memory and promotes all the remaining objects in Gen-0 to Gen-1. So in the future when ever you clean up Gen-1 you have to clean up Gen-0 as well. When you fill up Gen – 0 again, all of Gen – 1 dead objects are drenched and rest are moved to Gen-2 and Gen-0 objects are moved to Gen-1 to free up Gen-0, but by this time your Garbage collection process has started to take much more time than it usually takes. Now as I mentioned earlier when garbage collection is being run all page requests that come in during that period are queued up. Does this explain why possibly page requests are getting queued up, apart from this it could also be the case that you are waiting for a long running database process to complete.      Lets explore the heap a bit more… What is really a case of crisis is when the objects are living long enough to make it to Gen-2 and then dying, this is definitely a high cost operation. But sometimes you need objects in memory, for example when you cache data you hold on to the objects because you need to use them right across the user session, which is acceptable. But if you wanted to see what extreme caching can do to your server then write a simple application that chucks in a lot of data in cache, run a load test over it for about 10-15 minutes, forcing a lot of data in memory causing the heap to run out of memory. If you get to such a state where you start running out of memory the IIS as a mode of recovery restarts the worker process. It is great way to free up all your memory in the heap but this would clear the cache. The problem with this is if the customer had 10 items in their shopping basket and that data was stored in the application cache, the user basket will now be empty forcing them either to get frustrated and go to a competitor website or if the customer is really patient, give it another try! How can you address this, well two ways of addressing this; 1. Workaround – A x86 bit processor only allows a maximum of 4GB of RAM, this means the machine effectively has around 3.4 GB of RAM available, the OS needs about 1.5 GB of RAM to run efficiently, the IIS and .net framework also need their share of memory, leaving you a heap of around 800 MB to play with. Because Team builds by default build your application in ‘Compile as any mode’ it means the application is build such that it will run in x86 bit mode if run on a x86 bit processor and run in a x64 bit mode if run on a x64 but processor. The problem with this is not all applications are really x64 bit compatible specially if you are using com objects or external libraries. So, as a quick win if you compiled your application in x86 bit mode by changing the compile as any selection to compile as x86 in the team build, you will be able to run your application on a x64 bit machine in x86 bit mode (WOW – By running Windows on Windows) and what that means is, you could use 8GB+ worth of RAM, if you take away everything else your application will roughly get a heap size of at least 4 GB to play with, which is immense. If you need a heap size of more than 4 GB you have either build a software for NASA or there is something fundamentally wrong in your application. 2. Solution – Now that you have put a workaround in place the IIS will not restart the worker process that regularly, which means you can take a breather and start working to get to the root cause of this memory leak. But this begs a question “How do I Identify possible memory leaks in my application?” Well i won’t say that there is one single tool that can tell you where the memory leak is, but trust me, ‘Performance Profiling’ is a great start point, it definitely gets you started in the right direction, let’s have a look at how. Performance Wizard - Start the Performance Wizard and select Instrumentation, this lets you measure function call counts and timings. Before running the performance session right click the performance session settings and chose properties from the context menu to bring up the Performance session properties page and as shown in the screen shot below, check the check boxes in the group ‘.NET memory profiling collection’ namely ‘Collect .NET object allocation information’ and ‘Also collect the .NET Object lifetime information’.    Now if you fire off the profiling session on your pages you will notice that the results allows you to view ‘Object Lifetime’ which shows you the number of objects that made it to Gen-0, Gen-1, Gen-2, Large heap, etc. Another great feature about the profile is that if your application has > 5% cases where objects die right after making to the Gen-2 storage a threshold alert is generated to alert you. Since you have the option to also view the most expensive methods and by capturing the IntelliTrace data you can drill in to narrow down to the line of code that is the root cause of the problem. Well now that we have seen how crucial memory management is and how easy Visual Studio Ultimate 2010 makes it for us to identify and reproduce the problem with the best of breed tools in the product. Caching One of the main ways to improve performance is Caching. Which basically means you tell the web server that instead of going to the database for each request you keep the data in the webserver and when the user asks for it you serve it from the webserver itself. BUT that can have consequences! Let’s look at some code, trust me caching code is not very intuitive, I define a cache key for almost all searches made through the common search page and cache the results. The approach works fine, first time i get the data from the database and second time data is served from the cache, significant performance improvement, EXCEPT when two users try to do the same operation and run into each other. But it is easy to handle this by adding the lock as you can see in the snippet below. So, as long as a user comes in and finds that the cache is empty, the user locks and starts to get the cache no more concurrency issues. But lets say you are processing 10 requests per second, by the time i have locked the operation to get the results from the database, 9 other users came in and found that the cache key is null so after i have come out and populated the cache they will still go in to get the results again. The application will still be faster because the next set of 10 users and so on would continue to get data from the cache. BUT if we added another null check after locking to build the cache and before actual call to the db then the 9 users who follow me would not make the extra trip to the database at all and that would really increase the performance, but didn’t i say that the code won’t be very intuitive, may be you should leave a comment you don’t want another developer to come in and think what a fresher why is he checking for the cache key null twice !!! The downside of caching is, you are storing the data outside of the database and the data could be wrong because the updates applied to the database would make the data cached at the web server out of sync. So, how do you invalidate the cache? Well if you only had one way of updating the data lets say only one entry point to the data update you can write some logic to say that every time new data is entered set the cache object to null. But this approach will not work as soon as you have several ways of feeding data to the system or your system is scaled out across a farm of web servers. The perfect solution to this is Micro Caching which means you cache the query for a set time duration and invalidate the cache after that set duration. The advantage is every time the user queries for that data with in the time span for which you have cached the results there are no calls made to the database and the data is served right from the server which makes the response immensely quick. Now figuring out the appropriate time span for which you micro cache the query results really depends on the application. Lets say your website gets 10 requests per second, if you retain the cache results for even 1 minute you will have immense performance gains. You would reduce 90% hits to the database for searching. Ever wondered why when you go to e-bookers.com or xpedia.com or yatra.com to book a flight and you click on the book button because the fare seems too exciting and you get an error message telling you that the fare is not valid any more. Yes, exactly => That is a cache failure! These travel sites or price compare engines are not going to hit the database every time you hit the compare button instead the results will be served from the cache, because the query results are micro cached, its a perfect trade-off, by micro caching the results the site gains 100% performance benefits but every once in a while annoys a customer because the fare has expired. But the trade off works in the favour of these sites as they are still able to process up to 30+ page requests per second which means cater to the site traffic by may be losing 1 customer every once in a while to a competitor who is also using a similar caching technique what are the odds that the user will not come back to their site sooner or later? Recap   Resources Below are some Key resource you might like to review. I would highly recommend the documentation, walkthroughs and videos available on MSDN. You can always make use of Fiddler to debug Web Performance Tests. Some community test extensions and plug ins available on Codeplex might also be of interest to you. The Road Ahead Thank you for taking the time out and reading this blog post, you may also want to read Part I and Part II if you haven’t so far. If you enjoyed the post, remember to subscribe to http://feeds.feedburner.com/TarunArora. Questions/Feedback/Suggestions, etc please leave a comment. Next ‘Load Testing in the cloud’, I’ll be working on exploring the possibilities of running Test controller/Agents in the Cloud. See you on the other side! Thank You!   Share this post : CodeProject

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  • Effects of HTTP/TCP connection handshakes and server performance

    - by Blankman
    When running apache bench on the same server as the website like: ab -n 1000 -c 10 localhost:8080/ I am most probably not getting accurate results when compared to users hitting the server from various locations. I'm trying to understand how or rather why this will effect real world performance since a user in china will have different latency issues when compared to someone in the same state/country. Say my web server has a maximum thread limit of 100. Can someone explain in detail how end user latency can/will effect server performance. I'm assuming here that each request will be computed equally at say 10ms. What I'm not understand is how external factors can effect overal server performance, specifically internet connections (location, or even device like mobile) and http/tcp handshakes etc.

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  • Query performance counters from powershell

    - by Frane Borozan
    I am trying this script to query performance counters in different localized windows server versions. http://www.powershellmagazine.com/2013/07/19/querying-performance-counters-from-powershell/ Everything works as in the article, well partially :-) I am trying to access a counter ID 3906 Terminal Services Session and works well for English windows. However for example in French and German that counter doesn't exist under that ID. I think I figured to find the exact counter under ID 1548 in french and German, but that ID in English is something completely different. Anybody seen this behavior on the performance counters?

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  • SQL Server High Availability - Mirroring with MSCS?

    - by David
    I'm looking at options for high-availability for my SQL Server-powered application. The requirements are: HA protection from storage failure. Data accessibility when one of the DB servers is undergoing software updates (e.g. planned outage for Windows Update / SQL Server service-packs). Must not involve much in the way of hardware procurement. The application is an ASP.NET web application. The web application's users have their own database instances. I've seen two main options: SQL Server failover clustering, and SQL Server mirroring. I understand that SQL Server Failover Clustering requires the purchasing of a shared disk array and doesn't offer any protection if the shared storage goes down (so the documentation recommends to set up a Mirroring between two clusters). Database Mirroring seems the cheaper option (as it only requires two database servers and a simple witness box) - but I've heard it doesn't work well when you have a large number of databases. The application I'm developing involves giving each client their own database for their application - there could be hundreds of databases. Setting up the mirroring is no problem thanks to the automation systems we have in place. My final point concerns how failover works with respect to client connections - SQL Server Failover Clustering uses MSCS which means that the cluster is invisible to clients - a connection attempt might fail during the failover, but a simple reconnect will have it working again. However mirroring, as far as I know, requires that the client be aware of the mirrored partners: if the client cannot connect to the primary server then it tries the secondary server. I'm wondering how this work with respect to Connection Pooling in ASP.NET applications - does the client connection failovering mean that there's a potential 2-second (assuming 2000ms TCP timeout policy) pause when the connection pool tries the primary server on every connection attempt? I read somewhere that Mirroring can be used on top of MSCS which means that the client does not need to be aware of mirroring (so there wouldn't be any potential delays during connection, and also that no changes would need to be made to the client, not even the connection string) - however I'm finding it hard to get documentation or white papers on this approach. But if true, then it means the best method is then Mirroring (for HA) with MSCS (for client ignorance and connection performance). ...but how does this scale to a server instance that might contain hundreds of mirrored databases?

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  • RAID Array performance on an HP Proliant ML350 G5 Smart Array E200i

    - by Nate Pinchot
    We have a client who is complaining about performance of an application which utilizes an MS SQL database. They do not believe the performance issues are the fault of the application itself. The Smart Array E200i RAID controller has 128MB cache and we have the cache set to 75% read/25% write. The disk array set to enable write caching. Recently we ran a disk performance test using SQLIO based on this guide. We used a 10 GB file for the test found that the average sequential read rate was ~60 MB/sec (megabytes/sec) and the average random read rate was ~30 MB/sec. Are these numbers on par for what the server should be performing? Better than on par? Horrible? Amazing?

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  • How does NTFS compression affect performance?

    - by DragonLord
    I've heard that NTFS compression can reduce performance due to extra CPU usage, but I've read reports that it may actually increase performance because of reduced disk reads. How exactly does NTFS compression affect system performance? Notes: I'm running a laptop with a 5400 RPM hard drive, and many of the things I do on it are I/O bound. The processor is a AMD Phenom II with four cores running at 2.0 GHz. The system is defragmented regularly using UltraDefrag. The workload is mixed read-write, with reads occurring somewhat more often than writes. The files to be compressed include personal documents and selected programs, including several (less demanding) games and Visual Studio (which tends to be I/O bound more often than not).

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  • Enable: Asp.net connection pool monitoring with performance monitor

    - by BlackHawkDesign
    If this question is at the wrong forum, be free to tell me. I'm a c# developer, but I'm running in a system management issue here. Intro: Im suspecting that an asp.net application is having some issues with the connection pool and that the pool is flooding from time to time. So to make sure, I want to monitor the connection pool. After some searching I found this article : http://blog.idera.com/sql-server/performance-and-monitoring/ensure-proper-sql-server-connection-pooling-2/ Basicly it explains stuff about connection pools and how you can monitor the application pool with performance monitor. The problem: So I logged in to the asp.net server(The sql database is hosted on a different server) which hosts the website. Started performance monitor. But when I want to select 'Current # pooled and nonpooled connections', I have no instance to select. There fore I can't add it. Question How can I create/supply an instance so I can monitor the connection pool? Thanks in advance BHD

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  • Amazon EC2 performance vs desktop

    - by flashnik
    I'm wondering how to compare performance of EC2 instances with standard dedicated servers and desktop. I've found only comparance of defferent clouds. I need to find a solution to perform some computations which require CPU and memory (disc IO is not used). The choice is to use: EC2 (High-CPU) or Xeon 5620/5630 with DDR3 or Core i7-960/980 with DDR3 Can anybody help, how to compare their performance? I'm not speaking about reliability of alternatives, I want to understand pros and cons from the point of just performance.

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  • Server Performance

    - by Burt
    We have a dedicated server that we use to stage websites (our test server). The performance of the server has become really bad and we regularly have to restart it. When performance is poor I have checked task manager for the processes and memory but everything looks OK. We use a content management system and it is always when using the admin section of this CMS that we notice the performance degrade which makes me think it may have something to do with DB calls the CMS is making. Does this sound viable? Any other sggestions of how I can go about testing this? Thanks in advance...

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  • SQL Server Performance & Latching

    - by Colin
    I have a SQL server 2000 instance which runs several concurrent select statements on a group of 4 or 5 tables. Often the performance of the server during these queries becomes extremely diminished. The querys can take up to 10x as long as other runs of the same query, and it gets to the point where simple operations like getting the table list in object explorer or running sp_who can take several minutes. I've done my best to identify the cause of these issues, and the only performance metric which I've found to be off base is Average Latch Wait time. I've read that over 1 second wait time is bad, and mine ranges anywhere from 20 to 75 seconds under heavy use. So my question is, what could be the issue? Shouldn't SQL be able to handle multiple selects on a single table without losing so much performance? Can anyone suggest somewhere to go from here to investigate this problem? Thanks for the help.

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  • Flushing disk cache for performance benchmarks?

    - by Ido Hadanny
    I'm doing some performance benchmark on some heavy SQL script running on postgres 8.4 on a ubuntu box (natty). I'm experiencing some pretty un-stable performance, even though I'm supposed to be the only one running on the machine (the same script on the exact same data might run in 20m and then 40m for no specific reason). So, remembering my distant DBA training, I decided I should flush the postgres cache, using sudo /etc/init.d/postgresql restart, but it's still shaky! My question: maybe I'm missing some caches in my disk/os? I'm using a netapp appliance as my storage. Am I on the right track? Do I even want to make sure I get repeatable performance before I start tuning?

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  • Recommended website performance monitoring services? [closed]

    - by Dennis G.
    I'm looking for a good performance monitoring service for websites. I know about some of the available general monitoring services that check for uptime and notify you about unavailable services. But I'm specifically looking for a service with an emphasis on performance. I.e., I would like to see reports with detailed performance statistics from multiple locations world-wide, with a break-down on how long it took to fetch the different website resources, including third-party scripts such as Google Analytics and so on (the report should contain similar details such as the FireBug Net tab). Are there any such services and if so, which one is the best?

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

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

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  • About High Availability

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

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  • IIS High use & Server Performance issues

    - by HaydnWVN
    Have an SBS2011 running Exchange, a database app and a few other things serving 5 users (3 low use, 1 high). The server was never specced for the database app so it isn't as powerful as I'd like... Only 12GB RAM. We have increasingly found performance problems with this server, last week it was so bad I couldn't even connect remotely. To free up some available RAM I have (over the past month or so): Restricted the Exchange Message Store to 1GB with (so far) no ill effects. Restricted SQL Databases (including SBSMonitoring and Sharepoint/##SSEE (Which isn't used)). Now I am finding that IIS Worker threads are using up the available memory and I have (so far) been unable to track down much useful information about restricting them. This server is not 'serving' anything web-based apart from OWA that I am finding people using because Outlook is so slow (again related to the Servers performance). I am aware that Exchange on SBS2011 is designed to use up available resources (and concede when other applications request). But it is not doing so (or anywhere near fast enough) for our needs. Opening the database application (using Postgres) takes 5+ minutes from client machines and regularly times out or crashes due to this. After a reboot (before SQL/Exchange/IIS databases are very large/totally cached) we get the performace we need and expect. Previously a reboot once a month was enough... Then once a week... Now they have taken to rebooting it almost daily!

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  • High disk I/O - jbd2/sda2-8 process

    - by Evan Hamlet
    I have run a file server on a CentOS 5.8 final server. My only concern at the moment is what appears to be intermittent but continuous high disk I/O activity causing a general slowdown because of jbd2/sda2-8 process. jbd2/sda2-8 is making use of /dev/sda2, which is the 2nd partition of the first harddrive (IE: root partition). More info: using "iotop" the culprit appears to be "jbd2/sda1-8" making writes every second, which appears to be a kernel process associated with journaling on the ext4 filesystem, if my googling around is correct. I see "jbd2/sda2-8" appearing here every now and then, but certainly not every 3 seconds.. when idle, it appears about 1 or 2 times per minute. When I'm using the system, it appears more frequently. ATOP results: http://grabilla.com/02b14-8022db2e-4eb9-4f10-8e10-d65c49ad7530.png IOTOP results: http://grabilla.com/02b14-cf74b25d-4063-4447-9210-7d1b9b70e25b.png HTOP results: grabilla. com/02b14-ad8cad0e-89b0-46d3-849d-4fd515c1e690.png jbd2/sda2-8 is the processes I see with iotop making writes on disk even though it's not in use at all. Does someone has any idea how could I solve the high disk usage caused jbd2/sda2-8 process?

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  • High Load mysql on Debian server

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

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  • Revisiting ANTS Performance Profiler 7.4

    - by James Michael Hare
    Last year, I did a small review on the ANTS Performance Profiler 6.3, now that it’s a year later and a major version number higher, I thought I’d revisit the review and revise my last post. This post will take the same examples as the original post and update them to show what’s new in version 7.4 of the profiler. Background A performance profiler’s main job is to keep track of how much time is typically spent in each unit of code. This helps when we have a program that is not running at the performance we expect, and we want to know where the program is experiencing issues. There are many profilers out there of varying capabilities. Red Gate’s typically seem to be the very easy to “jump in” and get started with very little training required. So let’s dig into the Performance Profiler. I’ve constructed a very crude program with some obvious inefficiencies. It’s a simple program that generates random order numbers (or really could be any unique identifier), adds it to a list, sorts the list, then finds the max and min number in the list. Ignore the fact it’s very contrived and obviously inefficient, we just want to use it as an example to show off the tool: 1: // our test program 2: public static class Program 3: { 4: // the number of iterations to perform 5: private static int _iterations = 1000000; 6: 7: // The main method that controls it all 8: public static void Main() 9: { 10: var list = new List<string>(); 11: 12: for (int i = 0; i < _iterations; i++) 13: { 14: var x = GetNextId(); 15: 16: AddToList(list, x); 17: 18: var highLow = GetHighLow(list); 19: 20: if ((i % 1000) == 0) 21: { 22: Console.WriteLine("{0} - High: {1}, Low: {2}", i, highLow.Item1, highLow.Item2); 23: Console.Out.Flush(); 24: } 25: } 26: } 27: 28: // gets the next order id to process (random for us) 29: public static string GetNextId() 30: { 31: var random = new Random(); 32: var num = random.Next(1000000, 9999999); 33: return num.ToString(); 34: } 35: 36: // add it to our list - very inefficiently! 37: public static void AddToList(List<string> list, string item) 38: { 39: list.Add(item); 40: list.Sort(); 41: } 42: 43: // get high and low of order id range - very inefficiently! 44: public static Tuple<int,int> GetHighLow(List<string> list) 45: { 46: return Tuple.Create(list.Max(s => Convert.ToInt32(s)), list.Min(s => Convert.ToInt32(s))); 47: } 48: } So let’s run it through the profiler and see what happens! Visual Studio Integration First, let’s look at how the ANTS profilers integrate with Visual Studio’s menu system. Once you install the ANTS profilers, you will get an ANTS menu item with several options: Notice that you can either Profile Performance or Launch ANTS Performance Profiler. These sound similar but achieve two slightly different actions: Profile Performance: this immediately launches the profiler with all defaults selected to profile the active project in Visual Studio. Launch ANTS Performance Profiler: this launches the profiler much the same way as starting it from the Start Menu. The profiler will pre-populate the application and path information, but allow you to change the settings before beginning the profile run. So really, the main difference is that Profile Performance immediately begins profiling with the default selections, where Launch ANTS Performance Profiler allows you to change the defaults and attach to an already-running application. Let’s Fire it Up! So when you fire up ANTS either via Start Menu or Launch ANTS Performance Profiler menu in Visual Studio, you are presented with a very simple dialog to get you started: Notice you can choose from many different options for application type. You can profile executables, services, web applications, or just attach to a running process. In fact, in version 7.4 we see two new options added: ASP.NET Web Application (IIS Express) SharePoint web application (IIS) So this gives us an additional way to profile ASP.NET applications and the ability to profile SharePoint applications as well. You can also choose your level of detail in the Profiling Mode drop down. If you choose Line-Level and method-level timings detail, you will get a lot more detail on the method durations, but this will also slow down profiling somewhat. If you really need the profiler to be as unintrusive as possible, you can change it to Sample method-level timings. This is performing very light profiling, where basically the profiler collects timings of a method by examining the call-stack at given intervals. Which method you choose depends a lot on how much detail you need to find the issue and how sensitive your program issues are to timing. So for our example, let’s just go with the line and method timing detail. So, we check that all the options are correct (if you launch from VS2010, the executable and path are filled in already), and fire it up by clicking the [Start Profiling] button. Profiling the Application Once you start profiling the application, you will see a real-time graph of CPU usage that will indicate how much your application is using the CPU(s) on your system. During this time, you can select segments of the graph and bookmark them, giving them mnemonic names. This can be useful if you want to compare performance in one part of the run to another part of the run. Notice that once you select a block, it will give you the call tree breakdown for that selection only, and the relative performance of those calls. Once you feel you have collected enough information, you can click [Stop Profiling] to stop the application run and information collection and begin a more thorough analysis. Analyzing Method Timings So now that we’ve halted the run, we can look around the GUI and see what we can see. By default, the times are shown in terms of percentage of time of the total run of the application, though you can change it in the View menu item to milliseconds, ticks, or seconds as well. This won’t affect the percentages of methods, it only affects what units the times are shown. Notice also that the major hotspot seems to be in a method without source, ANTS Profiler will filter these out by default, but you can right-click on the line and remove the filter to see more detail. This proves especially handy when a bottleneck is due to a method in the BCL. So now that we’ve removed the filter, we see a bit more detail: In addition, ANTS Performance Profiler gives you the ability to decompile the methods without source so that you can dive even deeper, though typically this isn’t necessary for our purposes. When looking at timings, there are generally two types of timings for each method call: Time: This is the time spent ONLY in this method, not including calls this method makes to other methods. Time With Children: This is the total of time spent in both this method AND including calls this method makes to other methods. In other words, the Time tells you how much work is being done exclusively in this method, and the Time With Children tells you how much work is being done inclusively in this method and everything it calls. You can also choose to display the methods in a tree or in a grid. The tree view is the default and it shows the method calls arranged in terms of the tree representing all method calls and the parent method that called them, etc. This is useful for when you find a hot-spot method, you can see who is calling it to determine if the problem is the method itself, or if it is being called too many times. The grid method represents each method only once with its totals and is useful for quickly seeing what method is the trouble spot. In addition, you can choose to display Methods with source which are generally the methods you wrote (as opposed to native or BCL code), or Any Method which shows not only your methods, but also native calls, JIT overhead, synchronization waits, etc. So these are just two ways of viewing the same data, and you’re free to choose the organization that best suits what information you are after. Analyzing Method Source If we look at the timings above, we see that our AddToList() method (and in particular, it’s call to the List<T>.Sort() method in the BCL) is the hot-spot in this analysis. If ANTS sees a method that is consuming the most time, it will flag it as a hot-spot to help call out potential areas of concern. This doesn’t mean the other statistics aren’t meaningful, but that the hot-spot is most likely going to be your biggest bang-for-the-buck to concentrate on. So let’s select the AddToList() method, and see what it shows in the source window below: Notice the source breakout in the bottom pane when you select a method (from either tree or grid view). This shows you the timings in this method per line of code. This gives you a major indicator of where the trouble-spot in this method is. So in this case, we see that performing a Sort() on the List<T> after every Add() is killing our performance! Of course, this was a very contrived, duh moment, but you’d be surprised how many performance issues become duh moments. Note that this one line is taking up 86% of the execution time of this application! If we eliminate this bottleneck, we should see drastic improvement in the performance. So to fix this, if we still wanted to maintain the List<T> we’d have many options, including: delay Sort() until after all Add() methods, using a SortedSet, SortedList, or SortedDictionary depending on which is most appropriate, or forgoing the sorting all together and using a Dictionary. Rinse, Repeat! So let’s just change all instances of List<string> to SortedSet<string> and run this again through the profiler: Now we see the AddToList() method is no longer our hot-spot, but now the Max() and Min() calls are! This is good because we’ve eliminated one hot-spot and now we can try to correct this one as well. As before, we can then optimize this part of the code (possibly by taking advantage of the fact the list is now sorted and returning the first and last elements). We can then rinse and repeat this process until we have eliminated as many bottlenecks as possible. Calls by Web Request Another feature that was added recently is the ability to view .NET methods grouped by the HTTP requests that caused them to run. This can be helpful in determining which pages, web services, etc. are causing hot spots in your web applications. Summary If you like the other ANTS tools, you’ll like the ANTS Performance Profiler as well. It is extremely easy to use with very little product knowledge required to get up and running. There are profilers built into the higher product lines of Visual Studio, of course, which are also powerful and easy to use. But for quickly jumping in and finding hot spots rapidly, Red Gate’s Performance Profiler 7.4 is an excellent choice. Technorati Tags: Influencers,ANTS,Performance Profiler,Profiler

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