I asked this on HN but didn't get much advice.
I'm a n00b in web app development. Nevertheless, I've been working on an app (in Ruby on Rails + deployed with Heroku) that has gotten some really positive feedback, so I'd like to dedicated more resources to it.
However, I'm not a sysadmin or anything of the sort, so I'm unsure as to what steps to take to ensure my app is robust and can handle unexpected traffic spikes without crashing.
Essentially, I'd like to prepare for the worst-case scenario in terms of handling unexpected traffic spikes etc.
Any specific pointers (especially with Heroku) will be helpful!
What is the overall distribution of http requests for loading a typical page on your app? Open that in Mozilla Firebug / Chrome Dev Tool and analyze http requests being made.
If you see that there are LOTS of static content being loaded (Like CSS / images/ JS ) for each page then it would indicate a cache issue (static content are not getting cached).
You could even move static content to a CDN (http://en.wikipedia.org/wiki/Content_delivery_network) These two are low hanging fruits.
next step is to ensure that your app can be hosted on multiple machines (E.g. it does not depend on same http session across each host and similar things). This way you can add more hosts to serve the demand.
To ensure your app is stable during all development and deployments, write unit tests, functional tests and integration tests (there are a lot of gems to handle this, like shoulda, rspec, cucumber, capybara, selenium...).
I would also use Hoptoad for error notification. There is a free offer for 1 project ( https://hoptoadapp.com/account/new/Egg )
The next thing to monitor your site could be NewRelic ( http://newrelic.com/ ). It gives you an overview what queries took long and where is a bottleneck in your app.
A very short answer: In theory you need to learn about capacity, scalability and performance.
On practice you can spin up more instances on heroku (or engines) but you'll be paying more money for it.
Related
I am playing around with using Rails to underpin a kiosk. This is a terminal where there is only one local user at a time.
Under this system, a browser like Chrome would access the Rails app.
Things I assume would be helpful:
Super-fast, very lightweight Rails server (I'm using Puma).
Eliminating standard processes/assumptions that are meant for internet website contexts (caching, CDNs, middleware, etc.).
In some level of detail preferably, how should one set up a Rails app for maximum performance in a single-user kiosk?
This might sound like a non-answer, but the approach I would take is to use Rails in its default (production) configuration, and optimise performance issues as they arise in your test bed. Running Rails in production mode will likely give you more than enough performance if you have a dedicated machine for a single user (often you'll have many clients to a single Rails instance). Without testing the application, you could sink a considerable amount of time into optimisations that don't impact the user experience.
It may be worth sitting Rails behind Apache/nginx (Passenger is a well understood way to get a Rails app on Apache) to serve your static assets, but from the information provided so far I'd be surprised if performance optimisation was necessary at this stage.
A challenge that might be worth considering at this stage is how you'll deploy changes to your kiosk/set of kiosks. Will they be brought in for updates or need to have changes applied over-the-air? That will likely impact how you deploy it onto the machine, and in my experience is a harder thing to change later on.
Until now, our site has had a modest amount of traffic. None of our developers are big ops guys, but we've stayed ahead of it and keep the site up and running pretty quick. That said, our dev team is stretched, we've accumulated some technical debt, and there's plenty of opportunity to optimize.
Without getting into specifics, we just found out that we'll be expecting a massive amount of traffic in the near future in a very short period time. On the order of several million hits in a few hours. Scaling is one thing, but this is several orders of magnitude greater than what we're seeing now.
We're a Rails app hosted on S3 using ELB, and Postgresql.
I wanted to field some recommendations for broad starting points for scaling and load testing given this situation.
Update: Sorry, EC2, late night :)
#LastZactionHero
Pretty interesting question, let me answer you in detail, I hope you are talking about some e-commerce applications, enterprise or B2B apps doenst see spikes as such. Since you already mentioned that you are hosted your rails app on s3. Let me make couple of things clear.
1)You cant host an rails app on s3. S3 is simple storage service. Where you can only store files.
2) I guess you have hosted your rails app on AWS ec2 with a elastic load balancer attached above the ec2 instances which is pretty good.
3)You have a self managed Postgresql deployed on a ec2 instance.
If you are running on AWS you are half way safe and you can easily scale up and scale down.
I can see one problem in your present model, that your db. AWS has got db as a service. Thats called Relation database service.Which supports Mysql Oracle and MS SQL server.
RDS comes with lot of features like auto back up of your database, high IOPS etc.
But it doesnt support your Postgresql. You need to have or manage a self managed ec2 instance and run postgresql database, but make sure its fail safe and you do have proper back and restore system at place.
AWS provides auto scaling api and command line tools, pretty easy.
You dont have worry about the bandwidth issue etc, but I admit Angelo's answer too.
You can use elastic mem cache for caching your app. Use CDN if need to speed your app. RDS can manage upto 30000 IOPS, its a monster to it will do lot of work for you.
Feel free to ask me if you need any kind of help.
(Disclaimer: I am a senior devOps engineer working for an e-commerce company, use ruby on rails)
Congratulations and I hope your expectation pans out!!
This is such a difficult question to comprehensively answer given the available information. For example, is your site heavy on db reads, writes or both (and is your sharding/replication strategy in line with your db strain)? Is bandwidth an issue, etc? Obvious points would focus on making sure you have access to the appropriate hardware and that your recipies for whatever you use to provision/deploy your hardware is up to date and good to go. You can often throw hardware at a sudden spike in traffic until you can get to the root of whatever bottlenecks you discover (and yes, you will discover them at inconvenient times!)
Regarding scaling your app, you should at least:
1) Cache whatever you can. Pay attention to cache expiration, etc.
2) Be sure your DB has appropriate indexes set up (essentially, you should have an index on any field you're searching on.)
3) Watch your logs closely to identify potential long queries, N+1 queries, long view renders, etc.
4) Do things like what Shopify outlines in this post: http://www.shopify.com/technology/7535298-what-does-your-webserver-do-when-a-user-hits-refresh#axzz2O0gJDotV
5) Set up a good monitoring system (Monit, God, etc) for each layer of your stack - sudden spikes in traffic can quickly bottleneck your application in unexpected places and lead to more issues. The cascade can happen quickly.
6) Set up cron to automate all those little tasks you currently do manually...that you will probably forget about doing once you're dealing with traffic spikes.
7) Google scaling rails and you'll see tons of good info.
8) etc, etc, etc...
You can use some profiling tools (rubyperf, or something like NewRelic, etc) Whatever response you get from them is probably best to be considered as a rough baseline at best. Simple reason being that your profiling is dependent on your hardware stack which will certainly change depending on actual traffic patterns. Pretty easy to do if you have a site with one page of static content...incredibly difficult to do if you have a CMS site with a growing db and growing traffic.
Good luck!!!
I've been working on a rails project that's unusual for me in a sense that it's not going to be using a MySQL database and instead will roll with mongoDB + Redis.
The app is pretty simple - "boot up" data from mongoDB to Redis, after which point rails will be ready to take requests from users which will consist mainly of pulling data from redis, (I was told it'd be pretty darn fast at this) doing a quick calculation and sending some of the data back out to the user.
This will be happening ~1500-4500 times per second, with any luck.
Before the might of the user army comes down on the server, I was wondering if there was a way to "simulate" the page requests somehow internally - like running a rake task to simply execute that page N times per second or something of the sort?
If not, is there a way to test that load and then time the requests to get a rough idea of the delay most users will be looking at?
Caveat
Performance testing is a very broad topic, and the right tool often depends on the type and quality of results that you need. As just one example of the issues you have to deal with, consider what happens if you write a benchmark spec for a specific controller action, and call that method 1000 times in a row. This might give a good idea of performance of that controller method, but it might be making the same redis or mongo query 1000 times, the results of which the database driver may be caching. This also ignores the time it'll take your web server to respond and serve up the static assets that are part of the request (this may be okay, especially if you have other tests for this).
Basic Tools
ab, or ApacheBench, is a simple commandline tool that you can use to test the throughput and speed of your app. I usually go to this first when I want to send a thousand requests at a web server, or test how many simultaneous requests my app can handle (e.g. when comparing mongrel, unicorn, thin, and goliath). Because all requests originate from the same server, this is good for a small number of requests, but as the number of requests grow, you'll be limited by the resources on your testing machine (network stack, cpu, and maybe memory).
Benchmark is a standard ruby class, and is great for quickly spitting out some profiling information. It can also be used with Test::Unit and RSpec. If you want a rake task for doing some quick benchmarking, this is probably the place to start
mechanize - I like using mechanize for quickly scripting an interaction with a page. It handles cookies and forms, but won't go and grab assets like images by default. It can be a good tool if you're rolling your own tests, but shouldn't be the first one to go to.
There are also some tools that will simulate actual users interacting with the site (they'll download assets as a browser would, and can be configured to simulate several different users). Most notable are The Grinder and Tsung. While still very much in development, I'm currently working on tsung-rails to make it easier to automate rails load testing with tsung, and would love some help if you choose to go in this direction :)
Rails Profiling Links
Good overview for writing performance tests
Great slide deck covering most of the latest tools for profiling at various levels
I need to host a lot of simple rails/sinatra/padrino applications of different ruby versions each with 0..low hits per day. They belong to different owners and should be well isolated from each other.
When an app is hit it should respond in reasonably short time, but I expect several simultaneous visitors are hitting the same site to be a rare case.
I'm going to create separate os user for each application. Surely I'd like to put them as many per server as it's possible. Thus I need to choose the web server with the lowest memory footprint, which can run applications on behalf of different users with different ruby versions and gemsets.
I consider webrick,nginx+passenger,thin,apache+passenger. I suppose the reliability of all choices is sufficient for such a job, and while performance isn't an issue, the memory consumption is.
I found many posts regarding performance issues, but most of them discuss the performance tuning and issues. I couldn't find a comparison of web servers memory usage when idle.
Is "in process" webrick the best choice? Which one would you choose for that job?
And I couldn't figure out how to resolve subdomains to application ports with webrick. Shall I use nginx or apache for that?
I don't have much experience with hosting myself, but using Webrick for production is not a good idea I think. You can also check out mongrel which I saw used in production. In most cases though you will probably want to choose between thin and unicorn. Check out this http://cmelbye.github.com/2009/10/04/thin-vs-unicorn.html or google around. Good luck :-)
Why not use Heroku? Its free and gets you out of the hassle of server configuration and maintenance.
Currently after a build/deployment of our app (58 projects, large asp.net MVC 3 front end) takes ~15-20secs to load as it goes through the whole 'recycling the app pool' (release configuration).
We do have a web farm if that alters people's answers, but the question really is:
What are people doing in large scale applications where a maintenance window isn't viable (we're a 24/7 very active website) to minimize that initial 'first hit' on the app pool recycle after a deploy?
We've used a number of tools to analyze that startup time and there doesn't really seem to be any way to bring it down so what I'm looking for are what techniques do people employ in order to minimize the impact of a large application deploy affecting users.
By default - if you change 15 files in an ASP.NET application at once (even via FTP) then the app pool is automatically recycled. You can change the number of files but as soon as web.config and bin files are changed then it needs to recycle. So in my opinion the ideal solution for an environment like yours would be as follows:
4 web servers (this is an arbitrary number)
each server has a status.aspx that the load balancer looks at - use TeamCity to take 2 of these servers "off line" (off the load balancer) and wait 20 seconds for the traffic to filter across. A distributed cache will help keep user experience problems
Use TeamCity to deploy to those 2 servers - run your automated tests etc. and once you are happy put those back into the farm and take the other 2 offline and deploy to those
This can all be scripted / automated. The only issue with this is any schema changes that are not backwards compatible may not allow running the new version site in parallel with old version of the site for the 20 seconds for the load balancer to kick back in
This is good old fashioned Canary Releasing - there are some patterns here http://continuousdelivery.com/patterns/ to help take into consideration. Id also suggest a copy of that continuous delivery book - its like a continuous delivery bible and has got me out of a few situations :)
At the very base you could run a tinyget script against the application after completion of deployment which will "warm up" the application however if a customer hits your site before the script can run, they will still face a delay. What do you currently have in place, what post deployment steps do you have in place?
In a farm environment you could stage deployments too, so take one server out of load balance, update it and then bring that online after deployment and take the other out, complete the deployment and then reintroduce into the farm. How is your SQL Server setup - clustered?
copy and paste from my post here
We operate a Blue/Green deployment strategy on a 4 tier architecture which has a web site over 4 servers at the top tier. Due to the complexity the architecture introduced for deployments, we needed a way to deploy without disturbing any traffic to the "live" site. Following Fowler's advice, but not quite in the same way, we came up with a solution that means we have 2 sites on each server (a blue and a green, or in our case site A and site B). The live site has the appropriate host header, and once we have deployed and tested to the non-live site, we then flip the headers of the 2 sites so that what was once live is now the non-live site, and vice-versa. The effect is, a robust deployment that can be done in business hours and with the highest level of confidence.
This of course complicates your configuration and deployment slightly, but it's worth the effort. I guess it kind of goes without saying that you want to script both the deployment, and the host header swapping.
Firstly, unless you're running Google or something bigger, does a 15-20s load time at 3am for a handful of users really impact that much? I'd say the effort invested in eliminating the occasional lag would far outweigh the 15-20s inconvenience of a couple of users.
I consider it a necessary evil of using ASP.NET unfortunately. Using a pre-compiled site (.DLLs instead of the code-behind files) will lessen the time but not necessarily eliminate it.
The best thing you can do is use something like a status notification bar to warn users they may experience some "issues" during "essential maintenance".
But even then, I'd say in terms of user experience it'd be better to keep quiet and have a handful of people blame their "slow internet" when your site takes 20s to load on one occasion, than announce to all and sundry that it will be slow.
You can also try this approach : http://weblogs.asp.net/scottgu/archive/2009/09/15/auto-start-asp-net-applications-vs-2010-and-net-4-0-series.aspx
without knowing anything about your site, my first thought is that you might be able to break it down into smaller sites so that they start faster individually.
second, with your web farm, i assume you have some sort of load balancing device in front of that from which you can pull machines out of the pool when they are being deployed. don't put them back in the pool until after you have sent a request against the site to get it started up. you should be able to script this such that you are pretty much clicking a button that takes a machine out, deploys to it, and sends a request after it's back up and happy.
You can consider using aspnet_compiler.exe to precompile your application, because I think the delay after deployment is caused by the compilation phase rather than "whole recycling the app pool".