I have a rails app running on Heroku that makes use of threads, and it occasionally runs into database connection errors. Is this just because I am accessing the database within the threads or does each thread automatically open a database connection? I would like to learn more about threading in rails, and any resources are appreciated.
This question varies largely depending on how many instances you have running, how many requests your receiving, and more importantly your database. Databases can and will have a maximum number of concurrent connections. You can read more about Heroku/concurrent connections here in the Heroku official documentary, it's probably more informative than what I can tell you in a single comment.
That being said, your question was a little vague and it's hard to figure out what's going on. Can you tell us a little more about what error you're getting (like the specific error) and maybe a small backtrace? Are you getting these errors on the same pages or different pages? Would you say your site is particularly high traffic?
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I’ve set a client up with Heroku for their Ruby on Rails application and have had a great deal of trouble over the years with their application not running well regardless of how much money we spend on additional resources, find their documentation highly confusing. I’ve never been able to understand their specific terminology and documentation. We are constantly getting "H12" errors and "R14" errors etc. The memory usage and dyno loads are constantly spiking. And yet this is a small to medium-sized business without a massive amount of traffic. Wondering if anybody out there who does understand the ins and outs of Heroku can look this configuration over and tell me if it makes sense:
DB_POOL: 10
MALLOC_ARENA_MAX: 2
RAILS_MAX_THREADS: 5
WEB_CONCURRENCY: 4
Ruby 2.7
Rails 6.0
Puma
8 2x web dynos
5 1x worker dynos
$50 Postgres standard 0 database
$15 Memcachier
$10 Rediscloud
...etc addons
Your WEB_CONCURRENCY is too high for your Standard-2x dynos. The recommended default is 2: https://devcenter.heroku.com/articles/deploying-rails-applications-with-the-puma-web-server#recommended-default-puma-process-and-thread-configuration
This is likely contributing to your R14 errors as higher web concurrency means more memory usage. So you need to either lower your web concurrency (which may mean you also need to increase the # of dynos to compensate) or you need to use bigger dynos.
You already have MALLOC_ARENA_MAX=2 but not sure if you are using jemalloc. You might want to try that too.
Of course, you may also have other memory issues in your app - check out some tips here. I also recommend adding a monitoring tool like AppSignal as it's capable of tracking memory allocations per transaction.
For mitigating H12s:
Ensure you have installed something like the rack-timeout gem, which ensures that a long-running request is dropped at the dyno-level and thus avoids the H12 error (you get a Rack::TimeoutError exception instead). Set the timeout to 15s so that it is well under the 30s for H12 timeout.
Investigate your slow transactions. A monitoring tool is key here, i.e. New Relic (start with lowest-priced paid plan - free plan does not allow transaction tracing). Here is their blog post on how to trace transactions
When you've identified the problem - fix it!
if the bottleneck is external:
check for external API limits and throttling
add timeouts and make app resilient to slow external responses
if the bottleneck is due to the database:
optimize slow queries
check cache hit rates
check for the # of waiting connections and db locks -> if the number of waiting connections is consistently above 0 for X minutes, that indicates you have some long locks that you'll need to investigate. Waiting connections is easiest to track over time with Librato (free plan should do fine)
if the bottleneck is other app code:
add more custom instrumentation to get more insights, i.e. New Relic instructions
address app code issues
I want to stress the importance of monitoring tools to help diagnose issues and help determine optimal resource usage. Doing things like figuring out the correct concurrency configs, the correct size and # of dynos to run are virtually impossible without proper monitoring tools. Hopefully you have some already that are covered by your etc add-ons that are not listed, but if you do not, I'll summarize my recommendations and mention a couple other tips:
To get more metrics info, ensure you have enabled log-runtime-metrics
Also enable Ruby language metrics
Add a monitoring tool that can track Ruby memory allocations like AppSignal. Scout APM can do this too but I think their plans capable of this are more expensive (requires Scout Insights feature)
Add the lowest-paid version of New Relic. This is my go-to tool for transaction tracing. AppSignal can do this too if you don't want to pay for another tool, but I find it easier with New Relic.
Add Librato. It offers some great charts out of the box, including a set of Postgres charts in its own dashboard.
Set alerts in your monitoring apps to warn you about things like response times so you can look into them!
And of course, make all your changes in staging first AND load test them to see the impacts of your changes before attempting in production!
Update: I also just noticed that you said you are using Standard-0 Postgres, which means it has a 120 connection limit. So if you end up lowering your WEB_CONCURRENCY and increasing the # of dynos, watch out for your total connections to that database. Beyond just the fact that there is a limit, more connections also mean more overhead for your db anyway so if you are close to your connection limit, you are more likely to see db performance suffer. You may want to upgrade to another plan that has a higher connection limit or use pgbouncer as your connection pooler to avoid connection limits.
I have a Ruby on Rails application with models, controllers and stuff, so user requests are performed as independent ones. The app is backed by an MS SQL database. From time to time (at ~100 rpm) concurrent user requests cause deadlocks on DB resources, so one of the requests fails with an error.
What is the right way to handle such situations and avoid deadlocks? I'm looking for a general direction to dig. Thanks.
This blog post has some very good advice for preventing deadlocks in Rails and dealing with them.
There is also a drop-in deadlock_retry gem written by, among others, DHH, which will re-try transactions 3 times when a deadlock timeout is detected.
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.
I've heard often that deploying a traditional monolithic Rails app (i.e. no internal Web API, no message queue, no Redis/memcached server) to multiple servers can produce a bunch of bugs that are very hard to debug but I'm having a hard time coming up with some concrete examples despite a few hours of googling
Some obvious issues that I can think of are:
Observers - likely will not work properly as the observation is only propagated on one server and not all of them (assuming there is no Message Queue)
Sessions - would probably need to store these in the database which would need it's own host
Caches - any sweepers would have issues propagating invalidations between servers.
Anyone else care to contribute? I'd really appreciate any articles others may have come across or just general wisdom :)
Observers are just code callbacks.
They run on each process, on each server.
Sessions have defaulted to the cookie store for the last few years.
So multiple servers are no problem.
If you don't have enough space in your cookie then I suggest you may be doing something wrong.
Cache invalidation is indeed a problem.
But it always is.
One solution is to break your cache out into a standalone service.
Sites like Facebook have giant farms of memcache
I think scaling and clustering is always a hard problem.
But this seems to be an old argument against rails.
If anything the last few years have seen rails shine in this respect.
With ec2, nosql, and server automation becoming quite a norm in the community.
It seems that the only tutorials out there talking about using Amazon's SimpleDB in a rails site are using AWSDBProxy... Personally, I find this counter-intuitive to scaling out, considering the server layout of a typical Rails site below (using AWSDBProxy):
Plugin here: http://agilewebdevelopment.com/plugins/aws_sdb_proxy
Image here: http://www.freeimagehosting.net/uploads/91be4e0617.png
As you can see, even if we add more mongrels, we have two problems.
We have a single point of failure far less stable than our load balancer
We have to force all our information through this one WEBrick server
The solution is, of course, to add more AWSDBProxies... but why not then just use the following code in say, a class, skipping the proxy all together?
service = AwsSdb::Service.new(Logger.new(nil),
CONFIG['aws_access_key_id'],
CONFIG['aws_secret_access_key'])
service.query(domain, query)
So what I'm getting at, is if you are using AWSDBProxy, what are you justifications for it? And if you are indeed using it, what is your performance like? If you have hard numbers, this would be even more appreciated!
I'm not using it, nor have I ever heard of it, but this is what I would think are reasonable reasons.
You're running your main app server on EC2, so the chance of Internet FAIL doesn't really affect you more than once.
You run one proxy on each of your app servers. So it's connection going down is no worse than it's connection(s) to the database going down.
Because it can be done. This is as good a reason as any in an open source project. Sometimes it takes building a thing before you know whether said thing is a good/bad idea.
You don't have the traffic levels to need a load balancer. Then your diagram squashes down to a line, if not a single machine.