StatsD client for Ruby apps
This is a ruby client for statsd (http://github.com/etsy/statsd). It provides a lightweight way to track and measure metrics in your application.
We call out to statsd by sending data over a UDP socket. UDP sockets are fast, but unreliable, there is no guarantee that your data will ever arrive at it's location. In other words, fire and forget. This is perfect for this use case because it means your code doesn't get bogged down trying to log statistics. We send data to statsd several times per request and haven't noticed a performance hit.
The fact that all of your stats data may not make it into statsd is no issue. Graphite (the graph database that statsd is built on) will only show you trends in your data. Internally it only keeps enough data to satisfy the levels of granularity we specify. As well as satisfying it's requirement as a fixed size database. We can throw as much data at it as we want it and it will do it's best to show us the trends over time and get rid of the fluff.
For Shopify, our retention periods are:
- 10 seconds of granularity for the last 6 hours
- 60 seconds of granularity for the last week
- 10 minutes of granularity for the last 5 years
This is the same as what Etsy uses (mentioned in the README for http://github.com/etsy/statsd).
StatsD.server = 'statsd.myservice.com:8125' StatsD.logger = Rails.logger StatsD.mode = :production StatsD.prefix = 'my_app' # An optional prefix to be added to each stat. StatsD.default_sample_rate = 0.1 # Sample 10% of events. By default all events are reported.
If you set the mode to anything besides production then the library will print its calls to the logger, rather than sending them over the wire.
StatsD keys look like 'admin.logins.api.success'. Each dot in the key represents a 'folder' in the graphite interface. You can include any data you want in the keys.
Lets you benchmark how long the execution of a specific method takes.
# You can pass a key and a ms value StatsD.measure('GoogleBase.insert', 2.55) # or more commonly pass a block that calls your code StatsD.measure('GoogleBase.insert') do GoogleBase.insert(product) end
Rather than using this method directly it's more common to use the metaprogramming methods made available.
GoogleBase.extend StatsD::Instrument GoogleBase.statsd_measure :insert, 'GoogleBase.insert'
Lets you increment a key in statsd to keep a count of something. If the specified key doesn't exist it will create it for you.
# increments default to +1 StatsD.increment('GoogleBase.insert') # you can also specify how much to increment the key by StatsD.increment('GoogleBase.insert', 10) # you can also specify a sample rate, so only 1/10 of events # actually get to statsd. Useful for very high volume data StatsD.increment('GoogleBase.insert', 1, 0.1)
Again it's more common to use the metaprogramming methods.
As mentioned, it's most common to use the provided metaprogramming methods. This lets you define all of your instrumentation in one file and not litter your code with instrumentation details. You should enable a class for instrumentation by extending it with the
Then use the methods provided below to instrument methods in your class.
This will increment the given key even if the method doesn't finish (ie. raises).
GoogleBase.statsd_count :insert, 'GoogleBase.insert'
Note how I used the 'GoogleBase.insert' key above when measuring this method, and I reused here when counting the method calls. StatsD automatically separates these two kinds of stats into namespaces so there won't be a key collision here.
This will only increment the given key if the method executes successfully.
GoogleBase.statsd_count_if :insert, 'GoogleBase.insert'
So now, if GoogleBase#insert raises an exception or returns false (ie. result == false), we won't increment the key. If you want to define what success means for a given method you can pass a block that takes the result of the method.
GoogleBase.statsd_count_if :insert, 'GoogleBase.insert' do |response| response.code == 200 end
In the above example we will only increment the key in statsd if the result of the block returns true. So the method is returning a Net::HTTP response and we're checking the status code.
Similar to statsd_count_if, except this will increment one key in the case of success and another key in the case of failure.
GoogleBase.statsd_count_success :insert, 'GoogleBase.insert'
So if this method fails execution (raises or returns false) we'll increment the failure key ('GoogleBase.insert.failure'), otherwise we'll increment the success key ('GoogleBase.insert.success'). Notice that we're modifying the given key before sending it to statsd.
Again you can pass a block to define what success means.
GoogleBase.statsd_count_success :insert, 'GoogleBase.insert' do |response| response.code == 200 end
Instrumenting Class Methods
You can instrument class methods, just like instance methods, using the metaprogramming methods. You simply have to configure the instrumentation on the singleton class of the Class you want to instrument.
AWS::S3::Base.singleton_class.extend StatsD::Instrument AWS::S3::Base.singleton_class.statsd_measure :request, 'S3.request'
Reliance on DNS
Out of the box StatsD is set up to be unidirectional fire-and-forget over UDP. Configuring the StatsD host to be a non-ip will trigger a DNS lookup (ie synchronous round trip network call) for each metric sent. This can be particularly problematic in clouds that have a shared DNS infrastructure such as AWS.
- Using an IP avoids the DNS lookup but generally requires an application deploy to change.
- Hardcoding the DNS/IP pair in /etc/hosts allows the IP to change without redeploying your application but fails to scale as the number of servers increases.
- Installing caching software such as nscd that uses the DNS TTL avoids most DNS lookups but makes the exact moment of change indeterminate.