ActiveMq v 5.5 comes with default message storage configured as KahaDB. Does anyone use it in enterprise level solutions? Should it be replaced with MSSQL instead? And what benefits can each of them have?
The persistence mechanism should be based on your application's needs. A closely related concern is going to be failover/availability.
Speaking purely of the speed of message persistence, KahaDB is going to be the fastest; it's tuned specifically for patterns surrounding messaging (writing/reading/discarding). Were you to use something like MSSQL, even with journaling enabled, you're going to give up orders of magnitude (in mgs/sec) in efficiency. This setup works well if you are concerned with publishing high volumes of messages and are willing to leave message recovery up to an admin or some "invented-here" process.
So, why would you choose a different persistence mechanism? High availability.
Re: something like a relational database, it's probably something already available in your enterprise, meaning someone's (hopefully) gone through the effort of clustering and testing disaster recovery. This means you should be able to have a master/slave setup and your messages will be recoverable if a master were to go down. The slave will detect a loss of lock and start using the exact same message store. This setup is ideal if your performance threshold is much lower but you are extremely concerned about up-time and ensuring that you can always publish/subscribe messages.
Regardless, in a well-tuned system, we are talking >= hundreds msgs/sec so performance considerations are likely not going to be your first concern. Should performance really be that crucial, I'd consider looking at something like RabbitMQ, which definitely lends itself well to being extremely efficient at the cost of making high availability more complex to set up.
Here's a discussion on some of the failover options with ActiveMQ. I've settled on using a shared file master/slave setup with a KahaDB being shared on a SAN. Seems to be a nice middle-ground solution.
Related
FastCGI is old but it still seems like it must be the right answer in some cases.
It seems like the preferred deployment of Perl/Catalyst web applications is with FastCGI.
FastCGI was popular with Rails but seems to no longer be. (Why?)
The Java world doesn't seem to have anything to do with FastCGI. Is something like Tomcat way better than Apache+FastCGI?
Is choosing FastCGI still a good idea or just a lingering technology?
Ted
Since it depends a lot on your setup and requirements, I'll let the "Is X still a right answer?" up to you. However, by looking at different architectures, you can come up with a list of questions to ask to determine if it still is a right answer given specific circumstances.
Concerns of frequent interest
The questions you'll want to ask are usually related to security and flexibility. For security, you'll want to follow the principle of least privilege. For flexibility, you'll want to know if you can run multiple frameworks, multiple versions of the framework and how easily you can delegate work to other tasks.
Other concerns
For a simple web front-end to a database-backed application, not all of these questions are important. You also need to keep in mind that some of the recommendations have nothing to do with what's outlined here. Many web frameworks will recommend whatever architecture is easiest to setup with their framework. They do this because it helps get new users trying out the framework with minimal fuss and without flooding the mailing list. Also, the Java community tends to stick to a common denominator rather than take full advantage of the platform at hand, so they'll often recommend an all-Java solution.
Popular architectures
Single process architectures
From a pure performance point of view, a single process (probably threaded) with an embedded framework probably gives most performance as it reduces most communication overhead between whatever receives the request and whatever produces a response.
Security: a single process must have all of the permissions required to perform every single task it is handed. In simple applications, this might not be a problem. However, its possible you might serve multiple services
Flexibility: probably can't run multiple version of the same framework (e.g. code for different parts of your website require different versions of Java, Rails, Python, etc.). Moreover, changing your setup to serve some work on different machines becomes painful (less difficult when split up on virtual hosts).
Sub-process based architectures
Under the CGI model, you have to pay the price of spawning a new process for each request. Even on UNIX machines where spawning a process is considered cheap, 600 requests a second will kill your server if you spawn a process for each.
Security: to spawn child processes under different user accounts, your gateway probably runs under quite high privileges.
Flexibility: additional flexibility for the multiple frameworks, multiple versions, multiple languages approach, but you're still stuck on the same machine.
Distributed architectures
The FastCGI/SCGI approach tried to solve the CGI process management problem in a clean way. Just keep the process alive. Have the gateway talk to that process to serve the request.
Security: Because the gateway doesn't spawn the processes that serve requests, the gateway can run with far less privileges enabled. Actually, if it only serves as a gateway and doesn't do any work itself, it can run with hardly any privileges at all.
Flexibility: you get even better flexibility than the CGI model because you can forward the request to any machine on the network.
Conclusion
I like FastCGI, because it gives me high flexibility at a price (i.e. request forwarded through socket) I can afford to pay. It's not my full time job to administer systems. I don't develop all the apps I hosts. This means I look for the easiest solution for hosting whatever I try to host. FastCGI popular enough to be supported by major web servers and popular web frameworks. Adding another app usually just boils down to installing and mapping the desired URL to the application over FastCGI.
How can i write a cloud-aware application? e.g. an application that takes benefit of being deployed on cloud. Is it same as an application that runs or a vps/dedicated server? if not then what are the differences? are there any design changes? What are the procedures that i need to take if i am to migrate an application to cloud-aware?
Also i am about to implement a web application idea which would need features like security, performance, caching, and more importantly free. I have been comparing some frameworks and found that django has least RAM/CPU usage and works great in prefork+threaded mode, but i have also read that django based sites stop to respond with huge load of connections. Other frameworks that i have seen/know are Zend, CakePHP, Lithium/Cake3, CodeIgnitor, Symfony, Ruby on Rails....
So i would leave this to your opinion as well, suggest me a good free framework based on my needs.
Finally thanks for reading the essay ;)
I feel a matrix moment coming on... "what is the cloud? The cloud is all around us, a prison for your program..." (what? the FAQ said bring your sense of humour...)
Ok so seriously, what is the cloud? It depends on the implementation but usual features include scalable computing resource and a charge per cpu-hour, storage area etc. So yes, it is a bit like developing on your VPS/a normal server.
As I understand it, Google App Engine allows you to consume as much as you want. The back-end resource management is done by Google and billed to you and you pay for what you use. I believe there's even a free threshold.
Amazon EC2 exposes an API that actually allows you to add virtual machine instances (someone correct me please if I'm wrong) having pre-configured them, deploy another instance of your web app, talk between private IP ranges if you wish (slicehost definitely allow this). As such, EC2 can allow you to act like a giant load balancer on the front-end passing work off to a whole number of VMs on the back end, or expose all that publicly, take your pick. I'm not sure on the exact detail because I didn't build the system but that's how I understand it.
I have a feeling (but I know least about Azure) that on Azure, resource management is done automatically, for you, by Microsoft, based on what your app uses.
So, in summary, the cloud is different things depending on which particular cloud you choose. EC2 seems to expose an API for managing resource, GAE and Azure appear to be environments which grow and shrink in the background based on your use.
Note: I am aware there are certain constraints developing in GAE, particularly with Java. In a minute, I'll edit in another thread where someone made an excellent comment on one of my posts to this effect.
Edit as promised, see this thread: Cloud Agnostic Architecture?
As for a choice of framework, it really doesn't matter as far as I'm concerned. If you are planning on deploying to one of these platforms you might want to check framework/language availability. I personally have just started Django and love it, having learnt python a while ago, so, in my totally unbiased opinion, use Django. Other developers will probably recommend other things, based on their preferences. What do you know? What are you most comfortable with? What do you like the most? I'd go with that. I chose Django purely because I'm not such a big fan of PHP, I like Python and I was comfortable with the framework when I initially played around with it.
Edit: So how do you write cloud-aware code? You design your software in such a way it fits on one of these architectures. Again, see the cloud-agnostic thread for some really good discussion on ways of doing this. For example, you might talk to some services on GAE which scale. That they are on GAE (example) doesn't really matter, you use loose coupling ideas. In essence, this is just a step up from the web service idea.
Also, another feature of the cloud I forgot to mention is the idea of CDN's being provided for you - some cloud implementations might move your data around the globe to make it more efficient to serve, or just because that's where they've got space. If that's an issue, don't use the cloud.
I cannot answer your question - I'm not experienced in such projects - but I can tell you one thing... both CakePHP and CodeIgniter are designed for PHP4 - in other words: for really old technology. And it seems nothing is going to change in their case. Symfony (especially 2.0 version which is still in heavy beta) is worth considering, but as I said on the very beginning - I can not support this with my own experience.
For designing applications for deployment for the cloud, the main thing to consider if recoverability. If your server is terminated, you may lose all of your data. If you're deploying on Amazon, I'd recommend putting all data that you need persisted onto an Elastic Block Storage (EBS) device. This would be data like user generated content/files, the database files and logs. I also use the EBS snapshot on a 5 day rotation so that's backed up itself. That said, I've had a cloud server up on AWS for over a year without any issues.
As for frameworks, I'm giving Grails a try at the minute and I'm quite enjoying it. Built to be syntactically similar to Rails but runs on the JVM. It means you can take advantage of all the Java goodness, like threading, concurrency and all the great libraries out there to build your web application.
I am a bit confused about this. If you're building a distributed application, which in some cases may perform parallel operations (although not necessarily mathematical), should you use ASIO or something like MPI? I take it MPI is a higher level than ASIO, but it's not clear where in the stack one would begin.
I know nothing about ASIO but from a quick Google it looks to me to be a lot lower level than MPI. For me the whole point of MPI is so that I can program against a higher level of abstraction from the messaging than, it seems, ASIO provides. Where you begin depends on your needs. For mine, parallelising scientific codes for high-performance, the obvious answer is MPI. I'm not sure I'd use it, or at least not sure it would be my default choice, if I were writing more general-purpose distributed, as opposed to parallel, applications. Well, actually, it probably would be my default choice to avoid learning another approach (most of which are less portable and less long-lived than MPI) but I'll admit it might not be the best choice if starting from an equal footing.
As far as I know MPI is currently incapable of handling the situation, when the new distributed nodes want to join the already started group. The problems also may occur if one of the nodes goes offline.
MPI does not reveal any network related machinery that is underneath. Thus if you would ever need something on the lower level -- you're in trouble. If you on the other hand do not aticipate such a need, then you'll save yourself a lot of time using MPI.
I've heard that people say that they've made a scalable web application..
What really is scaling?
What can be done by developers to make their application scalable?
What are the factors that are looked after by developers during scaling?
Any tips and tricks about scaling web applications with asp.net and sql server...
What really is scaling?
Scaling is the increasing in capacity and/or usage of your application.
What do developers do to make their application scalable?
Either allow their applications to scale vertically or horizontally.
Horizontal scaling is about doing things in parallel.
Vertical scaling is about doing things faster. This typically means more powerful hardware.
Often when people talk about horizontal scalability the ideal is to have (near-)linear scalability. This means that if one $5k production box can handle 2,000 concurrent users then adding 4 more should handle 10,000 concurrent users. The closer it is to that figure the better.
The ideal for highly scalable apps is to have near-limitless near-linear horizontal scalability such that you can just plug in another box and your capacity increases by an expected amount with little or no diminishing returns.
Ideally redundancy is part of the equation too but that's typically a separate issue.
The poster child for this kind of scalability is, of course, Google.
What are the factors that are looked after by developers during scaling?
How much scale should be planned for? There's no point spending time and money on a problem you'll never have;
Is it possible and/or economical to scale vertically? This is the preferred option as it is typically much, much cheaper (in the short term);
Is it worth the (often significant) cost to enable your application to scale horizontally? Distributed/multithreaded apps are significantly more difficult and expensive to write.
Any tips and tricks about scaling web applications...
Yes:
Don't worry about problems you'll never have;
Don't worry much about problems you're unlikely to have. Chances are things will have changed long before you have them;
Don't be afraid to throw away code and start again. Having automated tests makes this far easier; and
Think in terms of developer time being expensive.
(4) is a key point. You might have a poorly written app that will require $20,000 of hardware to essentially fix. Nowadays $20,000 buys a lot of power (64+GB of RAM, 4 quad core CPUs, etc), probably more than 99% of people will ever need. Is it cheaper just to do that or spend 6 months rewriting and debugging a new app to make it faster?
It's easily the first option.
So I'll add another item to my list: be pragmatic.
My 2c definition of "scalable" is a system whose throughput grows linearly (or at least predictably) with resources. Add a machine and get 2x throughput. Add another machine and get 3x throughput. Or, move from a 2p machine to a 4p machine, and get 2x throughput.
It rarely works linearly, but a well-designed system can approach linear scalability. Add $1 of HW and get 1 unit worth of additional performance.
This is important in web apps because the potential user base is ~1b people.
Contention for resources within the app, when it is subjected to many concurrent requests, is what causes scalability to suffer. The end result of such a system is that no matter how much hardware you use, you cannot get it to deliver more throughput. It "tops out". The HW-cost versus performance curve goes asymptotic.
For example, if there's a single app-wide in-memory structure that needs to be updated for each web transaction or interaction, that structure will become a bottleneck, and will limit scalability of the app. Adding more CPUs or more memory or (maybe) more machines won't help increase throughput - you will still have requests lining up to lock that structure.
Often in a transactional app, the bottleneck is the database, or a particular table in the database.
What really is scaling?
Scaling means accommodating increases in usage and data volume, and ideally the implementation should be maintainable.
What developers do to make their application scalable?
Use a database, but cache as much as possible while accommodating user experience (possibly in the session).
Any tips and tricks about scaling web applications...
There are lots, but it depends on the implementation. What programming language(s), what database, etc. The question needs to be refined.
Scalable means that your app is prepared for (and capable of handling) future growth. It can handle higher traffic, more activity, etc. Making your site more scalable can entail various things. You may work on storing more in cache, rather than querying the database(s) unnecessarily. It may entail writing better queries, to keep connections to a minimum, and resources freed up.
Resources:
Seattle Conference on Scalability (Video)
Improving .NET Application Performance and Scalability (Video)
Writing Scalable Applications with PHP
Scalability, on Wikipedia
Books have been written on this topic. An excellent one which targets internet applications but describes principles and practices that can be applied in any development effort is Scalable Internet Architectures
May I suggest a "User-Centric" definition;
Scalable applications provide a consistent level of experience to each user irrespective of the number of users.
For web applications this means 24/7 anywhere in the world. However, given the diversity of the available bandwidth around the world and developer's lack of control over its performance and availability, we may re-define it as follows:
Scalable web applications provide a consistent response time, measured at the server TCP port in use, irrespective of the number of requests.
To achieve this the developer must avoid or remove all performance bottle-necks. Currently the most challenging issue is the scalability of distributed RDBMS systems.
Other than the monetary aspects, how different is Amazon's SimpleDB from Apache's CouchDB in the following terms
Interfacing with programming languages like Java, C++ etc
Performance and Scalability
Installation and maintenance
I'm a fairly heavy SimpleDB user (I'm the developer of http://www.backupsdb.com/) but am currently migrating some projects off SimpleDB and into Couch, so I guess I can see this from both sides now.
1. Interfacing with programming languages like Java, C++ etc
Easier with Couch as you can talk to it very easily using JSON. SimpleDB is a bit more work, largely due to the complexities of signing each request for security and the lower level access you get which requires you to implement exponential back off in the case of busy signals etc. You can get good libraries for SimpleDB though in many languages now and this takes the pain away in many respects.
2. Performance and Scalability
I don't have any benchmarks, but for my own use case, CouchDB outperforms SimpleDB. It's harder to scale though - SimpleDB is great at that, you chuck more at it and it autoscales around you.
There are lots of occasionally irritating limits in SimpleDB though, limits on the number of attributes, size of attributes, number of domains etc. The main annoyance for many applications is the attribute size limit which means you can't store large forum posts for example. The workaround is to offload those into something else such as S3, but it's a bit annoying at times. Obviously CouchDB doesn't have that issue and indeed the fact that you can attach large files to documents is one thing that particularly attracts me to it.
Scaling wise, you should also possibly be looking at bigcouch which gives you a distributed cluster and is closer to what you get with SDB.
3. Installation and Maintenance
I actually found it much easier with CouchDB. I suspect it depends on which library you need to use for SimpleDB, but when I was starting with it, the Amazon supplied libraries weren't very mature and the open source community ones had various issues that meant getting up and running and doing something serious with it took more time than I would have liked. I suspect this is much better now.
CouchDB was surprisingly easy to install and I love the web interface to it. Indeed that would be my major criticism of SimpleDB - Amazon still don't have any form of web console for it despite having web consoles for almost every other service. That's why we wrote the very basic BackupSDB just so we could extract data in XML and run queries from a web browser, I'd like to have seen Amazon do something similar (but more powerful and better) by now and have been very surprised that they haven't. There are lots of third party firefox plugins and some applications for it though but I have the impression that SimpleDB isn't that widely used - this is only a hunch really.
4. Other Observations
The biggest issue I think is that with SimpleDB you are entrusting all your data to a third party with no easy way of getting it out (you'll need to write something to do that), plus your costs keep gently rising. When you get to the point that the cost is comparable to a powerful dedicated database server, you kind of feel you'd get better value that way, but the migration headache is non trivial by this point as you'll have a large commitment to the cloud.
I started off as a huge Amazon evangelist, and for most things I still am, but when it comes to SDB, I feel it's a bit of a hobby project for Amazon the way the Apple TV was for Steve jobs.