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• Running OpenStack Icehouse with ZFS Storage Appliance

  - by Ronen Kofman

  Couple of months ago Oracle announced the support for OpenStack Cinder plugin with ZFS Storage Appliance (aka ZFSSA).  With our recent release of the Icehouse tech preview I thought it is a good opportunity to demonstrate the ZFSSA plugin working with Icehouse. One thing that helps a lot to get started with ZFSSA is that it has a VirtualBox simulator. This simulator allows users to try out the appliance’s features before getting to a real box. Users can test the functionality and design an environment even before they have a real appliance which makes the deployment process much more efficient. With OpenStack this is especially nice because having a simulator on the other end allows us to test the complete set of the Cinder plugin and check the entire integration on a single server or even a laptop. Let’s see how this works Installing and Configuring the Simulator To get started we first need to download the simulator, the simulator is available here, unzip it and it is ready to be imported to VirtualBox. If you do not already have VirtualBox installed you can download it from here according to your platform of choice. To import the simulator go to VirtualBox console File -> Import Appliance , navigate to the location of the simulator and import the virtual machine. When opening the virtual machine you will need to make the following changes: - Network – by default the network is “Host Only” , the user needs to change that to “Bridged” so the VM can connect to the network and be accessible. - Memory (optional) – the VM comes with a default of 2560MB which may be fine but if you have more memory that could not hurt, in my case I decided to give it 8192 - vCPU (optional) – the default the VM comes with 1 vCPU, I decided to change it to two, you are welcome to do so too. And here is how the VM looks like: Start the VM, when the boot process completes we will need to change the root password and the simulator is running and ready to go. Now that the simulator is up and running we can access simulated appliance using the URL https://<IP or DNS name>:215/, the IP is showing on the virtual machine console. At this stage we will need to configure the appliance, in my case I did not change any of the default (in other words pressed ‘commit’ several times) and the simulated appliance was configured and ready to go. We will need to enable REST access otherwise Cinder will not be able to call the appliance we do that in Configuration->Services and at the end of the page there is ‘REST’ button, enable it. If you are a more advanced user you can set additional features in the appliance but for the purpose of this demo this is sufficient. One final step will be to create a pool, go to Configuration -> Storage and add a pool as shown below the pool is named “default”: The simulator is now running, configured and ready for action. Configuring Cinder Back to OpenStack, I have a multi node deployment which we created according to the “Getting Started with Oracle VM, Oracle Linux and OpenStack” guide using Icehouse tech preview release. Now we need to install and configure the ZFSSA Cinder plugin using the README file. In short the steps are as follows: 1. Copy the file from here to the control node and place them at: /usr/lib/python2.6/site-packages/cinder/volume/drivers/zfssa 2. Configure the plugin, editing /etc/cinder/cinder.conf # Driver to use for volume creation (string value) #volume_driver=cinder.volume.drivers.lvm.LVMISCSIDriver volume_driver=cinder.volume.drivers.zfssa.zfssaiscsi.ZFSSAISCSIDriver zfssa_host = <HOST IP> zfssa_auth_user = root zfssa_auth_password = <ROOT PASSWORD> zfssa_pool = default zfssa_target_portal = <HOST IP>:3260 zfssa_project = test zfssa_initiator_group = default zfssa_target_interfaces = e1000g0 3. Restart the cinder-volume service: service openstack-cinder-volume restart 4. Look into the log file, this will tell us if everything works well so far. If you see any errors fix them before continuing. 5. Install iscsi-initiator-utils package, this is important since the plugin uses iscsi commands from this package: yum install -y iscsi-initiator-utils The installation and configuration are very simple, we do not need to have a “project” in the ZFSSA but we do need to define a pool. Creating and Using Volumes in OpenStack We are now ready to work, to get started lets create a volume in OpenStack and see it showing up on the simulator: #  cinder create 2 --display-name my-volume-1 +---------------------+--------------------------------------+ |       Property      |                Value                 | +---------------------+--------------------------------------+ |     attachments     |                  []                  | |  availability_zone  |                 nova                 | |       bootable      |                false                 | |      created_at     |      2014-08-12T04:24:37.806752      | | display_description |                 None                 | |     display_name    |             my-volume-1              | |      encrypted      |                False                 | |          id         | df67c447-9a36-4887-a8ff-74178d5d06ee | |       metadata      |                  {}                  | |         size        |                  2                   | |     snapshot_id     |                 None                 | |     source_volid    |                 None                 | |        status       |               creating               | |     volume_type     |                 None                 | +---------------------+--------------------------------------+ In the simulator: Extending the volume to 5G: # cinder extend df67c447-9a36-4887-a8ff-74178d5d06ee 5 In the simulator: Creating templates using Cinder Volumes By default OpenStack supports ephemeral storage where an image is copied into the run area during instance launch and deleted when the instance is terminated. With Cinder we can create persistent storage and launch instances from a Cinder volume. Booting from volume has several advantages, one of the main advantages of booting from volumes is speed. No matter how large the volume is the launch operation is immediate there is no copying of an image to a run areas, an operation which can take a long time when using ephemeral storage (depending on image size). In this deployment we have a Glance image of Oracle Linux 6.5, I would like to make it into a volume which I can boot from. When creating a volume from an image we actually “download” the image into the volume and making the volume bootable, this process can take some time depending on the image size, during the download we will see the following status: # cinder create --image-id 487a0731-599a-499e-b0e2-5d9b20201f0f --display-name ol65 2 # cinder list +--------------------------------------+-------------+--------------+------+-------------+ |                  ID                  |    Status   | Display Name | Size | Volume Type | … +--------------------------------------+-------------+--------------+------+------------- | df67c447-9a36-4887-a8ff-74178d5d06ee |  available  | my-volume-1  |  5   |     None    | … | f61702b6-4204-4f10-8bdf-7da792f15c28 | downloading |     ol65     |  2   |     None    | … +--------------------------------------+-------------+--------------+------+-------------+ After the download is complete we will see that the volume status changed to “available” and that the bootable state is “true”. We can use this new volume to boot an instance from or we can use it as a template. Cinder can create a volume from another volume and ZFSSA can replicate volumes instantly in the back end. The result is an efficient template model where users can spawn an instance from a “template” instantly even if the template is very large in size. Let’s try replicating the bootable volume with the Oracle Linux 6.5 on it creating additional 3 bootable volumes: # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-1 # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-2 # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-3 # cinder list +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ |                  ID                  |   Status  |   Display Name  | Size | Volume Type | Bootable | Attached to | +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ | 9bfe0deb-b9c7-4d97-8522-1354fc533c26 | available | ol65-bootable-2 |  2   |     None    |   true   |             | | a311a855-6fb8-472d-b091-4d9703ef6b9a | available | ol65-bootable-1 |  2   |     None    |   true   |             | | df67c447-9a36-4887-a8ff-74178d5d06ee | available |   my-volume-1   |  5   |     None    |  false   |             | | e7fbd2eb-e726-452b-9a88-b5eee0736175 | available | ol65-bootable-3 |  2   |     None    |   true   |             | | f61702b6-4204-4f10-8bdf-7da792f15c28 | available |       ol65      |  2   |     None    |   true   |             | +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ Note that the creation of those 3 volume was almost immediate, no need to download or copy, ZFSSA takes care of the volume copy for us. Start 3 instances: # nova boot --boot-volume a311a855-6fb8-472d-b091-4d9703ef6b9a --flavor m1.tiny ol65-instance-1 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca # nova boot --boot-volume 9bfe0deb-b9c7-4d97-8522-1354fc533c26 --flavor m1.tiny ol65-instance-2 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca # nova boot --boot-volume e7fbd2eb-e726-452b-9a88-b5eee0736175 --flavor m1.tiny ol65-instance-3 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca Instantly replicating volumes is a very powerful feature, especially for large templates. The ZFSSA Cinder plugin allows us to take advantage of this feature of ZFSSA. By offloading some of the operations to the array OpenStack create a highly efficient environment where persistent volume can be instantly created from a template. That’s all for now, with this environment you can continue to test ZFSSA with OpenStack and when you are ready for the real appliance the operations will look the same. @RonenKofman

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• C#/.NET Little Wonders: Interlocked CompareExchange()

  - by James Michael Hare

  Once again, in this series of posts I look at the parts of the .NET Framework that may seem trivial, but can help improve your code by making it easier to write and maintain. The index of all my past little wonders posts can be found here. Two posts ago, I discussed the Interlocked Add(), Increment(), and Decrement() methods (here) for adding and subtracting values in a thread-safe, lightweight manner.  Then, last post I talked about the Interlocked Read() and Exchange() methods (here) for safely and efficiently reading and setting 32 or 64 bit values (or references).  This week, we’ll round out the discussion by talking about the Interlocked CompareExchange() method and how it can be put to use to exchange a value if the current value is what you expected it to be. Dirty reads can lead to bad results Many of the uses of Interlocked that we’ve explored so far have centered around either reading, setting, or adding values.  But what happens if you want to do something more complex such as setting a value based on the previous value in some manner? Perhaps you were creating an application that reads a current balance, applies a deposit, and then saves the new modified balance, where of course you’d want that to happen atomically.  If you read the balance, then go to save the new balance and between that time the previous balance has already changed, you’ll have an issue!  Think about it, if we read the current balance as $400, and we are applying a new deposit of $50.75, but meanwhile someone else deposits $200 and sets the total to $600, but then we write a total of $450.75 we’ve lost $200! Now, certainly for int and long values we can use Interlocked.Add() to handles these cases, and it works well for that.  But what if we want to work with doubles, for example?  Let’s say we wanted to add the numbers from 0 to 99,999 in parallel.  We could do this by spawning several parallel tasks to continuously add to a total: 1: double total = 0; 2:  3: Parallel.For(0, 10000, next => 4: { 5: total += next; 6: }); Were this run on one thread using a standard for loop, we’d expect an answer of 4,999,950,000 (the sum of all numbers from 0 to 99,999).  But when we run this in parallel as written above, we’ll likely get something far off.  The result of one of my runs, for example, was 1,281,880,740.  That is way off!  If this were banking software we’d be in big trouble with our clients.  So what happened?  The += operator is not atomic, it will read in the current value, add the result, then store it back into the total.  At any point in all of this another thread could read a “dirty” current total and accidentally “skip” our add.   So, to clean this up, we could use a lock to guarantee concurrency: 1: double total = 0.0; 2: object locker = new object(); 3:  4: Parallel.For(0, count, next => 5: { 6: lock (locker) 7: { 8: total += next; 9: } 10: }); Which will give us the correct result of 4,999,950,000.  One thing to note is that locking can be heavy, especially if the operation being locked over is trivial, or the life of the lock is a high percentage of the work being performed concurrently.  In the case above, the lock consumes pretty much all of the time of each parallel task – and the task being locked on is relatively trivial. Now, let me put in a disclaimer here before we go further: For most uses, lock is more than sufficient for your needs, and is often the simplest solution!    So, if lock is sufficient for most needs, why would we ever consider another solution?  The problem with locking is that it can suspend execution of your thread while it waits for the signal that the lock is free.  Moreover, if the operation being locked over is trivial, the lock can add a very high level of overhead.  This is why things like Interlocked.Increment() perform so well, instead of locking just to perform an increment, we perform the increment with an atomic, lockless method. As with all things performance related, it’s important to profile before jumping to the conclusion that you should optimize everything in your path.  If your profiling shows that locking is causing a high level of waiting in your application, then it’s time to consider lighter alternatives such as Interlocked. CompareExchange() – Exchange existing value if equal some value So let’s look at how we could use CompareExchange() to solve our problem above.  The general syntax of CompareExchange() is: T CompareExchange<T>(ref T location, T newValue, T expectedValue) If the value in location == expectedValue, then newValue is exchanged.  Either way, the value in location (before exchange) is returned. Actually, CompareExchange() is not one method, but a family of overloaded methods that can take int, long, float, double, pointers, or references.  It cannot take other value types (that is, can’t CompareExchange() two DateTime instances directly).  Also keep in mind that the version that takes any reference type (the generic overload) only checks for reference equality, it does not call any overridden Equals(). So how does this help us?  Well, we can grab the current total, and exchange the new value if total hasn’t changed.  This would look like this: 1: // grab the snapshot 2: double current = total; 3:  4: // if the total hasn’t changed since I grabbed the snapshot, then 5: // set it to the new total 6: Interlocked.CompareExchange(ref total, current + next, current); So what the code above says is: if the amount in total (1st arg) is the same as the amount in current (3rd arg), then set total to current + next (2nd arg).  This check and exchange pair is atomic (and thus thread-safe). This works if total is the same as our snapshot in current, but the problem, is what happens if they aren’t the same?  Well, we know that in either case we will get the previous value of total (before the exchange), back as a result.  Thus, we can test this against our snapshot to see if it was the value we expected: 1: // if the value returned is != current, then our snapshot must be out of date 2: // which means we didn't (and shouldn't) apply current + next 3: if (Interlocked.CompareExchange(ref total, current + next, current) != current) 4: { 5: // ooops, total was not equal to our snapshot in current, what should we do??? 6: } So what do we do if we fail?  That’s up to you and the problem you are trying to solve.  It’s possible you would decide to abort the whole transaction, or perhaps do a lightweight spin and try again.  Let’s try that: 1: double current = total; 2:  3: // make first attempt... 4: if (Interlocked.CompareExchange(ref total, current + i, current) != current) 5: { 6: // if we fail, go into a spin wait, spin, and try again until succeed 7: var spinner = new SpinWait(); 8:  9: do 10: { 11: spinner.SpinOnce(); 12: current = total; 13: } 14: while (Interlocked.CompareExchange(ref total, current + i, current) != current); 15: } 16:  This is not trivial code, but it illustrates a possible use of CompareExchange().  What we are doing is first checking to see if we succeed on the first try, and if so great!  If not, we create a SpinWait and then repeat the process of SpinOnce(), grab a fresh snapshot, and repeat until CompareExchnage() succeeds.  You may wonder why not a simple do-while here, and the reason it’s more efficient to only create the SpinWait until we absolutely know we need one, for optimal efficiency. Though not as simple (or maintainable) as a simple lock, this will perform better in many situations.  Comparing an unlocked (and wrong) version, a version using lock, and the Interlocked of the code, we get the following average times for multiple iterations of adding the sum of 100,000 numbers: 1: Unlocked money average time: 2.1 ms 2: Locked money average time: 5.1 ms 3: Interlocked money average time: 3 ms So the Interlocked.CompareExchange(), while heavier to code, came in lighter than the lock, offering a good compromise of safety and performance when we need to reduce contention. CompareExchange() - it’s not just for adding stuff… So that was one simple use of CompareExchange() in the context of adding double values -- which meant we couldn’t have used the simpler Interlocked.Add() -- but it has other uses as well. If you think about it, this really works anytime you want to create something new based on a current value without using a full lock.  For example, you could use it to create a simple lazy instantiation implementation.  In this case, we want to set the lazy instance only if the previous value was null: 1: public static class Lazy<T> where T : class, new() 2: { 3: private static T _instance; 4:  5: public static T Instance 6: { 7: get 8: { 9: // if current is null, we need to create new instance 10: if (_instance == null) 11: { 12: // attempt create, it will only set if previous was null 13: Interlocked.CompareExchange(ref _instance, new T(), (T)null); 14: } 15:  16: return _instance; 17: } 18: } 19: } So, if _instance == null, this will create a new T() and attempt to exchange it with _instance.  If _instance is not null, then it does nothing and we discard the new T() we created. This is a way to create lazy instances of a type where we are more concerned about locking overhead than creating an accidental duplicate which is not used.  In fact, the BCL implementation of Lazy<T> offers a similar thread-safety choice for Publication thread safety, where it will not guarantee only one instance was created, but it will guarantee that all readers get the same instance.  Another possible use would be in concurrent collections.  Let’s say, for example, that you are creating your own brand new super stack that uses a linked list paradigm and is “lock free”.  We could use Interlocked.CompareExchange() to be able to do a lockless Push() which could be more efficient in multi-threaded applications where several threads are pushing and popping on the stack concurrently. Yes, there are already concurrent collections in the BCL (in .NET 4.0 as part of the TPL), but it’s a fun exercise!  So let’s assume we have a node like this: 1: public sealed class Node<T> 2: { 3: // the data for this node 4: public T Data { get; set; } 5:  6: // the link to the next instance 7: internal Node<T> Next { get; set; } 8: } Then, perhaps, our stack’s Push() operation might look something like: 1: public sealed class SuperStack<T> 2: { 3: private volatile T _head; 4:  5: public void Push(T value) 6: { 7: var newNode = new Node<int> { Data = value, Next = _head }; 8:  9: if (Interlocked.CompareExchange(ref _head, newNode, newNode.Next) != newNode.Next) 10: { 11: var spinner = new SpinWait(); 12:  13: do 14: { 15: spinner.SpinOnce(); 16: newNode.Next = _head; 17: } 18: while (Interlocked.CompareExchange(ref _head, newNode, newNode.Next) != newNode.Next); 19: } 20: } 21:  22: // ... 23: } Notice a similar paradigm here as with adding our doubles before.  What we are doing is creating the new Node with the data to push, and with a Next value being the original node referenced by _head.  This will create our stack behavior (LIFO – Last In, First Out).  Now, we have to set _head to now refer to the newNode, but we must first make sure it hasn’t changed! So we check to see if _head has the same value we saved in our snapshot as newNode.Next, and if so, we set _head to newNode.  This is all done atomically, and the result is _head’s original value, as long as the original value was what we assumed it was with newNode.Next, then we are good and we set it without a lock!  If not, we SpinWait and try again. Once again, this is much lighter than locking in highly parallelized code with lots of contention.  If I compare the method above with a similar class using lock, I get the following results for pushing 100,000 items: 1: Locked SuperStack average time: 6 ms 2: Interlocked SuperStack average time: 4.5 ms So, once again, we can get more efficient than a lock, though there is the cost of added code complexity.  Fortunately for you, most of the concurrent collection you’d ever need are already created for you in the System.Collections.Concurrent (here) namespace – for more information, see my Little Wonders – The Concurent Collections Part 1 (here), Part 2 (here), and Part 3 (here). Summary We’ve seen before how the Interlocked class can be used to safely and efficiently add, increment, decrement, read, and exchange values in a multi-threaded environment.  In addition to these, Interlocked CompareExchange() can be used to perform more complex logic without the need of a lock when lock contention is a concern. The added efficiency, though, comes at the cost of more complex code.  As such, the standard lock is often sufficient for most thread-safety needs.  But if profiling indicates you spend a lot of time waiting for locks, or if you just need a lock for something simple such as an increment, decrement, read, exchange, etc., then consider using the Interlocked class’s methods to reduce wait. Technorati Tags: C#,CSharp,.NET,Little Wonders,Interlocked,CompareExchange,threading,concurrency

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• Dovecot vs Courier vs Cyrus

  - by wag2639

  What is best for a Personal/SMB mail server running on an Ubuntu Server (8.04+)? I want to setup my own mail server at home to evaluate some options for my company before I make a recommendation. Which is the most secure, efficient, and reliable? Also, which is easiest to integrate with an LDAP and Calendar solution?

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• Adding QR Codes to Exclaimer

  - by Matt

  We are running a piece of software called Exclaimer which sets a standard template for email signatures and grabs some details from Active directory, like Contact numbers and title. I need to add a QR Code to the signature but it will need to be different for 50 + people, so I cannot use the standard template. I could create a template for everyone individually, but I would like to know if there is a more efficient way of doing this?

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• How do I delete old calendar items in Outlook 2003?

  - by Ramesh

  Hi. I'm trying to delete old calendar items (I have a few years' worth) in Outlook and was wondering if there was a way to delete only non-recurring items as I need the recurring events for the future. I tried View Arrange by Current view Category and figured that I could manually check and delete any calendar items by hand. Is there a more efficient way to do this without having to actually script code? Thanks for your time!

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• What is a good ratio of consultant to full time employees?

  - by Andre

  We are looking at significantly increasing our development next year and we are wondering how many consultants we could support without alienating long term employees and remaining relatively efficient? Any thoughts? Thanks, Andre

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• How to push configurations to multiple Cisco Switches

  - by nixda

  Assume I have around 50 Cisco IE2000 Switches connected together and I want to reconfigure some settings, the same settings for every switch. Normally I would open a command line session via Putty and paste the commands. But as the number of switches is growing, even this method takes its time. I am aware of Kiwi CatTools. Unfortunately it's not free so I'm wondering if there are other efficient ways to configure a large number of Cisco switches.

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• Find all duplicate files by md5 hash

  - by Jamie Curran

  I'm trying to find all duplicate files based upon md5 hash and ordered by file size. So far I have this: find . -type f -print0 | xargs -0 -I "{}" sh -c 'md5sum "{}" | cut -f1 -d " " | tr "\n" " "; du -h "{}"' | sort -h -k2 -r | uniq -w32 --all-repeated=separate The output of this is: 1832348bb0c3b0b8a637a3eaf13d9f22 4.0K ./picture.sh 1832348bb0c3b0b8a637a3eaf13d9f22 4.0K ./picture2.sh 1832348bb0c3b0b8a637a3eaf13d9f22 4.0K ./picture2.s d41d8cd98f00b204e9800998ecf8427e 0 ./test(1).log Is this the most efficient way?

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• Match Hard Disk Partition Table?

  - by MA1

  What is the most efficient way to match the partition tables on two different hard disks? I have saved the partition tables using dd command in linux. The partition tables are from a Windows system.

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• What are some SMART Criteria I can use when comparing "green" datacenters?

  - by makerofthings7

  I'm looking to reduce my carbon footprint and want to find a "green" datacenter. There are so many ways to define a "green datacenter' I'm looking for examples of SMART Criteria such as 20% of power from renewable resources Low Power Usage Effectiveness When it comes to running a green datacenter, what are additional key factors I need to look for? What key words or technologies might those energy efficient datacenters be using?

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• Energy Efficiency: OLED

  - by _ande_turner_

  Which of the two is more energy efficient on a OLED Display? White text on a black background Black text on a white background Links to OLED vs LCD, efficiency wise, would also be appreciated.

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• How to detect form spamming on your web servers?

  - by splattne

  If you run hundred of web sites on your servers, what it is the most efficient, automated way to detect if bots are using your HTML forms to send spam email, even if your forms have some kind of protection?

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• I/O intensive MySql server on Amazon AWS

  - by rhossi

  We recently moved from a traditional Data Center to cloud computing on AWS. We are developing a product in partnership with another company, and we need to create a database server for the product we'll release. I have been using Amazon Web Services for the past 3 years, but this is the first time I received a spec with this very specific hardware configuration. I know there are trade-offs and that real hardware will always be faster than virtual machines, and knowing that fact forehand, what would you recommend? 1) Amazon EC2? 2) Amazon RDS? 3) Something else? 4) Forget it baby, stick to the real hardware Here is the hardware requirements This server will be focused on I/O and MySQL for the statistics, memory size and disk space for the images hosting. Server 1 I/O The very main part on this server will be I/O processing, FusionIO cards have proven themselves extremely efficient, this is currently the best you can have in this domain. o Fusion ioDrive2 MLC 365GB (http://www.fusionio.com/load/-media-/1m66wu/docsLibrary/FIO_ioDrive2_Datasheet.pdf) CPU MySQL will use less CPU cores than Apache but it will use them very hard, the E7 family has 30M Cache L3 wichi provide boost performance : o 1x Intel E7-2870 will be ok. Storage SAS will be good enough in terms of performance, especially considering the space required. o RAID 10 of 4 x SAS 10k or 15k for a total available space of 512 GB. Memory o 64 GB minimum is required on this server considering the size of the statistics database. Warning: the statistics database will grow quickly, if possible consider starting with 128 GB directly, it will help. This server will be focused on I/O and MySQL for the statistics, memory size and disk space for the images hosting. Server 2 I/O The very main part on this server will be I/O processing, FusionIO cards have proven themselves extremely efficient, this is currently the best you can have in this domain. o Fusion ioDrive2 MLC 365GB (http://www.fusionio.com/load/-media-/1m66wu/docsLibrary/FIO_ioDrive2_Datasheet.pdf) CPU MySQL will use less CPU cores than Apache but it will use them very hard, the E7 family has 30M Cache L3 wichi provide boost performance : o 1x Intel E7-2870 will be ok. Storage SAS will be good enough in terms of performance, especially considering the space required. o RAID 10 of 4 x SAS 10k or 15k for a total available space of 512 GB. Memory o 64 GB minimum is required on this server considering the size of the statistics database. Warning: the statistics database will grow quickly, if possible consider starting with 128 GB directly, it will help. Thanks in advance. Best,

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• How can I efficiently replace a program's icon?

  - by RCIX

  I've downloaded a set of Adobe CS4 replacement icons, and I'd like to change the Adobe applications/document icons I have to use this new set. Is there an easy and efficient way I can do this?

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• How do a binary diff on two identically sized files under linux?

  - by Jon Cage

  I have two identically sized files and I need to do a binary diff to check whether they're the same. I'm currently runnnig diff file1.img file2.img but it's taking quite a while to process my 4GB files. Is this the most efficient way to do this?

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• Using SSD as disk cache

  - by casualcoder

  Is there software for Linux to use an SSD as disk cache? I believe that Sun does something like this with ZFS, though not sure. A quick search provides nothing suitable. The goal would be to put frequently requested files on the SSD on-the-fly. Since the SSD has more capacity than RAM for less money and better performance than hard disk, this should provide an efficient performance boost.

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• Domain name backwards, still good?

  - by Svein Erik

  I'm wondering if I buy a domain name the uses keywords backwards is almost as efficient as the "right way". For example, if I want the domain: "www.bluesocks.com", but that was occupied. Then I find that "www.socksblue.com" is available, will that domain be valuable for people searching for "blue socks"?

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• Providing DNS redirection to honeypot server for known bad domains

  - by syn-

  Currently running BIND on RHEL 5.4 and am looking for a more efficient manner of providing DNS redirection to a honeypot server for a large (30,000+) list of forbidden domains. Our current solution for this requirement is to include a file containing a zone master declaration for each blocked domain in named.conf. Subsequently, each of these zone declarations point to the same zone file, which resolves all hosts in that domain to our honeypot servers. ...basically this allows us to capture any "phone home" attempts by malware that may infiltrate the internal systems. The problem with this configuration is the large amount of time taken to load all 30,000+ domains as well as management of the domain list configuration file itself... if any errors creep into this file, the BIND server will fail to start, thereby making automation of the process a little frightening. So I'm looking for something more efficient and potentially less error prone. named.conf entry: include "blackholes.conf"; blackholes.conf entry example: zone "bad-domain.com" IN { type master; file "/var/named/blackhole.zone"; allow-query { any; }; notify no; }; blackhole.zone entries: $INCLUDE std.soa @ NS ns1.ourdomain.com. @ NS ns2.ourdomain.com. @ NS ns3.ourdomain.com.                        IN            A                192.168.0.99 *                      IN            A                192.168.0.99

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• installation and maintenance of an OS and applications over multiple PCs

  - by cornjuliox

  Let's say I've got around 50 PCs with identical specs but no CD or floppy drives and a blank hard disk, is there an efficient way to install (and update) an OS and software on each of them? Would I have to go to each PC one by one with the CDs or is there a way to install over a network? In the case of Windows XP would you need 50 separate copies?

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• Difference between linux and BSD

  - by karthi-27

  Hi all, I want to know the differences between Linux and BSD .Which is efficient. Because they have some of the similarities with them.

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• is there an alternative to outlook rules

  - by oo

  i have asked a number of questions around outlook rules and no matter how small i make the names and how efficient i make the rules, i ultimately still hit the 32 limit at about 40 rules. Is there any alternative to do this job since outlook rules just doesn't seem scalable to to keep up with the way people are emailing over the past 10 yearsoutlo.

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• Is there a Vim-like word processor?

  - by janoChen

  I've realized that Vim makes some basic tasks very efficient (cutting, deleting, pasting...) I would love to have those features in a word processor. Does anyone know one (I prefer open source).

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• Match Hard Dusk Partition Table?

  - by MA1

  Hi All What is the efficient way to match the two different hard disk partition tables? I have save the partition tables using dd command in linux. The partition tables are from Windows system. Regards,

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• Multitasking on iOS4 and its stated battery efficiency

  - by eml

  Apple stated that the reason multitasking didn't arrive before iOS4 is because they hadn't figured out how to do it right. Jobs stated at Apple WWDC 2010 that they now do and that they solved the problem of preserving battery performance regarding multitasking. Is iOS4's multitasking "feature" indeed more efficient regarding battery performance compared to Android? Have the Android developers managed to "do it right" too?

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• Mac OSX: Scroll half a page

  - by Eddy

  I am no longer using the trackpad on my macbook and using a separate wired apple keyboard instead. I miss the scrolling functionality on my trackpad, I'm having to make do with the keyboard (the mouse is too far away for efficient scrolling). Is there a way to map a key combination (such as cmd+pagedown) such that I scroll up/down half a page instead of a full page? Even better, is there a way to map key combinations to arbitrary scrolling distances? Thanks for your time

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