I’m very black and white when it comes to buying things and doing personal shopping. I almost take it to the extreme: a £20 t-shirt should be twice as good as a £10 t-shirt with regards to build quality. If it is not twice as good I’m paying for the brand. The trouble with the brand is that it is only perceived value. Perceived value is not the same as actual value and in reality bares no relationship to build quality.
I had a girlfriend a while back who spent an awful lot of money on shoes, bags and clothes. It was a constant bone of contention that a Gucci hand bag that cost £500 cost that much because it was made from quality components. Whereas a similar looking bag made by an independent was cheaper because it was made with sub-standard materials. “You’re paying for the quality” she kept saying. Amazing, such is the power of marketing!
While there may be other things that effect the price, such as after sales support, the majority of the cost comes from the perception that if it is expensive then only a select few will be able to afford them and so with that comes exclusivity. There is no way that a pair of Emporio Armani jeans are 5 times as good as a pair of Levi jeans even though their price tag is five times more. So what am I paying for? It costs a lot of money to advertise in exclusive magazines and even more to advertise on television. I expect it costs quite a bit to push their wears on celerities and sponsorship. But none of these expenses have anything to do with the actual product. I don’t expect these companies are pouring money into R & D to design the latest bags; market research isn’t that expensive and because it’s fashion, what ever they say the latest fashion is - then that’s what it is. So no money spent there either.
Maybe I’m taking a simplistic view on this, but is that just it. Is everyone being duped in to paying twice the price for nothing?
Edgar Watson Howe:
One of the most difficult things in the world is to convince a woman that even a bargain costs money.
I ended up with a house full of things I didn’t need or want that my girlfriend had bought because they were cheap. For some reason I couldn’t convince her that just because they had knocked 50% off the price didn’t mean that it was a bargain. It only became a bargain if we needed it and more often than not it was just used as ammo for her argument about buying a bigger house!
One of my current projects requires me to use Sentinel RMS within a Microsoft .NET framework using C#.
I had a couple of problems setting up the example solutions SafeNet gave out, so I thought I’d document them here. There’s probably not that many people who will use Sentinel RMS but I did run into a problem that might well be generally useful:
API call fail with message:System.BadImageFormatException: An attempt was made to load a program with an incorrect format. (Exception from HRESULT: 0x8007000
API call fail with error-code:501
While the manual for Sentinel RMS was pretty good it was all about the API’s and how to call them. The documentation was missing a How to get started section that would describe how to set up Visual Studio. There is a brief few lines saying which version of Visual Studio are supported but that’s about it.
- Download SDK RMS 8.5.0 Windows 32 and 64-bit GA release (you can get this from your support representative)
- Download the Sentinel RMS 8.4.1 .Net Interface (you can get this from your support representative)
- Unpack and install the SDK.
- Add the following DLL folder to your PATH:
C:\Program Files (x86)\SafeNet Sentinel\Sentinel RMS Development Kit\8.5\English\MsvcDev\Lib\MSVS2008\Win32\DLL\
- Unpack the .Net Interface.
- Navigate to
RMS 8.4.1 .NET Interface\Examples
- Create a folder called
- Copy the contents of
RMS 8.4.1 .NET Interface\Libraryinto the
RMS 8.4.1 .NET Interface\Examples\Librariesfolder
- Navigate to
RMS 8.4.1 .NET Interface\Examples\VisualC#\AddRemoveLicense
- Double click the solution file (.sln) to launch Visual Studio. The documentation says that only Microsoft Visual Studio 2003/2005/2008 is supported so make sure its one of those.
- When the solution loads in, right-click on the project name and select Properties.
- Under the Application tab change the Target Framework to 3.5.
- Under the Build tab change the Platform Target to x86.
- Then save, clean solution, rebuild solution and run.
I found that if you didn’t add the DLL folder to the
PATH then I got the following error message, and in order to fix it I had to manually copy the lsapiw32.dll into the Release/Debug folder. There didn’t seem to be anywhere in visual studio that let you add extra DLL search folders because it is rubbish.
API call fail with message:System.DllNotFoundException: Unable to load DLL ‘lsapiw32.dll’: The specified module could not be found. (Exception from HRESULT: 0x8007007E)
API call fail with error-code:501
The other problem, which is probably more generally useful, was that of the System.BadImageFormatException exception. This occurs when the Common Language Runtime (CLR) tries to load an assembly that contains unmanaged code built targeting a different platform (thanks Dave).
In my case with Sentinal, the
lsapiw32.dll was compiled with the platform x86 for the 32-bit version of the DLL. Visual Studio defaults to building for a target platform of Any and this discrepancy is what causes the error. Equally if I had chosen to fill the
Libraries folder with DLLs from the
Library(x64) folder (and the corresponding
C:\Program Files (x86)\SafeNet Sentinel\Sentinel RMS Development Kit\8.5\English\MsvcDev\Lib\MSVS2008\Win64\DLL) instead then I would have had exactly the same problem.
We have written a video transcoding application which sits under a RESTful front end provided by IIS. The transcoding application is CPU bound, that is, the CPU is the first place to bottleneck and prevent the computer from doing more work. The heavy CPU is caused by video transcoding. This involves reading a unit of video from a video server, converting it to another format and squirting it out to a client. Transcoding video is a pipeline process which means there are huge performance advantages in processing a series of consecutive video units in a read-ahead fashion.
A normal web server could handle 2 or 3 orders of magnitude more requests than ours. As a result we found that it was more difficult to load balance across an NLB cluster because the number of new incoming connections was relatively small.
The application suite has been designed to be stateless in order to allow it to fit into a cluster architecture. We want to be able to scale outward more easily so in order to support more clients we can just add more boxes.
Our experiments have shown that 1 PC can support about 10 simultaneous clients before the system’s performance degrades to unusable levels. For each new PC we add to the cluster, we can get another 8-10 clients.
We would like to keep each client talking to the same cluster node for a short period so that we can get the benefit of pipe-lining requests, while at the same time we need to make sure that clients can move between cluster nodes in order to keep the load evenly balanced across the cluster.
Under IIS, HTTP KeepAlive allows a client to connect once, then make as many requests down the connection pipe as it likes before the client closes the connection. The server will hang on to each client until they go away. If KeepAlive is switched off the connection will be closed at the end of each request which may add significant overheads to dealing with clients that a geologically distant. HTTP KeepAlive works on layer 5 of the OSI model.
NLB has a similar option called Affinity. The Affinity can be either sticky or non-sticky (there are other states but for the purposes of this article they can all be condensed into these two). Stickiness ensures that the same client is always directed to the same cluster node. NLB works on layer 4 of the OSI model.
The simplest solution is to switch NLB Affinity to non-sticky and set HTTP KeepAlive to false. Each incoming request that arrives at the cluster will be directed to a choice of machines, make its request, get the data and then tear down everything and start again for the next request. With this set up we will not be able to take any advantage of the pipe-lining efficiency that could be had and as a result the platform will be able to support fewer clients overall.
Each one of these technologies has advantages and disadvantages. The advantage of using stickiness with NLB is that you can ensure that all requests for a client, for the lifetime of the client or that cluster node will be directed to the same place. That will be good for pipe-lining but bad for load balancing. The advantages and disadvantages for HTTP KeepAlive are similar except here you are at the mercy of what the client decides to do.
In experiments we have shown that if one of the nodes in the cluster goes down the NLB will notice and rebalance; diverting incoming traffic to another node in the cluster. The HTTP KeepAlive clients will simply reconnect to the next allocated node in the cluster and stay there for the rest of their lives. This means that when a downed node comes back up, it balances with the rest of the cluster to make sure the request distribution is correct. NLB will not sever existing connections so all the existing clients will stay where they are. Only new incoming connections will be allocated to the newly added cluster node. So what we find is that after a cluster node failure the rest of the nodes take up the slack and end up working extra hard, but when the failed node re-enters the cluster it sits there doing nothing.
If you were dealing with thousands of small requests it would be a different story; it probably wouldn’t matter so much because new clients are coming and going all the time.
What we need is a combination of KeepAlive and not KeepAlive on a non-sticky platform. Apache has a configuration option called MaxKeepAliveRequests. This option severs the connection to the client after this many requests (the default is 100). With this option we can have 100 consecutive requests over the same connection to enjoy the benefits of pipe-lining the requests and yet we are giving the system/platform a chance to balance itself on a regular basis.
IIS has no concept of limiting the number of requests a connection can service, which probably goes some way to explaining why IIS only has 15.73% of the web server market. I posted a question on ServerFault but didn’t get a satisfactory response. The one reply I did get was from some one saying that if my application was truly stateless I needed to switch off KeepAlive altogether and take the penalty for the re-connection. While the application is stateless there are advantages to be had from batching requests together. An answer of it can’t be done or is not supported is, in my opinion not an answer. What they actually mean is that it is not supported yet. In I.T. almost everything *is* possible as long as you know what to do.
IIS7 has a new pipeline module architecture that allows you to inject code into the processing of a request at any one of about 12 different stages. The run line passes through each module at each requested stage in order to modify the request’s response.
When the module is loaded in, it reads the MaxKeepAliveRequests number from the
web.config. For each request that comes in the module will remember the remote host, remote port and how many requests have been serviced by that combination. When the request is in its final stage we’ll check to see if the number of serviced requests is bigger than MaxKeepAliveRequests. If it is then we can inject a Connection: close into the response. This will make its way through IIS, safely closing the connection on it’s way out.
Surprisingly there was a great deal of confusion on MSDN documentation, blogs and forums surrounding how to force a close after a request. I found that
HttpResponse.Close() can chop the end off the reply,
HttpApplication.CompleteRequest() didn’t work because the request’s run line was already inside the
EndRequest section of the pipeline. So I went back to the specification and in RFC2616: Section 8 - Connections it talks about injecting Connection: close into the response header so that after the response is sent out the server closes the connection. The closure forces the client to reconnect. I tried this using a telnet client (and not a web browser) and can reveal that it is the server that closes the connection and not the client deciding.
I had thought about using the Session to store the request count but I didn’t think it would help. If a proxy server is talking to your cluster then it may be interleaving requests from several sources with different session identifiers. We are interested in the transport layer, and not the session layer. We must use values from the transport layer to differentiate the clients in order to spread the load.
Simply compile up this C# and add it to your IIS integrated process pipe line.
You’ll need to add the configuration option to the
While B2Evolution’s search and back office interfaces are excellent they cater for the general use case. Search is a good example of this as there are many things to search for but a limited amount of search criteria in the interface. There are also tasks you might want to perform that would normally mean spending hours going through the web interface.
SQL is the way to go. It allows you to update your blogs structure underneath in a couple of well crafted statements. So I thought I’d share them with you.
Deleting a category with many dependencies
I came across a problem with deleting categories. If there are lots of posts using the category you want to delete, then you have to go into each post by hand and change the dependency on the category.
Finding articles without any tags
I wrote a related article plug-in that relies on tags so I wanted to find out which of my live blog articles don’t have enough tags. This piece of SQL gives you a list of blog article titles followed by the number of tags that are associated with each article. I have added a filter to ignore articles that have more than a set number of tags.
SELECT @mintags := 2;
SELECT post_ID, post_title, count(itag_tag_ID) ntags FROM evo_items__item
LEFT JOIN evo_items__itemtag ON itag_itm_ID = post_ID
WHERE post_status = ‘published’
GROUP BY post_ID
HAVING ntags < @mintags
You can pull out the post_id and use it in this SQL that displays the full set of tags for an article.
SELECT @postid := 30;
SELECT itag_itm_ID, tag_name
FROM evo_items__itemtag, evo_items__tag
WHERE itag_itm_ID = @postid
AND itag_tag_ID = tag_id
Viewing comments and deleting spam
SELECT comment_ID, comment_date, comment_author, comment_author_IP, SUBSTRING(TRIM(comment_content),1,150)
ORDER BY comment_author_IP
Then delete them all:
DELETE FROM evo_comments
Or delete by IP address:
DELETE FROM evo_comments
AND comment_author_IP IN (’xxx,xxx,xxx,xxx’, ‘yyy,yyy,yyy,yyy’)