I understand that polling will inevitably have delays in getting real time updates. Currently I am using websync from frozen mountain dot com for achieving this and it works very well. But I would like to still know if PollingDuplexHttpBinding is a worthwhile one.
Has some one used this in critical systems?
Is its performance better over comet? When I say performance, how many simultaneous client connections it can handle?
Is it possible to configure the time interval of polling? I mean once in 30 seconds, 60 seconds etc.,
We're currently using this for our Alanta web conferencing platform. Our default binding is Net.TCP, because it's faster and more performant. But not everyone lets Net.TCP through on the right ports, so if we can't connect over Net.TCP, we fallback to the PollingDuplexHttpBinding. And it seems to work reasonably well -- no major complaints so far at least.
With respect to performance, the PollingDuplex binding is roughly similar to what you'll find in other long-poll based systems. You can find more details on its performance on Tomek's blog.
And yes, it's possible to configure almost every aspect of the binding. The particular properties that control the polling interval are ClientPollTimeout and ServerPollTimeout. See here for more details.
Related
I have a background in web programming where both the data and the code live on the server. Web hosts with mysql or the like are plentiful and cheap so using the application from multiple pcs was never a problem.
However I'm considering switching to building desktop applications but the only factor that annoys me is the syncing of data across the many pcs I use. I was thinking of perhaps setting up a light amazon ec2 instance with a postgresql on it and having my desktop applications use that.
I have a few questions:
I'm curious as to what latency I might expect by running the database on ec2 instead of the local network, any experience or insight is appreciated.
Are there better/more obvious/cheaper solutions?
I've looked at the pricing and it seems to come down to 24.48$ per month for a yearly contract. Whilst not really expensive, it is not exactly cheap either. At what point does it become more interesting to run a local server?
I'm obviously not using my applications for large parts of the day (sleep, work,...). I was wondering if I can have the amazon server go into a sort of "sleep" mode and wake up when poked. An initial delay for the first desktop application is acceptable. The reason behind this behavior would be to save money on the instance if it is only actually needed for 10% of the day.
I welcome any feedback at all on how this problem is best tackled.
This could get ugly. Every single query you do will have latency associated with it. If you have a lot of queries, this can add up very fast. So keep your query count low, and try to pre-fetch and cache data when possible.
Not enough information to answer that question.
Depends on the cost of your local server. Keep in mind that you will need to pay for electricity to keep it on.
You can stop your instance when you are not needing it, with the exception of high utilization reservations, you wont get billed when its in stopped state. With high utilization reservations you will still pay the full cost.
I want to scale an e-commerce portal based on LAMP. Recently we've seen huge traffic surge.
What would be steps (please mention in order) in scaling it:
Should I consider moving onto Amazon EC2 or similar? what could be potential problems in switching servers?
Do we need to redesign database? I read, Facebook switched to Cassandra from MySql. What kind of code changes are required if switched to Cassandra? Would Cassandra be better option than MySql?
Possibility of Hadoop, not even sure?
Any other things, which need to be thought of?
Found this post helpful. This blog has nice articles as well. What I want to know is list of steps I should consider in scaling this app.
First, I would suggest making sure every resource served by your server sets appropriate cache control headers. The goal is to make sure truly dynamic content gets served fresh every time and any stable or static content gets served from somebody else's cache as much as possible. Why deliver a product image to every AOL customer when you can deliver it to the first and let AOL deliver it to all the others?
If you currently run your webserver and dbms on the same box, you can look into moving the dbms onto a dedicated database server.
Once you have done the above, you need to start measuring the specifics. What resource will hit its capacity first?
For example, if the webserver is running at or near capacity while the database server sits mostly idle, it makes no sense to switch databases or to implement replication etc.
If the webserver sits mostly idle while the dbms chugs away constantly, it makes no sense to look into switching to a cluster of load-balanced webservers.
Take care of the simple things first.
If the dbms is the likely bottle-neck, make sure your database has the right indexes so that it gets fast access times during lookup and doesn't waste unnecessary time during updates. Make sure the dbms logs to a different physical medium from the tables themselves. Make sure the application isn't issuing any wasteful queries etc. Make sure you do not run any expensive analytical queries against your transactional database.
If the webserver is the likely bottle-neck, profile it to see where it spends most of its time and reduce the work by changing your application or implementing new caching strategies etc. Make sure you are not doing anything that will prevent you from moving from a single server to multiple servers with a load balancer.
If you have taken care of the above, you will be much better prepared for making the move to multiple webservers or database servers. You will be much better informed for deciding whether to scale your database with replication or to switch to a completely different data model etc.
1) First thing - measure how many requests per second can serve you most-visited pages. For well-written PHP sites on average hardware it must be in 200-400 requests per second range. If you are not there - you have to optimize the code by reducing number of database requests, caching rarely changed data in memcached/shared memory, using PHP accelerator. If you are at some 10-20 requests per second, you need to get rid of your bulky framework.
2) Second - if you are still on Apache2, you have to switch to lighthttpd or nginx+apache2. Personally, I like the second option.
3) Then you move all your static data to separate server or CDN. Make sure it is served with "expires" headers, at least 24 hours.
4) Only after all these things you might start thinking about going to EC2/Hadoop, build multiple servers and balancing the load (nginx would also help you there)
After steps 1-3 you should be able to serve some 10'000'000 hits per day easily.
If you need just 1.5-3 times more, I would go for single more powerfull server (8-16 cores, lots of RAM for caching & database).
With step 4 and multiple servers you are on your way to 0.1-1billion hits per day (but for significantly larger hardware & support expenses).
Find out where issues are happening (or are likely to happen if you don't have them now). Knowing what is your biggest resource usage is important when evaluating any solution. Stick to solutions that will give you the biggest improvement.
Consider:
- higher than needed bandwidth use x user is something you want to address regardless of moving to ec2. It will cost you money either way, so its worth a shot at looking at things like this: http://developer.yahoo.com/yslow/
- don't invest into changing databases if that's a non issue. Find out first if that's really the problem, and even if you are having issues with the database it might be a code issue i.e. hitting the database lots of times per request.
- unless we are talking about v. big numbers, you shouldn't have high cpu usage issues, if you do find out where they are happening / optimization is worth it where specific code has a high impact in your overall resource usage.
- after making sure the above is reasonable, you might get big improvements with caching. In bandwith (making sure browsers/proxy can play their part on caching), local resources usage (avoiding re-processing/re-retrieving the same info all the time).
I'm not saying you should go all out with the above, just enough to make sure you won't get the same issues elsewhere in v. few months. Also enough to find out where are your biggest gains, and if you will get enough value from any scaling options. This will also allow you to come back and ask questions about specific problems, and how these scaling options relate to those.
You should prepare by choosing a flexible framework and be sure things are going to change along the way. In some situations it's difficult to predict your user's behavior.
If you have seen an explosion of traffic recently, analyze what are the slowest pages.
You can move to cloud, but EC2 is not the best performing one. Again, be sure there's no other optimization you can do.
Database might be redesigned, but I doubt all of it. Again, see the problem points.
Both Hadoop and Cassandra are pretty nifty, but they might be overkill.
I have a C# winform application. it has many forms with different functionalities. These forms wrap to a WCF service. for example
form1 calls serviceMethod1 continuously and updates the results
form2 calls serviceMethod2 continuously and updates the results
The calls are made in a different thread per each form, but this is ending up with too many threads as we have many forms. Is this bad and why? and is there a way to avoid this given my scenario?
Regards
How many threads are you talking about? If you have a lot of threads, you'll lose a bit of performance due to context switching - but in practice I wouldn't expect this to become a significant problem until you have an awful lot of them.
One alternative would be to use a Timer though (it sounds like a System.Timers.Timer or System.Threading.Timer would be most appropriate) - schedule each service call to be made on a regular basis, and the timer will use the threadpool to fire the calls. I suspect that although you say you're calling the services "continuously" you actually mean you're doing it regularly - which is exactly the kind of situation a timer is good for.
To answer the question frankly: It depends entirely on the OS and app design, but this question may indicate a shortcoming in the program's design.
Detail:
You want to learn the allocation requirements of a thread on your target architecture/OS, as well as keep your threads relatively busy/avoid polling, and to configure priorities correctly if you really do have a lot of threads. 'Many' threads may be 8 (or fewer, if busy), or 100+ if they have relatively little work to do, it ultimately depends on your needs and design.
As tests for some tests/objects/operations, I have used more than 100, and occasionally more than 1000 working threads. No explosions happened, though I have never had a true need for those operations to be that parallel in a shipping app (unless the aforementioned programs are being used in very unusual circumstances), and it made more sense to put the actual implementation into some centralized task manager. If you have time-critical/real time applications, then these tasks may be best on another thread. If they are short lived, consider a thread pool.. well, there are many ways to attack many problem classes...
You can use WCF asynchronious proxy
In Visual Studio, when you add Web Reference you can check "Generate Asynchronous operations" to generate an asynchronious proxy.
While the threads spend most of their time waiting for server response - even hundreds of threads are unlikely to degrade performance (CPU-wise). Otherwise, use thread pool and queue "request and update form once" tasks when previous update completes.
More important problem might be loading service with too many simultaneous requests.
As a general rule, you won't gain anything by having more threads than you have CPU cores. There are exceptions to the general rule, but I doubt they apply to your case.
From the OS' point of view, threads are no longer the lightweight things they used to be, but are almost as costly as full processes. Implementing thread synchronization correctly is not a simple task, debugging multi-threaded applications is a lot harder than a single threaded one.
With green threads, it is not an issue. Green threads being sort of a virtual thread, which is what you will generally get with Java and C#.
The benefit of threads in many apps is not to crunch more numbers but to allow lots of things to go on at once with good responsiveness, so having a lot of threads can be very useful for some things and will not always have any real cost.
Our tests showed that the polling duplex binding simply does not scale and can not be used on a service within a web-farm or even a web garden. We have looked at TCP/IP sockets for a client push method, but the firewall issue is does allow us to use sockets.
I was wondering what is the alternative "free" solution to this problem? allowing us to scale and allowing us to push data to client...
I have also tried the solution in this article http://tomasz.janczuk.org/2009/09/scale-out-of-silverlight-http-polling.html but at the end, there was too much polling on a database, and performance was affected.
Our Silverlight application need a pub/sub design, but it needs to be reliable and scalable... any ideas?
I heard about lightstreamer, which scales very well , but I´m not shure about license fees
Also have a look at this intresting conversation at silverlight.net
Check out WebSync, it's a full comet server built for .NET. It handles server farms, and over 30,000 simultaneous users per server on commodity hardware (3 gig ram, cheap AMD 3 core processor). It's not free, but it's a great solution. There's even an example running silverlight here.
Note: This is not for unit testing or integration testing. This is for when the application is running.
I am working on a system which communicates to multiple back end systems, which can be grouped into three types
Relational database
SOAP or WCF service
File system (network share)
Due to the environment this will run in, there are no guarantees that any of those will be available at run time. In fact some of them seem pretty brittle and go down multiple times a day :(
The thinking is to have a small bit of test code which runs before the actual code. If there is a problem then persist the request and poll until the target system until it is available. Tests could possibly be rerun within the code to check it is still available at logical points. The ultimate goal is to have a very stable system, regardless of the stability (or lack thereof) of the systems it communicates to.
My questions around this design are:
Are there major issues with it? (small things like the fact it may fail between the test completing and the code running are understandable)
Are there better ways to implement this sort of design?
Would using traditional exception handling and/or transactions be better?
Updates
The system needs to talk to the back end systems in a coordinated way.
The system is very async in nature so using things like queuing technologies is fine.
The system must run even if one or more backend systems are down as others may be up and processing of some information is possible.
You will be needing that traditional exception handling no matter what, since as you point out there's always the chance that things'll fail between your last check and the actual request. So I really think any solution you find should try to interact smoothly with this.
You are not stating if these flaky resources need to interact in some kind of coordinated manner, which would indicate that you should probably be using a transaction manager of some sort to do this. I do not believe you want to get into the footwork of transaction management in application code for most needs.
Sometimes I have also seen people use AOP to encapsulate retry logic to back-end systems that fail (for instance due to time-out issues). Used sparingly this may be a decent solution.
In some cases you can also use message queuing technology to alleviate unstable back-ends. You could for instance commit to a message queue as part of a transaction, and only pop off the queue when successful. But this design is normally only possible when you're able to live with an asynchronous process.
And as always, real stability can only be achieved by attacking the root cause of the problem. I had a 25-year old bug fixed in a mainframe TCP/IP stack fixed because we were overrunning it, so it is possible.
The Microsoft Smartclient framework provides a ConnectionMonitor class. Should be easy to use or duplicate.
Our approach to this kind of issue was to run a really basic 'sanity tester' prior to bringing up our main application. This was thick client so we could run the test every time the app started. This sanity test would go out and check things like database availability, and external network (extranet) access, and it could have been extended to do webservices as well.
If there was a failure, the user was informed, and crucially an email was also sent to the support/dev team. These emails soon became unweildy as so many were being created, but we then setup filters, so we knew when somethings really bad was happening. Overall the approach worked pretty well, our biggest win was being able to tell users that the system was down, before they had entered data, and got part way through a long winded process. They absolutely loved it.
At a technica level the sanity was written in C#, it used exception handling in a conventional way not to find the problems it was looking for. The sanity program became a mini app in its own right, and it was standalone from the main app. If I were doing it again I'd using a logging framework to capture issues, which is more flexible then our hard coded approach.