2009-05-25 We’ve had a perplexing issue with our Ruby daemons at OneSpot: they seem to grow to 300-400MB each within about 30 minutes, at which point our Monit scripts restart them. We suspected a memory leak and so upgraded from stock Ruby 1.8.5 shipped with CentOS to the latest REE 1.8.6 but nothing changed. I also saw a very similar issue at FiveRuns. Why is this problem seemingly endemic, even
from /prod_path/shared/bundle/ruby/2.1.0/gems/tiny_tds-1.0.2/lib/tiny_tds/client.rb:43:in `connect' from /prod_path/shared/bundle/ruby/2.1.0/gems/tiny_tds-1.0.2/lib/tiny_tds/client.rb:43:in `initialize' from /prod_path/shared/bundle/ruby/2.1.0/gems/activerecord-sqlserver-adapter-4.2.11/lib/active_record/connection_adapters/sqlserver_adapter.rb:311:in `new' from /prod_path/shared/bundle/ruby/2.1.0/
Creator of Ruby on Rails, Founder & CTO at Basecamp (formerly 37signals), NYT Best-selling author of REWORK and REMOTE, and Le Mans class-winning racing driver. Program to where the performance puck is going to be, not where it has beenIn the year of our lord, 2013, the thought of ARM-powered phones running the full web experience with JavaScript as fast as x86-powered desktops was a laughable pip
2008-11-09 I got back to Austin last night after a great three days in Orlando at RubyConf. I thought my talk went well and the crowd had several interesting questions so I know someone was paying attention. :-) Given that my interests lie in server-side performance and scalability, I saw two linked trends developing: Threads suck (on Ruby?) They work reasonably well in Java but you should avoid t
xUnit Test Patterns defines the System Under Test (SUT) as: whatever class, object or method we are testing; when we are writing customer tests, the SUT is probably the entire application or at least a major subsystem of it. The System Under Test helps us focus on what we’re really testing, what Depended-On Components (DOC) interact with it, and how to replace a Depended-On Component with a Test D
2007-10-02 At FiveRuns, we have a set of installed clients which upload data to our service periodically. Because of the way it is implemented, Rails is quite slow in handling file uploads. Merb is an alternative, albeit much simpler, stack to Rails which handles file uploads in a much saner manner. The performance difference is quite large. Optimizations Merb -- turned off ActiveRecord, environme
Dalli – memcached for Ruby 2010-08-30 memcached Dalli is my brand new memcached client for Ruby. I’ve maintained Ruby’s memcache-client for two years now and been dissatisfied with the codebase for a while. Coincidentally, NorthScale approached me recently about building a pure Ruby memcached client which used the new binary protocol defined in memcached 1.4. We worked out an arrangement to sponso
2015-11-05 Ruby provides several complex data structures out of the box; hash, array, set, and queue are all I need 99% of the time. However knowing about more advanced data structures means you know when to reach for something more esoteric. Here’s two examples I’ve used recently. ConnectionPool::TimedStack My connection_pool gem implements a thread-safe Stack with a time-limited pop operation. T
# File activerecord/lib/active_record/secure_token.rb, line 61 def generate_unique_secure_token(length: MINIMUM_TOKEN_LENGTH) SecureRandom.base58(length) end Example using has_secure_token # Schema: User(token:string, auth_token:string) class User < ActiveRecord::Base has_secure_token has_secure_token :auth_token, length: 36 end user = User.new user.save user.token # => "pX27zsMN2ViQKta1bGfLmVJE"
2009-05-19 I’ve been working with Varnish 2.0 for the last two weeks, going from complete n00b to someone who knows enough to feel I can improve the terrible lack of documentation for Varnish and VCL. There’s not a lot out there and what’s there is hard to find and sometimes erroneous. I’m hoping this post will help others like me who are struggling with Varnish and VCL. Basics VCL is essentially
Cassandra Internals – Writing 2010-03-13 cassandra We’ve started using Cassandra as our next-generation data storage engine at OneSpot (replacing a very large Postgresql machine with a cluster of EC2 machines) and so I’ve been using it for the last few weeks. As I’m an infrastructure nerd and a big believer in understanding the various layers in the stack, I’ve been reading up a bit on how Cassand
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く