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  • Cloud storage provider lost my data. How to back up next time?

    - by tomcam
    What do you do when cloud storage fails you? First, some background. A popular cloud storage provider (rhymes with Booger Link) damaged a bunch of my data. Getting it back was an uphill battle with all the usual accusations that it was my fault, etc. Finally I got the data back. Yes, I can back this up with evidence. Idiotically, I stayed with them, so I totally get that the rest of this is on me. The problem had been with a shared folder that works with all 12 computers my business and family use with the service. We'll call that folder the Tragic Briefcase. It is a sort of global folder that's publicly visible to all computers on the service. It's our main repository. Today I decided to deal with some residual effects of the Crash of '11. Part of the damage they did was that in just one of my computers (my primary, of course) all the documents in the Tragic Briefcase were duplicated in the Windows My Documents folder. I finally started deleting them. But guess what. Though they appeared to be duplicated in the file system, removing them from My Documents on the primary PC caused them to disappear from the Tragic Briefcase too. They efficiently disappeared from all the other computers' Tragic Briefcases as well. So now, 21 gigs of files are gone, and of course I don't know which ones. I want to avoid this in the future. Apart from using a different storage provider, the bigger picture is this: how do I back up my cloud data? A complete backup every week or so from web to local storage would cause me to exceed my ISP's bandwidth. Do I need to back up each of my 12 PCs locally? I do use Backupify for my primary Google Docs, but I have been storing taxes, confidential documents, Photoshop source, video source files, and so on using the web service. So it's a lot of data, but I need to keep it safe. Backup locally would also mean 2 backup drives or some kind of RAID per PC, right, because you can't trust a single point of failure? Assuming I move to DropBox or something of its ilk, what is the best way to make sure that if the next cloud storage provider messes up I can restore?

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  • Wifi network stopped being visible (and usable) (Linksys wag320n)

    - by s427
    Basically, my wifi network simply stopped working for no apparent reason. It doesn't appear in the list of the available networks anymore. I can see all my neighbors' networks, but not mine. It's as if it doesn't exist anymore. The internet connection (non-wifi), which goes through the same modem/router, is fine though. I already had a similar problem about one year ago (see here: Wifi network SSID not visible ), just after buying this very modem. I finally got it to work after performing two factory resets and getting rid of the Cisco "Magic" software; but this time it's not working. I use a linksys router-modem (WAG320N) which is directly connected (via network cable) to my desktop computer (Windows 7). I have (mainly) two devices that use the wifi network: my phone (Samsung Galaxy Nexus) and an Asus tablet (TF201, aka Transformer Prime). I also resurrected an old laptop computer (Dell, running Windows XP) to test that, and it doesn't see anything either (apart from the 20 other wifi networks, of course ^^). This wifi network was working just fine and has been for about a year. I haven't touched the modem settings so I have no idea what's causing the problem. I tried: making my phone "forget" about my network, hoping it would see it again after that: no luck. re-entering the network informations (SSID/password) manually on my phone: still no luck (says it's not in range) exporting the modem configuration, resetting the modem (factory reset, via modem admin), restarting it, importing the configuration: nope. factory reset, turning it off for 15 minutes, restarting, re-factory reset, and entering the configuration manually: still nothing. Has anybody experienced something similar before? Have you any suggestion to fix that? Thanks in advance. PS: to clear things up, here are the settings of my modem regarding wifi: Basic wireless settings: Configuration: manual Radio Band: 2.4GHz Wireless Network Mode: B/G/N-Mixed SSID: s427 Channel Bandwidth: Wide - 40 MHz Channel Wide Channel: 9 - 2.452GHz Standard Channel: 11 - 2.462GHz SSID Broadcast: Enable Advanced Wireless Settings AP Isolation: Disable Authentication Type: Auto Basic Rate: Default Transmission Rate: Auto N Transmission Rate: Auto CTS Protection Mode: Disable Beacon Interval: 100 DTIM Interval: 1 Fragmentation Threshold: 2346 RTS Threshold: 2346

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  • Following the Thread in OSB

    - by Antony Reynolds
    Threading in OSB The Scenario I recently led an OSB POC where we needed to get high throughput from an OSB pipeline that had the following logic: 1. Receive Request 2. Send Request to External System 3. If Response has a particular value   3.1 Modify Request   3.2 Resend Request to External System 4. Send Response back to Requestor All looks very straightforward and no nasty wrinkles along the way.  The flow was implemented in OSB as follows (see diagram for more details): Proxy Service to Receive Request and Send Response Request Pipeline   Copies Original Request for use in step 3 Route Node   Sends Request to External System exposed as a Business Service Response Pipeline   Checks Response to Check If Request Needs to Be Resubmitted Modify Request Callout to External System (same Business Service as Route Node) The Proxy and the Business Service were each assigned their own Work Manager, effectively giving each of them their own thread pool. The Surprise Imagine our surprise when, on stressing the system we saw it lock up, with large numbers of blocked threads.  The reason for the lock up is due to some subtleties in the OSB thread model which is the topic of this post.   Basic Thread Model OSB goes to great lengths to avoid holding on to threads.  Lets start by looking at how how OSB deals with a simple request/response routing to a business service in a route node. Most Business Services are implemented by OSB in two parts.  The first part uses the request thread to send the request to the target.  In the diagram this is represented by the thread T1.  After sending the request to the target (the Business Service in our diagram) the request thread is released back to whatever pool it came from.  A multiplexor (muxer) is used to wait for the response.  When the response is received the muxer hands off the response to a new thread that is used to execute the response pipeline, this is represented in the diagram by T2. OSB allows you to assign different Work Managers and hence different thread pools to each Proxy Service and Business Service.  In out example we have the “Proxy Service Work Manager” assigned to the Proxy Service and the “Business Service Work Manager” assigned to the Business Service.  Note that the Business Service Work Manager is only used to assign the thread to process the response, it is never used to process the request. This architecture means that while waiting for a response from a business service there are no threads in use, which makes for better scalability in terms of thread usage. First Wrinkle Note that if the Proxy and the Business Service both use the same Work Manager then there is potential for starvation.  For example: Request Pipeline makes a blocking callout, say to perform a database read. Business Service response tries to allocate a thread from thread pool but all threads are blocked in the database read. New requests arrive and contend with responses arriving for the available threads. Similar problems can occur if the response pipeline blocks for some reason, maybe a database update for example. Solution The solution to this is to make sure that the Proxy and Business Service use different Work Managers so that they do not contend with each other for threads. Do Nothing Route Thread Model So what happens if there is no route node?  In this case OSB just echoes the Request message as a Response message, but what happens to the threads?  OSB still uses a separate thread for the response, but in this case the Work Manager used is the Default Work Manager. So this is really a special case of the Basic Thread Model discussed above, except that the response pipeline will always execute on the Default Work Manager.   Proxy Chaining Thread Model So what happens when the route node is actually calling a Proxy Service rather than a Business Service, does the second Proxy Service use its own Thread or does it re-use the thread of the original Request Pipeline? Well as you can see from the diagram when a route node calls another proxy service then the original Work Manager is used for both request pipelines.  Similarly the response pipeline uses the Work Manager associated with the ultimate Business Service invoked via a Route Node.  This actually fits in with the earlier description I gave about Business Services and by extension Route Nodes they “… uses the request thread to send the request to the target”. Call Out Threading Model So what happens when you make a Service Callout to a Business Service from within a pipeline.  The documentation says that “The pipeline processor will block the thread until the response arrives asynchronously” when using a Service Callout.  What this means is that the target Business Service is called using the pipeline thread but the response is also handled by the pipeline thread.  This implies that the pipeline thread blocks waiting for a response.  It is the handling of this response that behaves in an unexpected way. When a Business Service is called via a Service Callout, the calling thread is suspended after sending the request, but unlike the Route Node case the thread is not released, it waits for the response.  The muxer uses the Business Service Work Manager to allocate a thread to process the response, but in this case processing the response means getting the response and notifying the blocked pipeline thread that the response is available.  The original pipeline thread can then continue to process the response. Second Wrinkle This leads to an unfortunate wrinkle.  If the Business Service is using the same Work Manager as the Pipeline then it is possible for starvation or a deadlock to occur.  The scenario is as follows: Pipeline makes a Callout and the thread is suspended but still allocated Multiple Pipeline instances using the same Work Manager are in this state (common for a system under load) Response comes back but all Work Manager threads are allocated to blocked pipelines. Response cannot be processed and so pipeline threads never unblock – deadlock! Solution The solution to this is to make sure that any Business Services used by a Callout in a pipeline use a different Work Manager to the pipeline itself. The Solution to My Problem Looking back at my original workflow we see that the same Business Service is called twice, once in a Routing Node and once in a Response Pipeline Callout.  This was what was causing my problem because the response pipeline was using the Business Service Work Manager, but the Service Callout wanted to use the same Work Manager to handle the responses and so eventually my Response Pipeline hogged all the available threads so no responses could be processed. The solution was to create a second Business Service pointing to the same location as the original Business Service, the only difference was to assign a different Work Manager to this Business Service.  This ensured that when the Service Callout completed there were always threads available to process the response because the response processing from the Service Callout had its own dedicated Work Manager. Summary Request Pipeline Executes on Proxy Work Manager (WM) Thread so limited by setting of that WM.  If no WM specified then uses WLS default WM. Route Node Request sent using Proxy WM Thread Proxy WM Thread is released before getting response Muxer is used to handle response Muxer hands off response to Business Service (BS) WM Response Pipeline Executes on Routed Business Service WM Thread so limited by setting of that WM.  If no WM specified then uses WLS default WM. No Route Node (Echo functionality) Proxy WM thread released New thread from the default WM used for response pipeline Service Callout Request sent using proxy pipeline thread Proxy thread is suspended (not released) until the response comes back Notification of response handled by BS WM thread so limited by setting of that WM.  If no WM specified then uses WLS default WM. Note this is a very short lived use of the thread After notification by callout BS WM thread that thread is released and execution continues on the original pipeline thread. Route/Callout to Proxy Service Request Pipeline of callee executes on requestor thread Response Pipeline of caller executes on response thread of requested proxy Throttling Request message may be queued if limit reached. Requesting thread is released (route node) or suspended (callout) So what this means is that you may get deadlocks caused by thread starvation if you use the same thread pool for the business service in a route node and the business service in a callout from the response pipeline because the callout will need a notification thread from the same thread pool as the response pipeline.  This was the problem we were having. You get a similar problem if you use the same work manager for the proxy request pipeline and a business service callout from that request pipeline. It also means you may want to have different work managers for the proxy and business service in the route node. Basically you need to think carefully about how threading impacts your proxy services. References Thanks to Jay Kasi, Gerald Nunn and Deb Ayers for helping to explain this to me.  Any errors are my own and not theirs.  Also thanks to my colleagues Milind Pandit and Prasad Bopardikar who travelled this road with me. OSB Thread Model Great Blog Post on Thread Usage in OSB

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  • Meet the New Windows Azure

    - by ScottGu
    Today we are releasing a major set of improvements to Windows Azure.  Below is a short-summary of just a few of them: New Admin Portal and Command Line Tools Today’s release comes with a new Windows Azure portal that will enable you to manage all features and services offered on Windows Azure in a seamless, integrated way.  It is very fast and fluid, supports filtering and sorting (making it much easier to use for large deployments), works on all browsers, and offers a lot of great new features – including built-in VM, Web site, Storage, and Cloud Service monitoring support. The new portal is built on top of a REST-based management API within Windows Azure – and everything you can do through the portal can also be programmed directly against this Web API. We are also today releasing command-line tools (which like the portal call the REST Management APIs) to make it even easier to script and automate your administration tasks.  We are offering both a Powershell (for Windows) and Bash (for Mac and Linux) set of tools to download.  Like our SDKs, the code for these tools is hosted on GitHub under an Apache 2 license. Virtual Machines Windows Azure now supports the ability to deploy and run durable VMs in the cloud.  You can easily create these VMs using a new Image Gallery built-into the new Windows Azure Portal, or alternatively upload and run your own custom-built VHD images. Virtual Machines are durable (meaning anything you install within them persists across reboots) and you can use any OS with them.  Our built-in image gallery includes both Windows Server images (including the new Windows Server 2012 RC) as well as Linux images (including Ubuntu, CentOS, and SUSE distributions).  Once you create a VM instance you can easily Terminal Server or SSH into it in order to configure and customize the VM however you want (and optionally capture your own image snapshot of it to use when creating new VM instances).  This provides you with the flexibility to run pretty much any workload within Windows Azure.   The new Windows Azure Portal provides a rich set of management features for Virtual Machines – including the ability to monitor and track resource utilization within them.  Our new Virtual Machine support also enables the ability to easily attach multiple data-disks to VMs (which you can then mount and format as drives).  You can optionally enable geo-replication support on these – which will cause Windows Azure to continuously replicate your storage to a secondary data-center at least 400 miles away from your primary data-center as a backup. We use the same VHD format that is supported with Windows virtualization today (and which we’ve released as an open spec), which enables you to easily migrate existing workloads you might already have virtualized into Windows Azure.  We also make it easy to download VHDs from Windows Azure, which also provides the flexibility to easily migrate cloud-based VM workloads to an on-premise environment.  All you need to do is download the VHD file and boot it up locally, no import/export steps required. Web Sites Windows Azure now supports the ability to quickly and easily deploy ASP.NET, Node.js and PHP web-sites to a highly scalable cloud environment that allows you to start small (and for free) and then scale up as your traffic grows.  You can create a new web site in Azure and have it ready to deploy to in under 10 seconds: The new Windows Azure Portal provides built-in administration support for Web sites – including the ability to monitor and track resource utilization in real-time: You can deploy to web-sites in seconds using FTP, Git, TFS and Web Deploy.  We are also releasing tooling updates today for both Visual Studio and Web Matrix that enable developers to seamlessly deploy ASP.NET applications to this new offering.  The VS and Web Matrix publishing support includes the ability to deploy SQL databases as part of web site deployment – as well as the ability to incrementally update database schema with a later deployment. You can integrate web application publishing with source control by selecting the “Set up TFS publishing” or “Set up Git publishing” links on a web-site’s dashboard: Doing do will enable integration with our new TFS online service (which enables a full TFS workflow – including elastic build and testing support), or create a Git repository that you can reference as a remote and push deployments to.  Once you push a deployment using TFS or Git, the deployments tab will keep track of the deployments you make, and enable you to select an older (or newer) deployment and quickly redeploy your site to that snapshot of the code.  This provides a very powerful DevOps workflow experience.   Windows Azure now allows you to deploy up to 10 web-sites into a free, shared/multi-tenant hosting environment (where a site you deploy will be one of multiple sites running on a shared set of server resources).  This provides an easy way to get started on projects at no cost. You can then optionally upgrade your sites to run in a “reserved mode” that isolates them so that you are the only customer within a virtual machine: And you can elastically scale the amount of resources your sites use – allowing you to increase your reserved instance capacity as your traffic scales: Windows Azure automatically handles load balancing traffic across VM instances, and you get the same, super fast, deployment options (FTP, Git, TFS and Web Deploy) regardless of how many reserved instances you use. With Windows Azure you pay for compute capacity on a per-hour basis – which allows you to scale up and down your resources to match only what you need. Cloud Services and Distributed Caching Windows Azure also supports the ability to build cloud services that support rich multi-tier architectures, automated application management, and scale to extremely large deployments.  Previously we referred to this capability as “hosted services” – with this week’s release we are now referring to this capability as “cloud services”.  We are also enabling a bunch of new features with them. Distributed Cache One of the really cool new features being enabled with cloud services is a new distributed cache capability that enables you to use and setup a low-latency, in-memory distributed cache within your applications.  This cache is isolated for use just by your applications, and does not have any throttling limits. This cache can dynamically grow and shrink elastically (without you have to redeploy your app or make code changes), and supports the full richness of the AppFabric Cache Server API (including regions, high availability, notifications, local cache and more).  In addition to supporting the AppFabric Cache Server API, it also now supports the Memcached protocol – allowing you to point code written against Memcached at it (no code changes required). The new distributed cache can be setup to run in one of two ways: 1) Using a co-located approach.  In this option you allocate a percentage of memory in your existing web and worker roles to be used by the cache, and then the cache joins the memory into one large distributed cache.  Any data put into the cache by one role instance can be accessed by other role instances in your application – regardless of whether the cached data is stored on it or another role.  The big benefit with the “co-located” option is that it is free (you don’t have to pay anything to enable it) and it allows you to use what might have been otherwise unused memory within your application VMs. 2) Alternatively, you can add “cache worker roles” to your cloud service that are used solely for caching.  These will also be joined into one large distributed cache ring that other roles within your application can access.  You can use these roles to cache 10s or 100s of GBs of data in-memory very effectively – and the cache can be elastically increased or decreased at runtime within your application: New SDKs and Tooling Support We have updated all of the Windows Azure SDKs with today’s release to include new features and capabilities.  Our SDKs are now available for multiple languages, and all of the source in them is published under an Apache 2 license and and maintained in GitHub repositories. The .NET SDK for Azure has in particular seen a bunch of great improvements with today’s release, and now includes tooling support for both VS 2010 and the VS 2012 RC. We are also now shipping Windows, Mac and Linux SDK downloads for languages that are offered on all of these systems – allowing developers to develop Windows Azure applications using any development operating system. Much, Much More The above is just a short list of some of the improvements that are shipping in either preview or final form today – there is a LOT more in today’s release.  These include new Virtual Private Networking capabilities, new Service Bus runtime and tooling support, the public preview of the new Azure Media Services, new Data Centers, significantly upgraded network and storage hardware, SQL Reporting Services, new Identity features, support within 40+ new countries and territories, and much, much more. You can learn more about Windows Azure and sign-up to try it for free at http://windowsazure.com.  You can also watch a live keynote I’m giving at 1pm June 7th (later today) where I’ll walk through all of the new features.  We will be opening up the new features I discussed above for public usage a few hours after the keynote concludes.  We are really excited to see the great applications you build with them. Hope this helps, Scott

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  • SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28

    - by pinaldave
    It is very easy to say that you replace your hardware as that is not up to the mark. In reality, it is very difficult to implement. It is really hard to convince an infrastructure team to change any hardware because they are not performing at their best. I had a nightmare related to this issue in a deal with an infrastructure team as I suggested that they replace their faulty hardware. This is because they were initially not accepting the fact that it is the fault of their hardware. But it is really easy to say “Trust me, I am correct”, while it is equally important that you put some logical reasoning along with this statement. PAGEIOLATCH_XX is such a kind of those wait stats that we would directly like to blame on the underlying subsystem. Of course, most of the time, it is correct – the underlying subsystem is usually the problem. From Book On-Line: PAGEIOLATCH_DT Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Destroy mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_EX Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Exclusive mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_KP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Keep mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_SH Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Shared mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_UP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Update mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_XX Explanation: Simply put, this particular wait type occurs when any of the tasks is waiting for data from the disk to move to the buffer cache. ReducingPAGEIOLATCH_XX wait: Just like any other wait type, this is again a very challenging and interesting subject to resolve. Here are a few things you can experiment on: Improve your IO subsystem speed (read the first paragraph of this article, if you have not read it, I repeat that it is easy to say a step like this than to actually implement or do it). This type of wait stats can also happen due to memory pressure or any other memory issues. Putting aside the issue of a faulty IO subsystem, this wait type warrants proper analysis of the memory counters. If due to any reasons, the memory is not optimal and unable to receive the IO data. This situation can create this kind of wait type. Proper placing of files is very important. We should check file system for the proper placement of files – LDF and MDF on separate drive, TempDB on separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. It is very possible that there are no proper indexes on the system and there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can significantly reduce lots of CPU, Memory and IO (considering cover index has much lesser columns than cluster table and all other it depends conditions). You can refer to the two articles’ links below previously written by me that talk about how to optimize indexes. Create Missing Indexes Drop Unused Indexes Updating statistics can help the Query Optimizer to render optimal plan, which can only be either directly or indirectly. I have seen that updating statistics with full scan (again, if your database is huge and you cannot do this – never mind!) can provide optimal information to SQL Server optimizer leading to efficient plan. Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Service Broker and CAP_CPU_PERCENT – Limiting SQL Server Instances to CPU Usage

    - by pinaldave
    I have mentioned several times on this blog that the best part of blogging is the questions I receive from readers. They are often very interesting. The questions from readers give me a good idea what other readers might be thinking as well. After reading my earlier article Simple Example to Configure Resource Governor – Introduction to Resource Governor – I received an email from a reader and we exchanged a few emails. After exchanging emails we both figured out what is going on. It was indeed interesting and reader suggested to that I should blog about it.  I asked for permission to publish his name but he does not like the attention so we will just call him Jeff. I have converted our emails into chat for easy consumption. Jeff: Your script does not work at all. I think either there is a bug in SQL Server. Pinal: Would you please explain in detail? Jeff: Your code does not limit the CPU usage? Pinal: How did you measure it? Jeff: Well, we have third party tools for it but let us say I have limited the resources for Reporting Services and used your script described in your blog. After that I ran only reporting service workload the CPU is still used more than 100% and it is not limited to 30% as described in your script. Clearly something is wrong somewhere. Pinal: Did you say you ONLY ran reporting server load? Jeff: Yeah, to validate I ran ONLY reporting server load and CPU did not throttle at 30% as per your script. Pinal: Oh! I get it here is the answer - CAP_CPU_PERCENT = 30. Use it. Jeff: What is that, I think your earlier script says it will throttle the Reporting Service workload and Application/OLTP workload and balance it. Pinal: Exactly, that is correct. Jeff: You need to write more in email buddy! Just like your blogs, your answers do not make sense! No Offense! Pinal: Hmm…feedback well taken. Let me try again. In SQL Server 2012 there are a few enhancements with regards to SQL Server Resource Governor. One of the enhancement is how the resources are allocated. Let me explain you with examples. Configuration: [Read Earlier Post] Reporting Workload: MIN_CPU_PERCENT=0, MAX_CPU_PERCENT=30 Application/OLTP Workload: MIN_CPU_PERCENT=50, MAX_CPU_PERCENT=100 Example 1: If there is only Reporting Workload on the server: SQL Server will not limit usage of CPU to only 30% workload but SQL Server instance will use all available CPU (if needed). In another word in this scenario it will use more than 30% CPU. Example 2: If there is Reproting Workload and heavy Application/OLTP workload: SQL Server will allocate a maximum of 30% CPU resources to Reporting Workload and allocate remaining resources to heavy application/OLTP workload. The reason for this enhancement is for better utilization of the resources. Let us think, if there is only single workload, which we have limited to max CPU usage to 30%. The other unused available CPU resources is now wasted. In this situation SQL Server allows the workload to use more than 30% resources leading to overall improved/optimized performance. However, in the case of multiple workload where lots of resources are needed the limits specified in MAX_CPU_PERCENT are acknowledged. Example 3: If there is a situation where the max CPU workload has to be enforced: This is a very interesting scenario, in the case when the max CPU workload has to be enforced irrespective of the workload and enhanced algorithm, the keyword CAP_CPU_PERCENT is essential. It specifies a hard cap on the CPU bandwidth that all requests in the resource pool will receive. It will never let CPU usage for reporting workload to go over 30% in our case. You can use the key word as follows: -- Creating Resource Pool for Report Server CREATE RESOURCE POOL ReportServerPool WITH ( MIN_CPU_PERCENT=0, MAX_CPU_PERCENT=30, CAP_CPU_PERCENT=40, MIN_MEMORY_PERCENT=0, MAX_MEMORY_PERCENT=30) GO Notice that there is MAX_CPU_PERCENT=30 and CAP_CPU_PERCENT=40, what it means is that when SQL Server Instance is under heavy load under different workload it will use the maximum CPU at 30%. However, when the SQL Server instance is not under workload it will go over the 30% limit. However, as CAP_CPU_PERCENT is set to 40, it will not go over 40% in any case by limiting the usage of CPU. CAP_CPU_PERCENT puts a hard limit on the resources usage by workload. Jeff: Nice Pinal, you should blog about it. [A day passes by] Pinal: Jeff, it is done! Click here to read it. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Service Broker

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  • Passing the CAML thru the EY of the NEEDL

    - by PointsToShare
    © 2011 By: Dov Trietsch. All rights reserved Passing the CAML thru the EY of the NEEDL Definitions: CAML (Collaborative Application Markup Language) is an XML based markup language used in Microsoft SharePoint technologies  Anonymous: A camel is a horse designed by committee  Dov Trietsch: A CAML is a HORS designed by Microsoft  I was advised against putting any Camel and Sphinx rhymes in here. Look it up in Google!  _____ Now that we have dispensed with the dromedary jokes (BTW, I have many more, but they are not fit to print!), here is an interesting problem and its solution.  We have built a list where the title must be kept unique so I needed to verify the existence (or absence) of a list item with a particular title. Two methods came to mind:  1: Span the list until the title is found (result = found) or until the list ends (result = not found). This is an algorithm of complexity O(N) and for long lists it is a performance sucker. 2: Use a CAML query instead. Here, for short list we’ll encounter some overhead, but because the query results in an SQL query on the content database, it is of complexity O(LogN), which is significantly better and scales perfectly. Obviously I decided to go with the latter and this is where the CAML s--t hit the fan.   A CAML query returns a SPListItemCollection and I simply checked its Count. If it was 0, the item did not already exist and it was safe to add a new item with the given title. Otherwise I cancelled the operation and warned the user. The trouble was that I always got a positive. Most of the time a false positive. The count was greater than 0 regardles of the title I checked (except when the list was empty, which happens only once). This was very disturbing indeed. To solve my immediate problem which was speedy delivery, I reverted to the “Span the list” approach, but the problem bugged me, so I wrote a little console app by which I tested and tweaked and tested, time and again, until I found the solution. Yes, one can pass the proverbial CAML thru the ey of the needle (e’s missing on purpose).  So here are my conclusions:  CAML that does not work:  Note: QT is my quote:  char QT = Convert.ToChar((int)34); string titleQuery = "<Query>><Where><Eq>"; titleQuery += "<FieldRef Name=" + QT + "Title" + QT + "/>"; titleQuery += "<Value Type=" + QT + "Text" + QT + ">" + uniqueID + "</Value></Eq></Where></Query>"; titleQuery += "<ViewFields><FieldRef Name=" + QT + "Title" + QT + "/></ViewFields>";  Why? Even though U2U generates it, the <Query> and </Query> tags do not belong in the query that you pass. Start your query with the <Where> clause.  Also the <ViewFiels> clause does not belong. I used this clause to limit the returned collection to a single column, and I still wish to do it. I’ll show how this is done a bit later.   When you use the <Query> </Query> tags in you query, it’s as if you did not specify the query at all. What you get is the all inclusive default query for the list. It returns evey column and every item. It is expensive for both server and network because it does all the extra processing and eats plenty of bandwidth.   Now, here is the CAML that works  string titleQuery = "<Where><Eq>"; titleQuery += "<FieldRef Name=" + QT + "Title" + QT + "/>"; titleQuery += "<Value Type=" + QT + "Text" + QT + ">" + uniqueID + "</Value></Eq></Where>";  You’ll also notice that inside the unusable <ViewFields> clause above, we have a <FieldRef> clause. This is what we pass to the SPQuery object. Here is how:  SPQuery query = new SPQuery(); query.Query = titleQuery; query.ViewFields = "<FieldRef Name=" + QT + "Title" + QT + "/>"; query.RowLimit = 1; SPListItemCollection col = masterList.GetItems(query);  Two thing to note: we enter the view fields into the SPQuery object and we also limited the number of rows that the query returns. The latter is not always done, but in an existence test, there is no point in returning hundreds of rows. The query will now return one item or none, which is all we need in order to verify the existence (or non-existence) of items. Limiting the number of columns and the number of rows is a great performance enhancer. That’s all folks!!

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  • Do Not Optimize Without Measuring

    - by Alois Kraus
    Recently I had to do some performance work which included reading a lot of code. It is fascinating with what ideas people come up to solve a problem. Especially when there is no problem. When you look at other peoples code you will not be able to tell if it is well performing or not by reading it. You need to execute it with some sort of tracing or even better under a profiler. The first rule of the performance club is not to think and then to optimize but to measure, think and then optimize. The second rule is to do this do this in a loop to prevent slipping in bad things for too long into your code base. If you skip for some reason the measure step and optimize directly it is like changing the wave function in quantum mechanics. This has no observable effect in our world since it does represent only a probability distribution of all possible values. In quantum mechanics you need to let the wave function collapse to a single value. A collapsed wave function has therefore not many but one distinct value. This is what we physicists call a measurement. If you optimize your application without measuring it you are just changing the probability distribution of your potential performance values. Which performance your application actually has is still unknown. You only know that it will be within a specific range with a certain probability. As usual there are unlikely values within your distribution like a startup time of 20 minutes which should only happen once in 100 000 years. 100 000 years are a very short time when the first customer tries your heavily distributed networking application to run over a slow WIFI network… What is the point of this? Every programmer/architect has a mental performance model in his head. A model has always a set of explicit preconditions and a lot more implicit assumptions baked into it. When the model is good it will help you to think of good designs but it can also be the source of problems. In real world systems not all assumptions of your performance model (implicit or explicit) hold true any longer. The only way to connect your performance model and the real world is to measure it. In the WIFI example the model did assume a low latency high bandwidth LAN connection. If this assumption becomes wrong the system did have a drastic change in startup time. Lets look at a example. Lets assume we want to cache some expensive UI resource like fonts objects. For this undertaking we do create a Cache class with the UI themes we want to support. Since Fonts are expensive objects we do create it on demand the first time the theme is requested. A simple example of a Theme cache might look like this: using System; using System.Collections.Generic; using System.Drawing; struct Theme { public Color Color; public Font Font; } static class ThemeCache { static Dictionary<string, Theme> _Cache = new Dictionary<string, Theme> { {"Default", new Theme { Color = Color.AliceBlue }}, {"Theme12", new Theme { Color = Color.Aqua }}, }; public static Theme Get(string theme) { Theme cached = _Cache[theme]; if (cached.Font == null) { Console.WriteLine("Creating new font"); cached.Font = new Font("Arial", 8); } return cached; } } class Program { static void Main(string[] args) { Theme item = ThemeCache.Get("Theme12"); item = ThemeCache.Get("Theme12"); } } This cache does create font objects only once since on first retrieve of the Theme object the font is added to the Theme object. When we let the application run it should print “Creating new font” only once. Right? Wrong! The vigilant readers have spotted the issue already. The creator of this cache class wanted to get maximum performance. So he decided that the Theme object should be a value type (struct) to not put too much pressure on the garbage collector. The code Theme cached = _Cache[theme]; if (cached.Font == null) { Console.WriteLine("Creating new font"); cached.Font = new Font("Arial", 8); } does work with a copy of the value stored in the dictionary. This means we do mutate a copy of the Theme object and return it to our caller. But the original Theme object in the dictionary will have always null for the Font field! The solution is to change the declaration of struct Theme to class Theme or to update the theme object in the dictionary. Our cache as it is currently is actually a non caching cache. The funny thing was that I found out with a profiler by looking at which objects where finalized. I found way too many font objects to be finalized. After a bit debugging I found the allocation source for Font objects was this cache. Since this cache was there for years it means that the cache was never needed since I found no perf issue due to the creation of font objects. the cache was never profiled if it did bring any performance gain. to make the cache beneficial it needs to be accessed much more often. That was the story of the non caching cache. Next time I will write something something about measuring.

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  • 3 Ways to Make Steam Even Faster

    - by Chris Hoffman
    Have you ever noticed how slow Steam’s built-in web browser can be? Do you struggle with slow download speeds? Or is Steam just slow in general? These tips will help you speed it up. Steam isn’t a game itself, so there are no 3D settings to change to achieve maximum performance. But there are some things you can do to speed it up dramatically. Speed Up the Steam Web Browser Steam’s built-in web browser — used in both the Steam store and in Steam’s in-game overlay to provide a web browser you can quickly use within games – can be frustratingly slow on many systems. Rather than the typical speed we’ve come to expect from Chrome, Firefox, or even Internet Explorer, Steam seems to struggle. When you click a link or go to a new page, there’s a noticeable delay before the new page appears — something that doesn’t happen in desktop browsers. Many people seem to have made peace with this slowness, accepting that Steam’s built-in browser is just bad. However, there’s a trick that will eliminate this delay on many systems and make the Steam web browser fast. This problem seems to arise from an incompatibility with the Automatically Detect Proxy Settings option, which is enabled by default on Windows. This is a compatibility option that very few people should actually need, so it’s safe to disable it. To disable this option, open the Internet Options dialog — press the Windows key to access the Start menu or Start screen, type Internet Options, and click the Internet Options shortcut. Select the Connections tab in the Internet Options window and click the LAN settings button. Uncheck the Automatically detect settings option here, then click OK to save your settings. If you experienced a significant delay every time a web page loaded in Steam’s web browser, it should now be gone. In the unlikely event that you encounter some sort of problem with your network connection, you could always re-enable this option. Increase Steam’s Game Download Speed Steam attempts to automatically select the nearest download server to your location. However, it may not always select the ideal download server. Or, in the case of high-traffic events like big seasonal sales and huge game launches, you may benefit from selecting a less-congested server. To do this, open Steam’s settings by clicking the Steam menu in Steam and selecting Settings. Click over to the Downloads tab and select the closest download server from the Download Region box. You should also ensure that Steam’s download bandwidth isn’t limited from here. You may want to restart Steam and see if your download speeds improve after changing this setting. In some cases, the closest server might not be the fastest. One a bit farther away could be faster if your local server is more congested, for example. Steam once provided information about content server load, which allowed you to select a regional server that wasn’t under high-load, but this information no longer seems to be available. Steam still provides a page that shows you the amount of download activity happening in different regions, including statistics about the difference in download speeds in different US states, but this information isn’t as useful. Accelerate Steam and Your Games One way to speed up all your games — and Steam itself —  is by getting a solid-state drive and installing Steam to it. Steam allows you to easily move your Steam folder — at C:\Program Files (x86)\Steam by default — to another hard drive. Just move it like you would any other folder. You can then launch the Steam.exe program as if you had never moved Steam’s files. Steam also allows you to configure multiple game library folders. This means that you can set up a Steam library folder on a solid-state drive and one on your larger magnetic hard drive. Install your most frequently played games to the solid-state drive for maximum speed and your less frequently played ones to the slower magnetic hard drive to save SSD space. To set up additional library folders, open Steam’s Settings window and click the Downloads tab. You’ll find the Steam Library Folders option here. Click the Add Library Folder button and create a new game library on another hard drive. When you install a game in Steam, you’ll be asked which library folder you want to install it to. With the proxy compatibility option disabled, the correct download server chosen, and Steam installed to a fast SSD, it should be a speed demon. There’s not much more you can do to speed up Steam, short of upgrading other hardware like your computer’s CPU. Image Credit: Andrew Nash on Flickr     

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  • Parner Webcast - Innovations in Products Program

    - by Richard Lefebvre
    We are pleased to invite you to join the Innovations in Products –webcast. Innovations in Products will present Oracle Applications' Product's new functions and features including sales positioning. The key objectives of these webcasts are to inspire System Integrator's implementation personnel to conduct successful after sales in their Customer projects. Innovations in Products will be presented on the 1st Monday of each quarter after the billable day (4:00 to 5:00 PM CET). The webcast is intended for System Integrator's Implementation Certified Specialists but Innovations in Products is open for other interested Oracle Applications system Integrator's personnel as well. At first, two Oracle representatives will discuss Oracle's contribution to Partners. Then you will see product breakout session followed by Q&A with Oracle Experts. Each session will last for maximum 1 hour. A Q&A document covering all questions and answers will be made available after the webcast. What are the Benefits for partners? Find out how Innovations in Products helps you to improve your after sales Discover new functions and features so you can enrich your Customers's solution Learn more about Oracle Applications products, especially sales positioning Hear crucial questions raised by colleague alike, learn from their interest Engage and present your questions to subject experts Be inspired of the richness of Oracle Application portfolio – for your and your customer’s benefit Note: Should you already be familiar with a specific Product, then choose another one. Doing so you would expand your knowledge of the overall Applications portfolio. Some presentations contain product demonstration, although these presentations are not intended to be extremely detailed technical presentations. Note: At the latter part of this email you have also 17 links into the recent Applications Products presentations and 6 links into the Public Sector Value Proposition presentations that were presented in Innovations in Industries -program. Product breakout sessions: Topics Speaker To Register Fusion Applications Technology and Extensibility: A next-generation platform that adapts to client needs. Matthew Johnson, Sr. Director, SCM Product Development, EMEA CLICK HERE Fusion Applications - Transforming your Back-Office Accounting Function: Changing how people work in back office functions to drive value add Liam Nolan, Director, ERP Product Development, EMEA CLICK HERE Fusion HCM & Talent Overview & Extensibility: A more in-depth look into a personalized HCM solution Synco Jonkeren, Vice-President HCM Product Development & Management, EMEA CLICK HERE Fusion HCM Compensation Planning: Compensate To Compete Rosie Warner, Director, HCM Sales Development CLICK HERE Enterprise PLM for the Product Value Chain: Oracle Enterprise PLM offers Industry specific solutions that cover the Product Value Chain Ulf Köster, Sales Development Leader Enterprise PLM, Oracle Western Europe CLICK HERE Oracle's Asset Management and Maintenance Solution: What you need to know to successfully implement Oracle Asset Management solutions within Oracle Installed Base Philip Carey, Asset Management and Maintenance Solution Specialist CLICK HERE For more details please visit Innovations in Products and other breakout sessions on OPN page. Delivery Format Innovations in Products –program is a series of FREE prerecorded Applications product presentations followed by Q&A. It will be delivered over the Web. Participants have the opportunity to submit questions during the web cast via chat and subject matter experts will provide verbal answers live. Innovations in Products consists of several parallel prerecorded product breakout sessions, each lasting for max. 1 hour. At first, two Oracle representatives will discuss Oracle’s contribution to Partners. Then you’ll see the product breakout sessions followed by Q&A with Oracle Experts. A Q&A document covering all questions and answers will be made available after the webcast. You can also see Innovations in Products afterwards as its content will be available online for the next 6-12 months. The next Innovations in Products web casts will be presented as follows: July 2nd 2012 October 1st 2012 January 14th 2013 April 8th 2013. Note: Depending on local network bandwidth please allow some seconds time the presentations to download. You might want to refresh your screen by pressing F5. Duration Maximum 1 hour For further information please contact me Markku Rouhiainen. Recent Innovations in Products presentations Applications Products presented on April the 2nd, 2012 Speaker To Register Fusion CRM: Effective, Efficient and Easy James Penfold , Senior Director, Applications Product Development and Product Management CLICK HERE Fusion HCM: Talent management overview performance, goals, talent review Jaime Losantos Viñolas, Director, HCM Sales Development CLICK HERE Distributed Order Management - Fusion SCM Solution Vikram K Singla, Business Development Director, Supply Chain Management Applications, UK CLICK HERE Oracle Transportation Management Dominic Regan, Senior Director Oracle Transportation Management EMEA CLICK HERE Oracle Value Chain Planning: Demantra Sales & Operation Planning and Demantra Demand Management Lionel Albert, Senior Director Value Chain Planning, EMEA CLICK HERE Oracle CX (Customer Experience) - formerly CEM: Powering Great Customer Experiences Maria Ramirez , CRM Presales Consultant, EPC CLICK HERE EPM 11.1.2.2 Overview Nicholas Cox , EMEA Sales Development Director - Enterprise Performance Management CLICK HERE Oracle Hyperion Profitability and Cost Management, 11.1.2.1 Daniela Lazar , Senior EPM Sales Consultant, EPC CLICK HERE January the 16th 2012 Speaker To Register CRM / ATG: Best-in-Class CRM & Commerce Maria Ramirez , Associate CRM Presales Consultant, EPC CLICK HERE CRM / Automate Business Rules for Maximum Efficiency with OPA (Oracle Policy Automation) Marco Nilo, Associate CRM Presales Consultant, EPC CLICK HERE CRM / InQuira Toby Baker, Principal Sales Consultant, CRM Product Specialist Team CLICK HERE EPM / Business Intelligence Foundation Suite – Sales and Product Updates Liviu Nitescu, Senior BI Sales Consultant, EPC CLICK HERE EPM / Hyperion Planning 11.1.2.1 - Sales & Product Updates Andreea Voinea, EPM Sales Consultant, EPC CLICK HERE ERP / JDE EnterpriseOne Fulfillment Management Overview Mirela Andreea Nasta , ERP Presales Consultant, EPC CLICK HERE ERP / Spotlights on iExpenses Elena Nita ,ERP Presales Consultant, EPC CLICK HERE MDM / Master Data Management Martin Boyd , Senior Director Product Strategy CLICK HERE Product break through session Fusion Applications Human Capital Management Rosie Warner , Director, HCM Sales Development CLICK HERE Recent Innovations in Industries Value Proposition presentations January the 16th 2012 Speaker To Register Process Modernisation Iemke Idsingh Public Sector Solutions Director CLICK HERE Shared Services Ann Smith Business Development Director, Shared Services CLICK HERE Strengthening Financial Discipline Whilst Delivering Cashable Savings Philippa Headley UK Sales Development Director Public Sector - EPM Solutions CLICK HERE Social Welfare Industry Solutions Christian Wernberg-Tougaard Industry Director - Social Welfare CLICK HERE Police Industry Solutions Jeff Penrose Solution Sales Director CLICK HERE Tax and Revenue Management Industry Solutions Andre van der Post Global Director - Tax Solutions and Strategy CLICK HERE  

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  • Cowboy Agile?

    - by Robert May
    In a previous post, I outlined the rules of Scrum.  This post details one of those rules. I’ve often heard similar phrases around Scrum that clue me in to someone who doesn’t understand Scrum.  The phrases go something like this: “We don’t do Agile because the idea of letting people just do whatever they want is wrong.  We believe in a more structured approach.” (i.e. Work is Prison, and I’m the Warden!) “I love Agile.  Agile lets us do whatever we want!” (Cowboy Agile?) “We’re Agile, but we use a process that I’ve created.” (Cowboy Agile?) All of those phrases have one thing in common:  The assumption that Agile, and I mean Scrum, lets you do whatever you want.  This is simply not true. Executing Scrum properly requires more dedication, rigor, and diligence than happens in most traditional development methods. Scrum and Waterfall Compared Since Scrum and Waterfall are two of the most commonly used methodologies, a little bit of contrasting and comparing is in order. Waterfall Scrum A project manager defines all tasks and then manages the tasks that team members are working on. The team members define the tasks and estimates of the stories for the current iteration.  Any team member may work on any task in the iteration. Usually only a few milestones that need to be met, the milestones are measured in months, and these milestones are expected to be missed.  Little work is ever done to improve estimates and poor estimators can hide behind high estimates. Stories must be delivered every iteration, milestones are measured in hours, and the team is expected to figure out why their estimates were wrong, even when they were under.  Repeated misses can get the entire team fired. Partially completed work is normal. Partially completed work doesn’t count. Nobody knows the task you’re working on. Everyone knows what you’re working on, whether or not you’re making progress and how much longer you think its going to take, in hours. Little requirement to show working code.  Prototypes are ok. Working code must be shown each iteration.  No smoke and mirrors allowed.  Testing is done in lengthy cycles at the end of development.  Developers aren’t held accountable. Testing is part of the team.  If the testers don’t accept the story as complete, the team can’t count it.  Complete means that the story’s functionality works as designed.  The team can’t have any open defects on the story. Velocity is rarely truly measured and difficult to evaluate. Velocity is integral to the process and can be seen at a glance and everyone in the company knows what it is. A business analyst writes requirements.  Designers mock up screens.  Developers hide behind “I did it just like the spec doc told me to and made the screen exactly like the picture” Developers are expected to collaborate in real time.  If a design is bad or lacks needed details, the developers are required to get it right in the iteration, because all software must be functional.  Designers and Business Analysts are part of the team and must do their work in iterations slightly ahead of the developers. Upper Management is often surprised.  “You told me things were going well two months ago!” Management receives updates at the end of every iteration showing them exactly what the team did and how that compares to what' is remaining in the backlog.  Managers know every iteration what their money is buying. Status meetings are rare or don’t occur.  Email is a primary form of communication. Teams coordinate every single day with each other and use other high bandwidth communication channels to make sure they’re making progress.  Email is used only as a last resort.  Instead, team members stand up, walk to each other, and talk, face to face.  If that’s not possible, they pick up the phone. IF someone asks what happened, its at the end of a lengthy development cycle measured in months, and nobody really knows why it happened. Someone asks what happened every iteration.  The team talks about what happened, and then adapts to make sure that what happened either never happens again or happens every time.   That’s probably enough for now.  As you can see, a lot is required of Scrum teams! One of the key differences in Scrum is that the burden for many activities is shifted to a group of people who share responsibility, instead of a single person having responsibility.  This is a very good thing, since small groups usually come up with better and more insightful work than single individuals.  This shift also results in better velocity.  Team members can take vacations and the rest of the team simply picks up the slack.  With Waterfall, if a key team member takes a vacation, delays can ensue. Scrum requires much more out of every team member and as a result, Scrum teams outperform non-Scrum teams working 60 hour weeks. Recommended Reading Everyone considering Scrum should read Mike Cohn’s excellent book, User Stories Applied. Technorati Tags: Agile,Scrum,Waterfall

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  • How to Customize Fonts and Colors for Gnome Panels in Ubuntu Linux

    - by The Geek
    Earlier this week we showed you how to make the Gnome Panels totally transparent, but you really need some customized fonts and colors to make the effect work better. Here’s how to do it. This article is the first part of a multi-part series on how to customize the Ubuntu desktop, written by How-To Geek reader and ubergeek, Omar Hafiz. Changing the Gnome Colors the Easy Way You’ll first need to install Gnome Color Chooser which is available in the default repositories (the package name is gnome-color-chooser). Then go to System > Preferences > Gnome Color Chooser to launch the program. When you see all these tabs you immediately know that Gnome Color Chooser does not only change the font color of the panel, but also the color of the fonts all over Ubuntu, desktop icons, and many other things as well. Now switch to the panel tab, here you can control every thing about your panels. You can change font, font color, background and background color of the panels and start menus. Tick the “Normal” option and choose the color you want for the panel font. If you want you can change the hover color of the buttons on the panel by too. A little below the color option is the font options, this includes the font, font size, and the X and Y positioning of the font. The first two options are pretty straight forward, they change the typeface and the size. The X-Padding and Y-Padding may confuse you but they are interesting, they may give a nice look for your panels by increasing the space between items on your panel like this: X-Padding:   Y-Padding:   The bottom half of the window controls the look of your start menus which is the Applications, Places, and Systems menus. You can customize them just the way you did with the panel.   Alright, this was the easy way to change the font of your panels. Changing the Gnome Theme Colors the Command-Line Way The other hard (not so hard really) way will be changing the configuration files that tell your panel how it should look like. In your Home Folder, press Ctrl+H to show the hidden files, now find the file “.gtkrc-2.0”, open it and insert this line in it. If there are any other lines in the file leave them intact. include “/home/<username>/.gnome2/panel-fontrc” Don’t forget to replace the <user_name> with you user account name. When done close and save the file. Now navigate the folder “.gnome2” from your Home Folder and create a new file and name it “panel-fontrc”. Open the file you just created with a text editor and paste the following in it: style “my_color”{fg[NORMAL] = “#FF0000”}widget “*PanelWidget*” style “my_color”widget “*PanelApplet*” style “my_color” This text will make the font red. If you want other colors you’ll need to replace the Hex value/HTML Notation (in this case #FF0000) with the value of the color you want. To get the hex value you can use GIMP, Gcolor2 witch is available in the default repositories or you can right-click on your panel > Properties > Background tab then click to choose the color you want and copy the Hex value. Don’t change any other thing in the text. When done, save and close. Now press Alt+F2 and enter “killall gnome-panel” to force it to restart or you can log out and login again. Most of you will prefer the first way of changing the font and color for it’s ease of applying and because it gives you much more options but, some may not have the ability/will to download and install a new program on their machine or have reasons of their own for not to using it, that’s why we provided the two way. Latest Features How-To Geek ETC How to Enable User-Specific Wireless Networks in Windows 7 How to Use Google Chrome as Your Default PDF Reader (the Easy Way) How To Remove People and Objects From Photographs In Photoshop Ask How-To Geek: How Can I Monitor My Bandwidth Usage? Internet Explorer 9 RC Now Available: Here’s the Most Interesting New Stuff Here’s a Super Simple Trick to Defeating Fake Anti-Virus Malware The Splendiferous Array of Culinary Tools [Infographic] Add a Real-Time Earth Wallpaper App to Ubuntu with xplanetFX The Citroen GT – An Awesome Video Game Car Brought to Life [Video] Final Man vs. Machine Round of Jeopardy Unfolds; Watson Dominates Give Chromium-Based Browser Desktop Notifications a Native System Look in Ubuntu Chrome Time Track Is a Simple Task Time Tracker

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  • Planning an Event&ndash;SPS NYC

    - by MOSSLover
    I bet some of you were wondering why I am not going to any events for the most part in June and July (aside from volunteering at SPS Chicago).  Well I basically have no life for the next 2 months.  We are approaching the 11th hour of SharePoint Saturday New York City.  The event is slated to have 350 to 400 attendees.  This is second year in a row I’ve helped run it with Jason Gallicchio.  It’s amazingly crazy how much effort this event requires versus Kansas City.  It’s literally 2x the volume of attendees, speakers, and sponsors plus don’t even get me started about volunteers.  So here is a bit of the break down… We have 30 volunteers+ that Tasha Scott from the Hampton Roads Area will be managing the day of the event to do things like timing the speakers, handing out food, making sure people don’t walk into the event that did not sign up until we get a count for fire code, registering people, watching the sharpees, watching the prizes, making sure attendees get to the right place,  opening and closing the partition in the big room, moving chairs, moving furniture, etc…Then there is Jason, Greg, and I who will be making sure that the speakers, sponsors, and everything is going smoothly in the background.  We need to make sure that everything is setup properly and in the right spot.  We also need to make sure signs are printed, schedules are created, bags are stuffed with sponsor material.  Plus we need to send out emails to sponsors reminding them to send us the right information to post on the site for charity sessions, send us boxes with material to stuff bags, and we need to make sure that Michael Lotter gets there information for invoicing.  We also need to check that Michael has invoiced everyone and who has paid, because we can’t order anything for the event without money.  Once people have paid we need to setup food orders, speaker and volunteer dinners, buy prizes, buy bags, buy speakers/volunteer/organizer shirts, etc…During this process we need all the abstracts from speakers, all the bios, pictures, shirt sizes, and other items so we can create schedules and order items.  We also need to keep track of who is attending the dinner the night before for volunteers and speakers and make sure we don’t hit capacity.  Then there is attendee tracking and making sure that we don’t hit too many attendees.  We need to make sure that attendees know where to go and what to do.  We have to make all kinds of random supply lists during this process and keep on track with a variety of lists and emails plus conference calls.  All in all it’s a lot of work and I am trying to keep track of it all the top so that we don’t duplicate anything or miss anything.  So basically all in all if you don’t see me around for another month don’t worry I do exist. Right now if you look at what I’m doing I am traveling every Monday morning and Thursday night back and forth to Washington DC from New Jersey.  Every night I am working on organizational stuff for SharePoint Saturday New York City.  Every Tuesday night we are running an event conference call.  Every weekend I am either with family or my boyfriend and cat trying hard not to touch the event.  So all my time is pretty much work, event, and family/boyfriend.  I have 0 bandwidth for anything in the community.  If you compound that with my severe allergy problems in DC and a doctor’s appointment every month plus a new med once a week I’m lucky I am still standing and walking.  So basically once July 30th hits hopefully Jason Gallicchio, Greg Hurlman, and myself will be able to breathe a little easier.  If I forget to do this thank you Greg and Jason.  Thank you Tom Daly.  Thank you Michael Lotter.  Thank you Tasha Scott.  Thank you Kevin Griffin.  Thank you all the volunteers, speakers, sponsors, and attendees who will and have made this event a success.  Hopefully, we have enough time until next year to regroup, recharge, and make the event grow bigger in a different venue.  Awesome job everyone we sole out within 3 days of registration and we still have several weeks to go.  Right now the waitlist is at 49 people with room to grow.  If you attend the event thank all these guys I mentioned above for making it possible.  It’s going to be awesome I know it but I probably won’t remember half of it due to the blur of things that we will all be taking care of the day of the event.  Catch you all in the end of July/Early August where I will attempt to post something useful and clever and possibly while wearing a fez. Technorati Tags: SPS NYC,SharePoint Saturday,SharePoint Saturday New York City

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  • Infiniband: a highperformance network fabric - Part I

    - by Karoly Vegh
    Introduction:At the OpenWorld this year I managed to chat with interesting people again - one of them answering Infiniband deepdive questions with ease by coffee turned out to be one of Oracle's IB engineers, Ted Kim, who actually actively participates in the Infiniband Trade Association and integrates Oracle solutions with this highspeed network. This is why I love attending OOW. He granted me an hour of his time to talk about IB. This post is mostly based on that tech interview.Start of the actual post: Traditionally datatransfer between servers and storage elements happens in networks with up to 10 gigabit/seconds or in SANs with up to 8 gbps fiberchannel connections. Happens. Well, data rather trickles through.But nowadays data amounts grow well over the TeraByte order of magnitude, and multisocket/multicore/multithread Servers hunger data that these transfer technologies just can't deliver fast enough, causing all CPUs of this world do one thing at the same speed - waiting for data. And once again, I/O is the bottleneck in computing. FC and Ethernet can't keep up. We have half-TB SSDs, dozens of TB RAM to store data to be modified in, but can't transfer it. Can't backup fast enough, can't replicate fast enough, can't synchronize fast enough, can't load fast enough. The bad news is, everyone is used to this, like back in the '80s everyone was used to start compile jobs and go for a coffee. Or on vacation. The good news is, there's an alternative. Not so-called "bleeding-edge" 8gbps, but (as of now) 56. Not layers of overhead, but low latency. And it is available now. It has been for a while, actually. Welcome to the world of Infiniband. Short history:Infiniband was born as a result of joint efforts of HPAQ, IBM, Intel, Sun and Microsoft. They planned to implement a next-generation I/O fabric, in the 90s. In the 2000s Infiniband (from now on: IB) was quite popular in the high-performance computing field, powering most of the top500 supercomputers. Then in the middle of the decade, Oracle realized its potential and used it as an interconnect backbone for the first Database Machine, the first Exadata. Since then, IB has been booming, Oracle utilizes and supports it in a large set of its HW products, it is the backbone of the famous Engineered Systems: Exadata, SPARC SuperCluster, Exalogic, OVCA and even the new DB backup/recovery box. You can also use it to make servers talk highspeed IP to eachother, or to a ZFS Storage Appliance. Following Oracle's lead, even IBM has jumped the wagon, and leverages IB in its PureFlex systems, their first InfiniBand Machines.IB Structural Overview: If you want to use IB in your servers, the first thing you will need is PCI cards, in IB terms Host Channel Adapters, or HCAs. Just like NICs for Ethernet, or HBAs for FC. In these you plug an IB cable, going to an IB switch providing connection to other IB HCAs. Of course you're going to need drivers for those in your OS. Yes, these are long-available for Solaris and Linux. Now, what protocols can you talk over IB? There's a range of choices. See, IB isn't accepting package loss like Ethernet does, and hence doesn't need to rely on TCP/IP as a workaround for resends. That is, you still can run IP over IB (IPoIB), and that is used in various cases for control functionality, but the datatransfer can run over more efficient protocols - like native IB. About PCI connectivity: IB cards, as you see are fast. They bring low latency, which is just as important as their bandwidth. Current IB cards run at 56 gbit/s. That is slightly more than double of the capacity of a PCI Gen2 slot (of ~25 gbit/s). And IB cards are equipped usually with two ports - that is, altogether you'd need 112 gbit/s PCI slots, to be able to utilize FDR IB cards in an active-active fashion. PCI Gen3 slots provide you with around ~50gbps. This is why the most IB cards are configured in an active-standby way if both ports are used. Once again the PCI slot is the bottleneck. Anyway, the new Oracle servers are equipped with Gen3 PCI slots, an the new IB HCAs support those too. Oracle utilizes the QDR HCAs, running at 40gbp/s brutto, which translates to a 32gbp/s net traffic due to the 10:8 signal-to-data information ratio. Consolidation techniques: Technology never stops to evolve. Mellanox is working on the 100 gbps (EDR) version already, which will be optical, since signal technology doesn't allow EDR to be copper. Also, I hear you say "100gbps? I will never use/need that much". Are you sure? Have you considered consolidation scenarios, where (for example with Oracle Virtual Network) you could consolidate your platform to a high densitiy virtualized solution providing many virtual 10gbps interfaces through that 100gbps? Technology never stops to evolve. I still remember when a 10mbps network was impressively fast. Back in those days, 16MB of RAM was a lot. Now we usually run servers with around 100.000 times more RAM. If network infrastrucure speends could grow as fast as main memory capacities, we'd have a different landscape now :) You can utilize SRIOV as well for consolidation. That is, if you run LDoms (aka Oracle VM Server for SPARC) you do not have to add physical IB cards to all your guest LDoms, and you do not need to run VIO devices through the hypervisor either (avoiding overhead). You can enable SRIOV on those IB cards, which practically virtualizes the PCI bus, and you can dedicate Physical- and Virtual Functions of the virtualized HCAs as native, physical HW devices to your guests. See Raghuram's excellent post explaining SRIOV. SRIOV for IB is supported since LDoms 3.1.  This post is getting lengthier, so I will rename it to Part I, and continue it in a second post. 

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  • The Linux powered LAN Gaming House

    - by sachinghalot
    LAN parties offer the enjoyment of head to head gaming in a real-life social environment. In general, they are experiencing decline thanks to the convenience of Internet gaming, but Kenton Varda is a man who takes his LAN gaming very seriously. His LAN gaming house is a fascinating project, and best of all, Linux plays a part in making it all work.Varda has done his own write ups (short, long), so I'm only going to give an overview here. The setup is a large house with 12 gaming stations and a single server computer.The client computers themselves are rack mounted in a server room, and they are linked to the gaming stations on the floor above via extension cables (HDMI for video and audio and USB for mouse and keyboard). Each client computer, built into a 3U rack mount case, is a well specced gaming rig in its own right, sporting an Intel Core i5 processor, 4GB of RAM and an Nvidia GeForce 560 along with a 60GB SSD drive.Originally, the client computers ran Ubuntu Linux rather than Windows and the games executed under WINE, but Varda had to abandon this scheme. As he explains on his site:"Amazingly, a majority of games worked fine, although many had minor bugs (e.g. flickering mouse cursor, minor rendering artifacts, etc.). Some games, however, did not work, or had bad bugs that made them annoying to play."Subsequently, the gaming computers have been moved onto a more conventional gaming choice, Windows 7. It's a shame that WINE couldn't be made to work, but I can sympathize as it's rare to find modern games that work perfectly and at full native speed. Another problem with WINE is that it tends to suffer from regressions, which is hardly surprising when considering the difficulty of constantly improving the emulation of the Windows API. Varda points out that he preferred working with Linux clients as they were easier to modify and came with less licensing baggage.Linux still runs the server and all of the tools used are open source software. The hardware here is a Intel Xeon E3-1230 with 4GB of RAM. The storage hanging off this machine is a bit more complex than the clients. In addition to the 60GB SSD, it also has 2x1TB drives and a 240GB SDD.When the clients were running Linux, they booted over PXE using a toolchain that will be familiar to anyone who has setup Linux network booting. DHCP pointed the clients to the server which then supplied PXELINUX using TFTP. When booted, file access was accomplished through network block device (NBD). This is a very easy to use system that allows you to serve the contents of a file as a block device over the network. The client computer runs a user mode device driver and the device can be mounted within the file system using the mount command.One snag with offering file access via NBD is that it's difficult to impose any security restrictions on different areas of the file system as the server only sees a single file. The advantage is perfomance as the client operating system simply sees a block device, and besides, these security issues aren't relevant in this setup.Unfortunately, Windows 7 can't use NBD, so, Varda had to switch to iSCSI (which works in both server and client mode under Linux). His network cards are not compliant with this standard when doing a netboot, but fortunately, gPXE came to the rescue, and he boostraps it over PXE. gPXE is also available as an ISO image and is worth knowing about if you encounter an awkward machine that can't manage a network boot. It can also optionally boot from a HTTP server rather than the more traditional TFTP server.According to Varda, booting all 12 machines over the Gigabit Ethernet network is surprisingly fast, and once booted, the machines don't seem noticeably slower than if they were using local storage. Once loaded, most games attempt to load in as much data as possible, filling the RAM, and the the disk and network bandwidth required is small. It's worth noting that these are aspects of this project that might differ from some other thin client scenarios.At time of writing, it doesn't seem as though the local storage of the client machines is being utilized. Instead, the clients boot into Windows from an image on the server that contains the operating system and the games themselves. It uses the copy on write feature of LVM so that any writes from a client are added to a differencing image allocated to that client. As the administrator, Varda can log into the Linux server and authorize changes to the master image for updates etc.SummaryOverall, Varda estimates the total cost of the project at about $40,000, and of course, he needed a property that offered a large physical space in order to house the computers and the gaming workstations. Obviously, this project has stark differences to most thin client projects. The balance between storage, network usage, GPU power and security would not be typical of an office installation, for example. The only letdown is that WINE proved to be insufficiently compatible to run a wide variety of modern games, but that is, perhaps, asking too much of it, and hats off to Varda for trying to make it work.

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  • Converting LINQ to Twitter to Twitter API v1.1

    - by Joe Mayo
    Twitter recently updated their API to v1.1 (Current status: API v1.1). Naturally, LINQ to Twitter  needed to be updated too. This blog post outlines the changes made to LINQ to Twitter during this conversion and highlights important features that LINQ to Twitter developers will want to know. Overall Impact Generally speaking, Twitter API v1.1 is semantically very much the same as it’s predecessor. The base URL changed and so did a few resource segments, but the resources themselves are still intact. The good news is that LINQ to Twitter has always shielded the developer from this plumbing, so the entities, types, and filters didn’t change much at all.  The following sections describe what did  change. Authentication In Twitter API v1.0 authentication was not required for some resources, such as user timelines and search. However, that’s all changed because *all* queries must be authenticated in Twitter API v1.1. LINQ to Twitter has various types of authorizers you can use, supporting whatever OAuth options are available via Twitter.  You can see the LINQ to Twitter documentation, Securing Your Applications, for more info on OAuth support. The New Search One of the larger changes to the API was Search. To be more specific, the Search entity now contains a List<Status>, named Statuses, to hold results.  Additionally, any meta-data associated with the search is now in a property named SearchMetaData. The change to the Search entity and responses is the big change, but the good news is that your Search query syntax doesn’t change. Different Rate Limits The issue of rate limits itself is contentious, but this discussion is focused on the coding experience and I’ll leave the politics to those who prefer to engage in that activity. What’s important here is that both headers and resources have changed. You should review Twitter’s Rate Limit documentation to understand what the changes mean.  A quick explanation is that rate limits are applied individually to each resource in 15 minute time intervals. In LINQ to Twitter these changes surface on the Help entity, via HelpType.RateLimits. The RateLimits query has a Resources filter where you can specify a comma-separated list of categories to return rate limit info for.  The results materialize in the RateLimits dictionary, keyed on category. The Help entity also has a RateLimitsAuthorizationContext, holding the Access Token for the user performing queries – and to whom the rate limits apply. In addition to the new RateLimits query, there are new RateLimit headers that appear in the query response, whose HTTP header name is of the form X-Rate-Limit… which is different from the previous header name. LINQ to Twitter surfaces these headers via the existing properties of the TwitterContext instance. For anyone who retrieved rate limit information via the Headers property of TwitterContext, you should be aware of the new header names.  I haven’t done anything with Feature rate limit properties yet, but they appear to no longer be available – this will require more follow-up. Error Handling Twitter API v1.1 has a new format for Error Codes & Responses. LINQ to Twitter wraps these messages in the TwitterQueryException, which has been updated appropriately. The Message property of TwitterQueryException now reflects the Twitter error message, when available. There’s also a new ErrorCode that’s populated with the message error code. Parameters Most parameters stayed the same, but one of interest is Include Entities (different from LINQ to Twitter data object entities). Entities are metadata hanging off tweets, that provide start/end position in the tweet and other information for mentions, urls, hash tags, and media. Entities used to not be included unless you specified you wanted them. Now, in v1.1, entities are included by default for all APIs that return a Status.  If you were always setting IncludeEntities to true, then you won’t see a change. However, be aware that you’ll now be receiving additional data in your response from Twitter, which will explain a sudden increase in bandwidth utilization. This might or might not  matter to you  depending on the requirements of your application, but you should be aware of it. Everything Else There might be small changes here and there that I haven’t mentioned, but these were the ones you should be most aware of.  Streams didn’t change, but Twitter will be deprecating username/password authentication on public streams, in favor of OAuth, so you’ll be seeing me make that change some time in the future.  Also, Twitter will continue to evolve the API and you can expect that LINQ to Twitter will change accordingly. Summary The big changes to Twitter API were Authentication, Search, Rate Limits, and Error Handling. All API calls must be authenticated. You’ll need to change your code to read Search results differently, but the query is much the same as you use now. There’s a new RateLimits API, one of the Help queries.  Also, the new error messages are integrated into TwitterQueryException. Besides these changes, I expect  most others to be small or affect a smaller percentage of developers.  You can get the latest version of LINQ to Twitter from NuGet or visit the LINQ to Twitter download page at CodePlex.com.   @JoeMayo

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  • JavaDay Taipei 2014 Trip Report

    - by reza_rahman
    JavaDay Taipei 2014 was held at the Taipei International Convention Center on August 1st. Organized by Oracle University, it is one of the largest Java developer events in Taiwan. This was another successful year for JavaDay Taipei with a fully sold out venue packed with youthful, energetic developers (this was my second time at the event and I have already been invited to speak again next year!). In addition to Oracle speakers like me, Steve Chin and Naveen Asrani, the event also featured a bevy of local speakers including Taipei Java community leaders. Topics included Java SE, Java EE, JavaFX, cloud and Big Data. It was my pleasure and privilege to present one of the opening keynotes for the event. I presented my session on Java EE titled "JavaEE.Next(): Java EE 7, 8, and Beyond". I covered the changes in Java EE 7 as well as what's coming in Java EE 8. I demoed the Cargo Tracker Java EE BluePrints. I also briefly talked about Adopt-a-JSR for Java EE 8. The slides for the keynote are below (click here to download and view the actual PDF): It appears your Web browser is not configured to display PDF files. No worries, just click here to download the PDF file. In the afternoon I did my JavaScript + Java EE 7 talk titled "Using JavaScript/HTML5 Rich Clients with Java EE 7". This talk is basically about aligning EE 7 with the emerging JavaScript ecosystem (specifically AngularJS). The talk was completely packed. The slide deck for the talk is here: JavaScript/HTML5 Rich Clients Using Java EE 7 from Reza Rahman The demo application code is posted on GitHub. The code should be a helpful resource if this development model is something that interests you. Do let me know if you need help with it but the instructions should be fairly self-explanatory. I am delivering this material at JavaOne 2014 as a two-hour tutorial. This should give me a little more bandwidth to dig a little deeper, especially on the JavaScript end. I finished off Java Day Taipei with my talk titled "Using NoSQL with ~JPA, EclipseLink and Java EE" (this was the last session of the conference). The talk covers an interesting gap that there is surprisingly little material on out there. The talk has three parts -- a birds-eye view of the NoSQL landscape, how to use NoSQL via a JPA centric facade using EclipseLink NoSQL, Hibernate OGM, DataNucleus, Kundera, Easy-Cassandra, etc and how to use NoSQL native APIs in Java EE via CDI. The slides for the talk are here: Using NoSQL with ~JPA, EclipseLink and Java EE from Reza Rahman The JPA based demo is available here, while the CDI based demo is available here. Both demos use MongoDB as the data store. Do let me know if you need help getting the demos up and running. After the event the Oracle University folks hosted a reception in the evening which was very well attended by organizers, speakers and local Java community leaders. I am extremely saddened by the fact that this otherwise excellent trip was scarred by terrible tragedy. After the conference I joined a few folks for a hike on the Maokong Mountain on Saturday. The group included friends in the Taiwanese Java community including Ian and Robbie Cheng. Without warning, fatal tragedy struck on a remote part of the trail. Despite best efforts by us, the excellent Taiwanese Emergency Rescue Team and World class Taiwanese physicians we were unable to save our friend Robbie Cheng's life. Robbie was just thirty-four years old and is survived by his younger brother, mother and father. Being the father of a young child myself, I can only imagine the deep sorrow that this senseless loss unleashes. Robbie was a key member of the Taiwanese Java community and a Java Evangelist at Sun at one point. Ironically the only picture I was able to take of the trail was mere moments before tragedy. I thought I should place him in that picture in profoundly respectful memoriam: Perhaps there is some solace in the fact that there is something inherently honorable in living a bright life, dying young and meeting one's end on a beautiful remote mountain trail few venture to behold let alone attempt to ascend in a long and tired lifetime. Perhaps I'd even say it's a fate I would not entirely regret facing if it were my own. With that thought in mind it seems appropriate to me to quote some lyrics from the song "Runes to My Memory" by legendary Swedish heavy metal band Amon Amarth idealizing a fallen Viking warrior cut down in his prime: "Here I lie on wet sand I will not make it home I clench my sword in my hand Say farewell to those I love When I am dead Lay me in a mound Place my weapons by my side For the journey to Hall up high When I am dead Lay me in a mound Raise a stone for all to see Runes carved to my memory" I submit my deepest condolences to Robbie's family and hope my next trip to Taiwan ends in a less somber note.

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  • CPU Usage in Very Large Coherence Clusters

    - by jpurdy
    When sizing Coherence installations, one of the complicating factors is that these installations (by their very nature) tend to be application-specific, with some being large, memory-intensive caches, with others acting as I/O-intensive transaction-processing platforms, and still others performing CPU-intensive calculations across the data grid. Regardless of the primary resource requirements, Coherence sizing calculations are inherently empirical, in that there are so many permutations that a simple spreadsheet approach to sizing is rarely optimal (though it can provide a good starting estimate). So we typically recommend measuring actual resource usage (primarily CPU cycles, network bandwidth and memory) at a given load, and then extrapolating from those measurements. Of course there may be multiple types of load, and these may have varying degrees of correlation -- for example, an increased request rate may drive up the number of objects "pinned" in memory at any point, but the increase may be less than linear if those objects are naturally shared by concurrent requests. But for most reasonably-designed applications, a linear resource model will be reasonably accurate for most levels of scale. However, at extreme scale, sizing becomes a bit more complicated as certain cluster management operations -- while very infrequent -- become increasingly critical. This is because certain operations do not naturally tend to scale out. In a small cluster, sizing is primarily driven by the request rate, required cache size, or other application-driven metrics. In larger clusters (e.g. those with hundreds of cluster members), certain infrastructure tasks become intensive, in particular those related to members joining and leaving the cluster, such as introducing new cluster members to the rest of the cluster, or publishing the location of partitions during rebalancing. These tasks have a strong tendency to require all updates to be routed via a single member for the sake of cluster stability and data integrity. Fortunately that member is dynamically assigned in Coherence, so it is not a single point of failure, but it may still become a single point of bottleneck (until the cluster finishes its reconfiguration, at which point this member will have a similar load to the rest of the members). The most common cause of scaling issues in large clusters is disabling multicast (by configuring well-known addresses, aka WKA). This obviously impacts network usage, but it also has a large impact on CPU usage, primarily since the senior member must directly communicate certain messages with every other cluster member, and this communication requires significant CPU time. In particular, the need to notify the rest of the cluster about membership changes and corresponding partition reassignments adds stress to the senior member. Given that portions of the network stack may tend to be single-threaded (both in Coherence and the underlying OS), this may be even more problematic on servers with poor single-threaded performance. As a result of this, some extremely large clusters may be configured with a smaller number of partitions than ideal. This results in the size of each partition being increased. When a cache server fails, the other servers will use their fractional backups to recover the state of that server (and take over responsibility for their backed-up portion of that state). The finest granularity of this recovery is a single partition, and the single service thread can not accept new requests during this recovery. Ordinarily, recovery is practically instantaneous (it is roughly equivalent to the time required to iterate over a set of backup backing map entries and move them to the primary backing map in the same JVM). But certain factors can increase this duration drastically (to several seconds): large partitions, sufficiently slow single-threaded CPU performance, many or expensive indexes to rebuild, etc. The solution of course is to mitigate each of those factors but in many cases this may be challenging. Larger clusters also lead to the temptation to place more load on the available hardware resources, spreading CPU resources thin. As an example, while we've long been aware of how garbage collection can cause significant pauses, it usually isn't viewed as a major consumer of CPU (in terms of overall system throughput). Typically, the use of a concurrent collector allows greater responsiveness by minimizing pause times, at the cost of reducing system throughput. However, at a recent engagement, we were forced to turn off the concurrent collector and use a traditional parallel "stop the world" collector to reduce CPU usage to an acceptable level. In summary, there are some less obvious factors that may result in excessive CPU consumption in a larger cluster, so it is even more critical to test at full scale, even though allocating sufficient hardware may often be much more difficult for these large clusters.

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  • A Patent for Workload Management Based on Service Level Objectives

    - by jsavit
    I'm very pleased to announce that after a tiny :-) wait of about 5 years, my patent application for a workload manager was finally approved. Background Many operating systems have a resource manager which lets you control machine resources. For example, Solaris provides controls for CPU with several options: shares for proportional CPU allocation. If you have twice as many shares as me, and we are competing for CPU, you'll get about twice as many CPU cycles), dedicated CPU allocation in which a number of CPUs are exclusively dedicated to an application's use. You can say that a zone or project "owns" 8 CPUs on a 32 CPU machine, for example. And, capped CPU in which you specify the upper bound, or cap, of how much CPU an application gets. For example, you can throttle an application to 0.125 of a CPU. (This isn't meant to be an exhaustive list of Solaris RM controls.) Workload management Useful as that is (and tragic that some other operating systems have little resource management and isolation, and frighten people into running only 1 app per OS instance - and wastefully size every server for the peak workload it might experience) that's not really workload management. With resource management one controls the resources, and hope that's enough to meet application service objectives. In fact, we hold resource distribution constant, see if that was good enough, and adjust resource distribution if that didn't meet service level objectives. Here's an example of what happens today: Let's try 30% dedicated CPU. Not enough? Let's try 80% Oh, that's too much, and we're achieving much better response time than the objective, but other workloads are starving. Let's back that off and try again. It's not the process I object to - it's that we to often do this manually. Worse, we sometimes identify and adjust the wrong resource and fiddle with that to no useful result. Back in my days as a customer managing large systems, one of my users would call me up to beg for a "CPU boost": Me: "it won't make any difference - there's plenty of spare CPU to be had, and your application is completely I/O bound." User: "Please do it anyway." Me: "oh, all right, but it won't do you any good." (I did, because he was a friend, but it didn't help.) Prior art There are some operating environments that take a stab about workload management (rather than resource management) but I find them lacking. I know of one that uses synthetic "service units" composed of the sum of CPU, I/O and memory allocations multiplied by weighting factors. A workload is set to make a target rate of service units consumed per second. But this seems to be missing a key point: what is the relationship between artificial 'service units' and actually meeting a throughput or response time objective? What if I get plenty of one of the components (so am getting enough service units), but not enough of the resource whose needed to remove the bottleneck? Actual workload management That's not really the answer either. What is needed is to specify a workload's service levels in terms of externally visible metrics that are meaningful to a business, such as response times or transactions per second, and have the workload manager figure out which resources are not being adequately provided, and then adjust it as needed. If an application is not meeting its service level objectives and the reason is that it's not getting enough CPU cycles, adjust its CPU resource accordingly. If the reason is that the application isn't getting enough RAM to keep its working set in memory, then adjust its RAM assignment appropriately so it stops swapping. Simple idea, but that's a task we keep dumping on system administrators. In other words - don't hold the number of CPU shares constant and watch the achievement of service level vary. Instead, hold the service level constant, and dynamically adjust the number of CPU shares (or amount of other resources like RAM or I/O bandwidth) in order to meet the objective. Instrumenting non-instrumented applications There's one little problem here: how do I measure application performance in a way relating to a service level. I don't want to do it based on internal resources like number of CPU seconds it received per minute - We need to make resource decisions based on externally visible and meaningful measures of performance, not synthetic items or internal resource counters. If I have a way of marking the beginning and end of a transaction, I can then measure whether or not the application is meeting an objective based on it. If I can observe the delay factors for an application, I can see which resource shortages are slowing an application enough to keep it from meeting its objectives. I can then adjust resource allocations to relieve those shortages. Fortunately, Solaris provides facilities for both marking application progress and determining what factors cause application latency. The Solaris DTrace facility let's me introspect on application behavior: in particular I can see events like "receive a web hit" and "respond to that web hit" so I can get transaction rate and response time. DTrace (and tools like prstat) let me see where latency is being added to an application, so I know which resource to adjust. Summary After a delay of a mere few years, I am the proud creator of a patent (advice to anyone interested in going through the process: don't hold your breath!). The fundamental idea is fairly simple: instead of holding resource constant and suffering variable levels of success meeting service level objectives, properly characterise the service level objective in meaningful terms, instrument the application to see if it's meeting the objective, and then have a workload manager change resource allocations to remove delays preventing service level attainment. I've done it by hand for a long time - I think that's what a computer should do for me.

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  • What is Happening vs. What is Interesting

    - by Geertjan
    Devoxx 2011 was yet another confirmation that all development everywhere is either on the web or on mobile phones. Whether you looked at the conference schedule or attended sessions or talked to speakers at any point at all, it was very clear that no development whatsoever is done anymore on the desktop. In fact, that's something Tim Bray himself told me to my face at the speakers dinner. No new developments of any kind are happening on the desktop. Everyone who is currently on the desktop is working overtime to move all of their applications to the web. They're probably also creating a small subset of their application on an Android tablet, with an even smaller subset on their Android phone. Then you scratch that monolithic surface and find some interesting results. Without naming any names, I asked one of these prominent "ah, forget about the desktop" people at the Devoxx speakers dinner (and I have a witness): "Yes, the desktop is dead, but what about air traffic control, stock trading, oil analysis, risk management applications? In fact, what about any back office application that needs to be usable across all operating systems? Here there is no concern whatsoever with 100% accessibility which is, after all, the only thing that the web has over the desktop, (except when there's a network failure, of course, or when you find yourself in the 3/4 of the world where there's bandwidth problems)? There are 1000's of hidden applications out there that have processing requirements, security requirements, and the requirement that they'll be available even when the network is down or even completely unavailable. Isn't that a valid use case and aren't there 1000's of applications that fall into this so-called niche category? Are you not, in fact, confusing consumer applications, which are increasingly web-based and mobile-based, with high-end corporate applications, which typically need to do massive processing, of one kind or another, for which the web and mobile worlds are completely unsuited?" And you will not believe what the reply to the above question was. (Again, I have a witness to this discussion.) But here it is: "Yes. But those applications are not interesting. I do not want to spend any of my time or work in any way on those applications. They are boring." I'm sad to say that the leaders of the software development community, including those in the Java world, either share the above opinion or are led by it. Because they find something that is not new to be boring, they move on to what is interesting and start talking like the supposedly-boring developments don't even exist. (Kind of like a rapper pretending classical music doesn't exist.) Time and time again I find myself giving Java desktop development courses (at companies, i.e., not hobbyists, or students, but companies, i.e., the places where dollars are earned), where developers say to me: "The course you're giving about creating cross-platform, loosely coupled, and highly cohesive applications is really useful to us. Why do we never find information about this topic at conferences? Why can we never attend a session at a conference where the story about pluggable cross-platform Java is told? Why do we get the impression that we are uncool because we're not on the web and because we're not on a mobile phone, while the reason for that is because we're creating $1000,000 simulation software which has nothing to gain from being on the web or on the mobile phone?" And then I say: "Because nobody knows you exist. Because you're not submitting abstracts to conferences about your very interesting use cases. And because conferences tend to focus on what is new, which tends to be web related (especially HTML 5) or mobile related (especially Android). Because you're not taking the responsibility on yourself to tell the real stories about the real applications being developed all the time and every day. Because you yourself think your work is boring, while in fact it is fascinating. Because desktop developers are working from 9 to 5 on the desktop, in secure environments, such as banks and defense, where you can't spend time, nor have the interest in, blogging your latest tip or trick, as opposed to web developers, who tend to spend a lot of time on the web anyway and are therefore much more inclined to create buzz about the kind of work they're doing." So, next time you look at a conference program and wonder why there's no stories about large desktop development projects in the program, here's the short answer: "No one is going to put those items on the program until you start submitting those kinds of sessions. And until you start blogging. Until you start creating the buzz that the web developers have been creating around their work for the past 10 years or so. And, yes, indeed, programmers get the conference they deserve." And what about Tim Bray? Ask yourself, as Google's lead web technology evangelist, how many desktop developers do you think he talks to and, more generally, what his frame of reference is and what, clearly, he considers to be most interesting.

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  • What's New in Oracle VM VirtualBox 4.2?

    - by Fat Bloke
    A year is a long time in the IT industry. Since the last VirtualBox feature release, which was a little over a year ago, we've seen: new releases of cool new operating systems, such as Windows 8, ChromeOS, and Mountain Lion; we've seen a myriad of new Linux releases from big Enterprise class distributions like Oracle 6.3, to accessible desktop distros like Ubuntu 12.04 and Fedora 17; and we've also seen the spec of a typical PC or laptop double in power. All of these events have influenced our new VirtualBox version which we're releasing today. Here's how... Powerful hosts  One of the trends we've seen is that as the average host platform becomes more powerful, our users are consistently running more and more vm's. Some of our users have large libraries of vm's of various vintages, whilst others have groups of vm's that are run together as an assembly of the various tiers in a multi-tiered software solution, for example, a database tier, middleware tier, and front-ends.  So we're pleased to unveil a more powerful VirtualBox Manager to address the needs of these users: VM Groups Groups allow you to organize your VM library in a sensible way, e.g.  by platform type, by project, by version, by whatever. To create groups you can drag one VM onto another or select one or more VM's and choose Machine...Group from the menu bar. You can expand and collapse groups to save screen real estate, and you can Enter and Leave a group (think iPad navigation here) by using the right and left arrow keys when groups are selected. But groups are more than passive folders, because you can now also perform operations on groups, rather than all the individual VMs. So if you have a multi-tiered solution you can start the whole stack up with just one click. Autostart Many VirtualBox users run dedicated services in their VMs, for example, running a Wiki. With these types of VM workloads, you really want the VM start up when the host machine boots up. So with 4.2 we've introduced a cross-platform Auto-start mechanism to allow you to treat VMs as host services. Headless VM Launching With VM's such as web servers, wikis, and other types of server-class workloads, the Console of the VM is pretty much redundant. For some time now VirtualBox has offered a separate launch mechanism for these VM's, namely the command-line interface commands VBoxHeadless or VBoxManage startvm ... --type headless commands. But with 4.2 we also allow you launch headless VMs from the Manager. Simply hold down Shift when launching the VM from the Manager.  It's that easy. But how do you stop a headless VM? Well, with 4.2 we allow you to Close the VM from the Manager. (BTW best to use the ACPI Shutdown method which allows the guest VM to close down gracefully.) Easy VM Creation For our expert users, the  New VM Wizard was a little tiresome, so now there's a faster 2-click VM creation mode. Just Hide the description when creating a new VM. Powerful VMs  As the hosts have become more powerful, so are the guests that are running inside them. Here are some of the 4.2 features to accommodate them: Virtual Network Interface Cards  With 4.2, it's now possible to create VMs with up to 36 NICs, when using the ICH9 chipset emulation. But with great power comes great responsibility (didn't Obi-Wan say something similar?), and so we have also introduced bandwidth limiting to prevent a rogue VM stealing the whole pipe. VLAN tagging Some of our users leverage VLANs extensively so we've enhanced the E1000 NICs to support this.  Processor Performance If you are running a CPU which supports Nested Paging (aka EPT in the Intel world) such as most of the Core i5 and i7 CPUs, or are running an AMD Bulldozer or later, you should see some performance improvements from our work with these processors. And while we're talking Processors, we've added support for some of the more modern VIA CPUs too. Powerful Automation Because VirtualBox runs atop a fully blown operating system, it makes sense to leverage the capabilities of the host to run scripts that can drive the guest VMs. Guest Automation was introduced in a prior release but with 4.2 we've revamped the APIs to allow a richer and more powerful set of operations to be executed by the guest. Check out the IGuest APIs in the VirtualBox Programming Guide and Reference (SDK). Powerful Platforms  All the hardcore engineering that has gone into 4.2 has been done for a purpose and that is to deliver a fast and powerful engine that can run almost any x86 OS because of the integrity of the virtualization. So we're pleased to add support for these platforms: Mac OS X "Mountain Lion"  Windows 8 Windows Server 2012 Ubuntu 12.04 (“Precise Pangolin”) Fedora 17 Oracle Linux 6.3  Here's the proof: We don't have time to go into the myriad of smaller improvements such as support for burning audio CDs from a guest, bi-directional clipboard control,  drag-and-drop of files into Linux guests, etc. so we'll leave that as an exercise for the user as soon as you've downloaded from the Oracle or community site and taken a peek at the User Guide. So all in all, a pretty solid release, one that we hope you'll enjoy discovering. - FB 

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  • CLSF & CLK 2013 Trip Report by Jeff Liu

    - by jamesmorris
    This is a contributed post from Jeff Liu, lead XFS developer for the Oracle mainline Linux kernel team. Recently, I attended both the China Linux Storage and Filesystem workshop (CLSF), and the China Linux Kernel conference (CLK), which were held in Shanghai. Here are the highlights for both events. CLSF - 17th October XFS update (led by Jeff Liu) XFS keeps rapid progress with a lot of changes, especially focused on the infrastructure/performance improvements as well as  new feature development.  This can be reflected with a sample statistics among XFS/Ext4+JBD2/Btrfs via: # git diff --stat --minimal -C -M v3.7..v3.12-rc4 -- fs/xfs|fs/ext4+fs/jbd2|fs/btrfs XFS: 141 files changed, 27598 insertions(+), 19113 deletions(-) Ext4+JBD2: 39 files changed, 10487 insertions(+), 5454 deletions(-) Btrfs: 70 files changed, 19875 insertions(+), 8130 deletions(-) What made up those changes in XFS? Self-describing metadata(CRC32c). This is a new feature and it contributed about 70% code changes, it can be enabled via `mkfs.xfs -m crc=1 /dev/xxx` for v5 superblock. Transaction log space reservation improvements. With this change, we can calculate the log space reservation at mount time rather than runtime to reduce the the CPU overhead. User namespace support. So both XFS and USERNS can be enabled on kernel configuration begin from Linux 3.10. Thanks Dwight Engen's efforts for this thing. Split project/group quota inodes. Originally, project quota can not be enabled with group quota at the same time because they were share the same quota file inode, now it works but only for v5 super block. i.e, CRC enabled. CONFIG_XFS_WARN, an new lightweight runtime debugger which can be deployed in production environment. Readahead log object recovery, this change can speed up the log replay progress significantly. Speculative preallocation inode tracking, clearing and throttling. The main purpose is to deal with inodes with post-EOF space due to speculative preallocation, support improved quota management to free up a significant amount of unwritten space when at or near EDQUOT. It support backgroup scanning which occurs on a longish interval(5 mins by default, tunable), and on-demand scanning/trimming via ioctl(2). Bitter arguments ensued from this session, especially for the comparison between Ext4 and Btrfs in different areas, I have to spent a whole morning of the 1st day answering those questions. We basically agreed on XFS is the best choice in Linux nowadays because: Stable, XFS has a good record in stability in the past 10 years. Fengguang Wu who lead the 0-day kernel test project also said that he has observed less error than other filesystems in the past 1+ years, I own it to the XFS upstream code reviewer, they always performing serious code review as well as testing. Good performance for large/small files, XFS does not works very well for small files has already been an old story for years. Best choice (maybe) for distributed PB filesystems. e.g, Ceph recommends delopy OSD daemon on XFS because Ext4 has limited xattr size. Best choice for large storage (>16TB). Ext4 does not support a single file more than around 15.95TB. Scalability, any objection to XFS is best in this point? :) XFS is better to deal with transaction concurrency than Ext4, why? The maximum size of the log in XFS is 2038MB compare to 128MB in Ext4. Misc. Ext4 is widely used and it has been proved fast/stable in various loads and scenarios, XFS just need more customers, and Btrfs is still on the road to be a manhood. Ceph Introduction (Led by Li Wang) This a hot topic.  Li gave us a nice introduction about the design as well as their current works. Actually, Ceph client has been included in Linux kernel since 2.6.34 and supported by Openstack since Folsom but it seems that it has not yet been widely deployment in production environment. Their major work is focus on the inline data support to separate the metadata and data storage, reduce the file access time, i.e, a file access need communication twice, fetch the metadata from MDS and then get data from OSD, and also, the small file access is limited by the network latency. The solution is, for the small files they would like to store the data at metadata so that when accessing a small file, the metadata server can push both metadata and data to the client at the same time. In this way, they can reduce the overhead of calculating the data offset and save the communication to OSD. For this feature, they have only run some small scale testing but really saw noticeable improvements. Test environment: Intel 2 CPU 12 Core, 64GB RAM, Ubuntu 12.04, Ceph 0.56.6 with 200GB SATA disk, 15 OSD, 1 MDS, 1 MON. The sequence read performance for 1K size files improved about 50%. I have asked Li and Zheng Yan (the core developer of Ceph, who also worked on Btrfs) whether Ceph is really stable and can be deployed at production environment for large scale PB level storage, but they can not give a positive answer, looks Ceph even does not spread over Dreamhost (subject to confirmation). From Li, they only deployed Ceph for a small scale storage(32 nodes) although they'd like to try 6000 nodes in the future. Improve Linux swap for Flash storage (led by Shaohua Li) Because of high density, low power and low price, flash storage (SSD) is a good candidate to partially replace DRAM. A quick answer for this is using SSD as swap. But Linux swap is designed for slow hard disk storage, so there are a lot of challenges to efficiently use SSD for swap. SWAPOUT swap_map scan swap_map is the in-memory data structure to track swap disk usage, but it is a slow linear scan. It will become a bottleneck while finding many adjacent pages in the use of SSD. Shaohua Li have changed it to a cluster(128K) list, resulting in O(1) algorithm. However, this apporoach needs restrictive cluster alignment and only enabled for SSD. IO pattern In most cases, the swap io is in interleaved pattern because of mutiple reclaimers or a free cluster is shared by all reclaimers. Even though block layer can merge interleaved IO to some extent, but we cannot count on it completely. Hence the per-cpu cluster is added base on the previous change, it can help reclaimer do sequential IO and the block layer will be easier to merge IO. TLB flush: If we're reclaiming one active page, we should first move the page from active lru list to inactive lru list, and then reclaim the page from inactive lru to swap it out. During the process, we need to clear PTE twice: first is 'A'(ACCESS) bit, second is 'P'(PRESENT) bit. Processors need to send lots of ipi which make the TLB flush really expensive. Some works have been done to improve this, including rework smp_call_functiom_many() or remove the first TLB flush in x86, but there still have some arguments here and only parts of works have been pushed to mainline. SWAPIN: Page fault does iodepth=1 sync io, but it's a little waste if only issue a page size's IO. The obvious solution is doing swap readahead. But the current in-kernel swap readahead is arbitary(always 8 pages), and it always doesn't perform well for both random and sequential access workload. Shaohua introduced a new flag for madvise(MADV_WILLNEED) to do swap prefetch, so the changes happen in userspace API and leave the in-kernel readahead unchanged(but I think some improvement can also be done here). SWAP discard As we know, discard is important for SSD write throughout, but the current swap discard implementation is synchronous. He changed it to async discard which allow discard and write run in the same time. Meanwhile, the unit of discard is also optimized to cluster. Misc: lock contention For many concurrent swapout and swapin , the lock contention such as anon_vma or swap_lock is high, so he changed the swap_lock to a per-swap lock. But there still have some lock contention in very high speed SSD because of swapcache address_space lock. Zproject (led by Bob Liu) Bob gave us a very nice introduction about the current memory compression status. Now there are 3 projects(zswap/zram/zcache) which all aim at smooth swap IO storm and promote performance, but they all have their own pros and cons. ZSWAP It is implemented based on frontswap API and it uses a dynamic allocater named Zbud to allocate free pages. Zbud means pairs of zpages are "buddied" and it can only store at most two compressed pages in one page frame, so the max compress ratio is 50%. Each page frame is lru-linked and can do shink in memory pressure. If the compressed memory pool reach its limitation, shink or reclaim happens. It decompress the page frame into two new allocated pages and then write them to real swap device, but it can fail when allocating the two pages. ZRAM Acts as a compressed ramdisk and used as swap device, and it use zsmalloc as its allocator which has high density but may have fragmentation issues. Besides, page reclaim is hard since it will need more pages to uncompress and free just one page. ZRAM is preferred by embedded system which may not have any real swap device. Now both ZRAM and ZSWAP are in driver/staging tree, and in the mm community there are some disscussions of merging ZRAM into ZSWAP or viceversa, but no agreement yet. ZCACHE Handles file page compression but it is removed out of staging recently. From industry (led by Tang Jie, LSI) An LSI engineer introduced several new produces to us. The first is raid5/6 cards that it use full stripe writes to improve performance. The 2nd one he introduced is SandForce flash controller, who can understand data file types (data entropy) to reduce write amplification (WA) for nearly all writes. It's called DuraWrite and typical WA is 0.5. What's more, if enable its Dynamic Logical Capacity function module, the controller can do data compression which is transparent to upper layer. LSI testing shows that with this virtual capacity enables 1x TB drive can support up to 2x TB capacity, but the application must monitor free flash space to maintain optimal performance and to guard against free flash space exhaustion. He said the most useful application is for datebase. Another thing I think it's worth to mention is that a NV-DRAM memory in NMR/Raptor which is directly exposed to host system. Applications can directly access the NV-DRAM via a memory address - using standard system call mmap(). He said that it is very useful for database logging now. This kind of NVM produces are beginning to appear in recent years, and it is said that Samsung is building a research center in China for related produces. IMHO, NVM will bring an effect to current os layer especially on file system, e.g. its journaling may need to redesign to fully utilize these nonvolatile memory. OCFS2 (led by Canquan Shen) Without a doubt, HuaWei is the biggest contributor to OCFS2 in the past two years. They have posted 46 upstream patches and 39 patches have been merged. Their current project is based on 32/64 nodes cluster, but they also tried 128 nodes at the experimental stage. The major work they are working is to support ATS (atomic test and set), it can be works with DLM at the same time. Looks this idea is inspired by the vmware VMFS locking, i.e, http://blogs.vmware.com/vsphere/2012/05/vmfs-locking-uncovered.html CLK - 18th October 2013 Improving Linux Development with Better Tools (Andi Kleen) This talk focused on how to find/solve bugs along with the Linux complexity growing. Generally, we can do this with the following kind of tools: Static code checkers tools. e.g, sparse, smatch, coccinelle, clang checker, checkpatch, gcc -W/LTO, stanse. This can help check a lot of things, simple mistakes, complex problems, but the challenges are: some are very slow, false positives, may need a concentrated effort to get false positives down. Especially, no static checker I found can follow indirect calls (“OO in C”, common in kernel): struct foo_ops { int (*do_foo)(struct foo *obj); } foo->do_foo(foo); Dynamic runtime checkers, e.g, thread checkers, kmemcheck, lockdep. Ideally all kernel code would come with a test suite, then someone could run all the dynamic checkers. Fuzzers/test suites. e.g, Trinity is a great tool, it finds many bugs, but needs manual model for each syscall. Modern fuzzers around using automatic feedback, but notfor kernel yet: http://taviso.decsystem.org/making_software_dumber.pdf Debuggers/Tracers to understand code, e.g, ftrace, can dump on events/oops/custom triggers, but still too much overhead in many cases to run always during debug. Tools to read/understand source, e.g, grep/cscope work great for many cases, but do not understand indirect pointers (OO in C model used in kernel), give us all “do_foo” instances: struct foo_ops { int (*do_foo)(struct foo *obj); } = { .do_foo = my_foo }; foo>do_foo(foo); That would be great to have a cscope like tool that understands this based on types/initializers XFS: The High Performance Enterprise File System (Jeff Liu) [slides] I gave a talk for introducing the disk layout, unique features, as well as the recent changes.   The slides include some charts to reflect the performances between XFS/Btrfs/Ext4 for small files. About a dozen users raised their hands when I asking who has experienced with XFS. I remembered that when I asked the same question in LinuxCon/Japan, only 3 people raised their hands, but they are Chris Mason, Ric Wheeler, and another attendee. The attendee questions were mainly focused on stability, and comparison with other file systems. Linux Containers (Feng Gao) The speaker introduced us that the purpose for those kind of namespaces, include mount/UTS/IPC/Network/Pid/User, as well as the system API/ABI. For the userspace tools, He mainly focus on the Libvirt LXC rather than us(LXC). Libvirt LXC is another userspace container management tool, implemented as one type of libvirt driver, it can manage containers, create namespace, create private filesystem layout for container, Create devices for container and setup resources controller via cgroup. In this talk, Feng also mentioned another two possible new namespaces in the future, the 1st is the audit, but not sure if it should be assigned to user namespace or not. Another is about syslog, but the question is do we really need it? In-memory Compression (Bob Liu) Same as CLSF, a nice introduction that I have already mentioned above. Misc There were some other talks related to ACPI based memory hotplug, smart wake-affinity in scheduler etc., but my head is not big enough to record all those things. -- Jeff Liu

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  • ASPNET WebAPI REST Guidance

    - by JoshReuben
    ASP.NET Web API is an ideal platform for building RESTful applications on the .NET Framework. While I may be more partial to NodeJS these days, there is no denying that WebAPI is a well engineered framework. What follows is my investigation of how to leverage WebAPI to construct a RESTful frontend API.   The Advantages of REST Methodology over SOAP Simpler API for CRUD ops Standardize Development methodology - consistent and intuitive Standards based à client interop Wide industry adoption, Ease of use à easy to add new devs Avoid service method signature blowout Smaller payloads than SOAP Stateless à no session data means multi-tenant scalability Cache-ability Testability   General RESTful API Design Overview · utilize HTTP Protocol - Usage of HTTP methods for CRUD, standard HTTP response codes, common HTTP headers and Mime Types · Resources are mapped to URLs, actions are mapped to verbs and the rest goes in the headers. · keep the API semantic, resource-centric – A RESTful, resource-oriented service exposes a URI for every piece of data the client might want to operate on. A REST-RPC Hybrid exposes a URI for every operation the client might perform: one URI to fetch a piece of data, a different URI to delete that same data. utilize Uri to specify CRUD op, version, language, output format: http://api.MyApp.com/{ver}/{lang}/{resource_type}/{resource_id}.{output_format}?{key&filters} · entity CRUD operations are matched to HTTP methods: · Create - POST / PUT · Read – GET - cacheable · Update – PUT · Delete - DELETE · Use Uris to represent a hierarchies - Resources in RESTful URLs are often chained · Statelessness allows for idempotency – apply an op multiple times without changing the result. POST is non-idempotent, the rest are idempotent (if DELETE flags records instead of deleting them). · Cache indication - Leverage HTTP headers to label cacheable content and indicate the permitted duration of cache · PUT vs POST - The client uses PUT when it determines which URI (Id key) the new resource should have. The client uses POST when the server determines they key. PUT takes a second param – the id. POST creates a new resource. The server assigns the URI for the new object and returns this URI as part of the response message. Note: The PUT method replaces the entire entity. That is, the client is expected to send a complete representation of the updated product. If you want to support partial updates, the PATCH method is preferred DELETE deletes a resource at a specified URI – typically takes an id param · Leverage Common HTTP Response Codes in response headers 200 OK: Success 201 Created - Used on POST request when creating a new resource. 304 Not Modified: no new data to return. 400 Bad Request: Invalid Request. 401 Unauthorized: Authentication. 403 Forbidden: Authorization 404 Not Found – entity does not exist. 406 Not Acceptable – bad params. 409 Conflict - For POST / PUT requests if the resource already exists. 500 Internal Server Error 503 Service Unavailable · Leverage uncommon HTTP Verbs to reduce payload sizes HEAD - retrieves just the resource meta-information. OPTIONS returns the actions supported for the specified resource. PATCH - partial modification of a resource. · When using PUT, POST or PATCH, send the data as a document in the body of the request. Don't use query parameters to alter state. · Utilize Headers for content negotiation, caching, authorization, throttling o Content Negotiation – choose representation (e.g. JSON or XML and version), language & compression. Signal via RequestHeader.Accept & ResponseHeader.Content-Type Accept: application/json;version=1.0 Accept-Language: en-US Accept-Charset: UTF-8 Accept-Encoding: gzip o Caching - ResponseHeader: Expires (absolute expiry time) or Cache-Control (relative expiry time) o Authorization - basic HTTP authentication uses the RequestHeader.Authorization to specify a base64 encoded string "username:password". can be used in combination with SSL/TLS (HTTPS) and leverage OAuth2 3rd party token-claims authorization. Authorization: Basic sQJlaTp5ZWFslylnaNZ= o Rate Limiting - Not currently part of HTTP so specify non-standard headers prefixed with X- in the ResponseHeader. X-RateLimit-Limit: 10000 X-RateLimit-Remaining: 9990 · HATEOAS Methodology - Hypermedia As The Engine Of Application State – leverage API as a state machine where resources are states and the transitions between states are links between resources and are included in their representation (hypermedia) – get API metadata signatures from the response Link header - in a truly REST based architecture any URL, except the initial URL, can be changed, even to other servers, without worrying about the client. · error responses - Do not just send back a 200 OK with every response. Response should consist of HTTP error status code (JQuery has automated support for this), A human readable message , A Link to a meaningful state transition , & the original data payload that was problematic. · the URIs will typically map to a server-side controller and a method name specified by the type of request method. Stuff all your calls into just four methods is not as crazy as it sounds. · Scoping - Path variables look like you’re traversing a hierarchy, and query variables look like you’re passing arguments into an algorithm · Mapping URIs to Controllers - have one controller for each resource is not a rule – can consolidate - route requests to the appropriate controller and action method · Keep URls Consistent - Sometimes it’s tempting to just shorten our URIs. not recommend this as this can cause confusion · Join Naming – for m-m entity relations there may be multiple hierarchy traversal paths · Routing – useful level of indirection for versioning, server backend mocking in development ASPNET WebAPI Considerations ASPNET WebAPI implements a lot (but not all) RESTful API design considerations as part of its infrastructure and via its coding convention. Overview When developing an API there are basically three main steps: 1. Plan out your URIs 2. Setup return values and response codes for your URIs 3. Implement a framework for your API.   Design · Leverage Models MVC folder · Repositories – support IoC for tests, abstraction · Create DTO classes – a level of indirection decouples & allows swap out · Self links can be generated using the UrlHelper · Use IQueryable to support projections across the wire · Models can support restful navigation properties – ICollection<T> · async mechanism for long running ops - return a response with a ticket – the client can then poll or be pushed the final result later. · Design for testability - Test using HttpClient , JQuery ( $.getJSON , $.each) , fiddler, browser debug. Leverage IDependencyResolver – IoC wrapper for mocking · Easy debugging - IE F12 developer tools: Network tab, Request Headers tab     Routing · HTTP request method is matched to the method name. (This rule applies only to GET, POST, PUT, and DELETE requests.) · {id}, if present, is matched to a method parameter named id. · Query parameters are matched to parameter names when possible · Done in config via Routes.MapHttpRoute – similar to MVC routing · Can alternatively: o decorate controller action methods with HttpDelete, HttpGet, HttpHead,HttpOptions, HttpPatch, HttpPost, or HttpPut., + the ActionAttribute o use AcceptVerbsAttribute to support other HTTP verbs: e.g. PATCH, HEAD o use NonActionAttribute to prevent a method from getting invoked as an action · route table Uris can support placeholders (via curly braces{}) – these can support default values and constraints, and optional values · The framework selects the first route in the route table that matches the URI. Response customization · Response code: By default, the Web API framework sets the response status code to 200 (OK). But according to the HTTP/1.1 protocol, when a POST request results in the creation of a resource, the server should reply with status 201 (Created). Non Get methods should return HttpResponseMessage · Location: When the server creates a resource, it should include the URI of the new resource in the Location header of the response. public HttpResponseMessage PostProduct(Product item) {     item = repository.Add(item);     var response = Request.CreateResponse<Product>(HttpStatusCode.Created, item);     string uri = Url.Link("DefaultApi", new { id = item.Id });     response.Headers.Location = new Uri(uri);     return response; } Validation · Decorate Models / DTOs with System.ComponentModel.DataAnnotations properties RequiredAttribute, RangeAttribute. · Check payloads using ModelState.IsValid · Under posting – leave out values in JSON payload à JSON formatter assigns a default value. Use with RequiredAttribute · Over-posting - if model has RO properties à use DTO instead of model · Can hook into pipeline by deriving from ActionFilterAttribute & overriding OnActionExecuting Config · Done in App_Start folder > WebApiConfig.cs – static Register method: HttpConfiguration param: The HttpConfiguration object contains the following members. Member Description DependencyResolver Enables dependency injection for controllers. Filters Action filters – e.g. exception filters. Formatters Media-type formatters. by default contains JsonFormatter, XmlFormatter IncludeErrorDetailPolicy Specifies whether the server should include error details, such as exception messages and stack traces, in HTTP response messages. Initializer A function that performs final initialization of the HttpConfiguration. MessageHandlers HTTP message handlers - plug into pipeline ParameterBindingRules A collection of rules for binding parameters on controller actions. Properties A generic property bag. Routes The collection of routes. Services The collection of services. · Configure JsonFormatter for circular references to support links: PreserveReferencesHandling.Objects Documentation generation · create a help page for a web API, by using the ApiExplorer class. · The ApiExplorer class provides descriptive information about the APIs exposed by a web API as an ApiDescription collection · create the help page as an MVC view public ILookup<string, ApiDescription> GetApis()         {             return _explorer.ApiDescriptions.ToLookup(                 api => api.ActionDescriptor.ControllerDescriptor.ControllerName); · provide documentation for your APIs by implementing the IDocumentationProvider interface. Documentation strings can come from any source that you like – e.g. extract XML comments or define custom attributes to apply to the controller [ApiDoc("Gets a product by ID.")] [ApiParameterDoc("id", "The ID of the product.")] public HttpResponseMessage Get(int id) · GlobalConfiguration.Configuration.Services – add the documentation Provider · To hide an API from the ApiExplorer, add the ApiExplorerSettingsAttribute Plugging into the Message Handler pipeline · Plug into request / response pipeline – derive from DelegatingHandler and override theSendAsync method – e.g. for logging error codes, adding a custom response header · Can be applied globally or to a specific route Exception Handling · Throw HttpResponseException on method failures – specify HttpStatusCode enum value – examine this enum, as its values map well to typical op problems · Exception filters – derive from ExceptionFilterAttribute & override OnException. Apply on Controller or action methods, or add to global HttpConfiguration.Filters collection · HttpError object provides a consistent way to return error information in the HttpResponseException response body. · For model validation, you can pass the model state to CreateErrorResponse, to include the validation errors in the response public HttpResponseMessage PostProduct(Product item) {     if (!ModelState.IsValid)     {         return Request.CreateErrorResponse(HttpStatusCode.BadRequest, ModelState); Cookie Management · Cookie header in request and Set-Cookie headers in a response - Collection of CookieState objects · Specify Expiry, max-age resp.Headers.AddCookies(new CookieHeaderValue[] { cookie }); Internet Media Types, formatters and serialization · Defaults to application/json · Request Accept header and response Content-Type header · determines how Web API serializes and deserializes the HTTP message body. There is built-in support for XML, JSON, and form-urlencoded data · customizable formatters can be inserted into the pipeline · POCO serialization is opt out via JsonIgnoreAttribute, or use DataMemberAttribute for optin · JSON serializer leverages NewtonSoft Json.NET · loosely structured JSON objects are serialzed as JObject which derives from Dynamic · to handle circular references in json: json.SerializerSettings.PreserveReferencesHandling =    PreserveReferencesHandling.All à {"$ref":"1"}. · To preserve object references in XML [DataContract(IsReference=true)] · Content negotiation Accept: Which media types are acceptable for the response, such as “application/json,” “application/xml,” or a custom media type such as "application/vnd.example+xml" Accept-Charset: Which character sets are acceptable, such as UTF-8 or ISO 8859-1. Accept-Encoding: Which content encodings are acceptable, such as gzip. Accept-Language: The preferred natural language, such as “en-us”. o Web API uses the Accept and Accept-Charset headers. (At this time, there is no built-in support for Accept-Encoding or Accept-Language.) · Controller methods can take JSON representations of DTOs as params – auto-deserialization · Typical JQuery GET request: function find() {     var id = $('#prodId').val();     $.getJSON("api/products/" + id,         function (data) {             var str = data.Name + ': $' + data.Price;             $('#product').text(str);         })     .fail(         function (jqXHR, textStatus, err) {             $('#product').text('Error: ' + err);         }); }            · Typical GET response: HTTP/1.1 200 OK Server: ASP.NET Development Server/10.0.0.0 Date: Mon, 18 Jun 2012 04:30:33 GMT X-AspNet-Version: 4.0.30319 Cache-Control: no-cache Pragma: no-cache Expires: -1 Content-Type: application/json; charset=utf-8 Content-Length: 175 Connection: Close [{"Id":1,"Name":"TomatoSoup","Price":1.39,"ActualCost":0.99},{"Id":2,"Name":"Hammer", "Price":16.99,"ActualCost":10.00},{"Id":3,"Name":"Yo yo","Price":6.99,"ActualCost": 2.05}] True OData support · Leverage Query Options $filter, $orderby, $top and $skip to shape the results of controller actions annotated with the [Queryable]attribute. [Queryable]  public IQueryable<Supplier> GetSuppliers()  · Query: ~/Suppliers?$filter=Name eq ‘Microsoft’ · Applies the following selection filter on the server: GetSuppliers().Where(s => s.Name == “Microsoft”)  · Will pass the result to the formatter. · true support for the OData format is still limited - no support for creates, updates, deletes, $metadata and code generation etc · vnext: ability to configure how EditLinks, SelfLinks and Ids are generated Self Hosting no dependency on ASPNET or IIS: using (var server = new HttpSelfHostServer(config)) {     server.OpenAsync().Wait(); Tracing · tracability tools, metrics – e.g. send to nagios · use your choice of tracing/logging library, whether that is ETW,NLog, log4net, or simply System.Diagnostics.Trace. · To collect traces, implement the ITraceWriter interface public class SimpleTracer : ITraceWriter {     public void Trace(HttpRequestMessage request, string category, TraceLevel level,         Action<TraceRecord> traceAction)     {         TraceRecord rec = new TraceRecord(request, category, level);         traceAction(rec);         WriteTrace(rec); · register the service with config · programmatically trace – has helper extension methods: Configuration.Services.GetTraceWriter().Info( · Performance tracing - pipeline writes traces at the beginning and end of an operation - TraceRecord class includes aTimeStamp property, Kind property set to TraceKind.Begin / End Security · Roles class methods: RoleExists, AddUserToRole · WebSecurity class methods: UserExists, .CreateUserAndAccount · Request.IsAuthenticated · Leverage HTTP 401 (Unauthorized) response · [AuthorizeAttribute(Roles="Administrator")] – can be applied to Controller or its action methods · See section in WebApi document on "Claim-based-security for ASP.NET Web APIs using DotNetOpenAuth" – adapt this to STS.--> Web API Host exposes secured Web APIs which can only be accessed by presenting a valid token issued by the trusted issuer. http://zamd.net/2012/05/04/claim-based-security-for-asp-net-web-apis-using-dotnetopenauth/ · Use MVC membership provider infrastructure and add a DelegatingHandler child class to the WebAPI pipeline - http://stackoverflow.com/questions/11535075/asp-net-mvc-4-web-api-authentication-with-membership-provider - this will perform the login actions · Then use AuthorizeAttribute on controllers and methods for role mapping- http://sixgun.wordpress.com/2012/02/29/asp-net-web-api-basic-authentication/ · Alternate option here is to rely on MVC App : http://forums.asp.net/t/1831767.aspx/1

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  • Tips / techniques for high-performance C# server sockets

    - by McKenzieG1
    I have a .NET 2.0 server that seems to be running into scaling problems, probably due to poor design of the socket-handling code, and I am looking for guidance on how I might redesign it to improve performance. Usage scenario: 50 - 150 clients, high rate (up to 100s / second) of small messages (10s of bytes each) to / from each client. Client connections are long-lived - typically hours. (The server is part of a trading system. The client messages are aggregated into groups to send to an exchange over a smaller number of 'outbound' socket connections, and acknowledgment messages are sent back to the clients as each group is processed by the exchange.) OS is Windows Server 2003, hardware is 2 x 4-core X5355. Current client socket design: A TcpListener spawns a thread to read each client socket as clients connect. The threads block on Socket.Receive, parsing incoming messages and inserting them into a set of queues for processing by the core server logic. Acknowledgment messages are sent back out over the client sockets using async Socket.BeginSend calls from the threads that talk to the exchange side. Observed problems: As the client count has grown (now 60-70), we have started to see intermittent delays of up to 100s of milliseconds while sending and receiving data to/from the clients. (We log timestamps for each acknowledgment message, and we can see occasional long gaps in the timestamp sequence for bunches of acks from the same group that normally go out in a few ms total.) Overall system CPU usage is low (< 10%), there is plenty of free RAM, and the core logic and the outbound (exchange-facing) side are performing fine, so the problem seems to be isolated to the client-facing socket code. There is ample network bandwidth between the server and clients (gigabit LAN), and we have ruled out network or hardware-layer problems. Any suggestions or pointers to useful resources would be greatly appreciated. If anyone has any diagnostic or debugging tips for figuring out exactly what is going wrong, those would be great as well. Note: I have the MSDN Magazine article Winsock: Get Closer to the Wire with High-Performance Sockets in .NET, and I have glanced at the Kodart "XF.Server" component - it looks sketchy at best.

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  • MVC 2 View Layout CSS Control Layout

    - by Cory Mathewson
    I'm new to a lot of what I'm trying to do with the development of a new MVC2 web application so this is a beginner question. I need to understand my options for control and content layout on a web page. I’m using MVC2 so I’m using Controllers, Views, ViewModels, and View Templates. What I need to spin up on…fast…is control the granular layout of controls and content on any particular view. Below I’ve pasted two examples of auto generated templates that illustrate my challenge. I see that layout is controlled by CSS in my Site.css document. In the first example I get a sequential flow of DisplayLabel and DisplayField. I prefer the adjacent layout of DisplayLabel on the same line as DisplayField produced from example 2. However, example 2 is too simple because the formatting is applied to the Label and the Field. I think the correct way to tackle this learning curve is Microsoft Expression but I don’t have personal bandwidth at the moment to tackle Expression. Can anyone point me to a resource that will expose me to lots of examples for CSS formatting? I have lots of syntax questions. For instance, I believe is referencing the Site.css but I can’t find a "display-label" section in Site.css. Example 1 <fieldset> <legend>Fields</legend> <div class="display-label">DocTitle</div> <div class="display-field"><%: Model.DocTitle %></div> <div class="display-label">DocoumentPropertiesID</div> <div class="display-field"><%: Model.DocumentPropertiesID %></div> Example 2 <h2>Title: <%: Model.DocTitle %></h2> <h2>Created: <%: Model.Created %></h2> <h2>Modified: <%: Model.Modified %></h2> <h2>Author: <%: Model.tbl_Author.Name %></h2> <h2>Genre: <%: Model.tbl_DocumentGenre.GenreName %></h2>

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