Ostrich is a library for scala servers that makes it easy to:
- load & reload per-environment configuration
- collect runtime statistics (counters, gauges, metrics, and labels)
- report those statistics through a simple web interface (optionally with graphs) or into log files
- interact with the server over HTTP to check build versions or shut it down
The idea is that it should be simple and straightforward, allowing you to plug it in and get started quickly.
This library is deprecated, and users should migrate to Commons Metrics. Please see TwitterServer's migration guide for details.
Use sbt (simple-build-tool) to build:
$ sbt clean update package-dist
The finished jar will be in dist/.
There are four kinds of statistics that ostrich captures:
-
counters
A counter is a value that never decreases. Examples might be "
widgets_sold" or "births". You just increment the counter each time a countable event happens, and graphing utilities usually graph the deltas over time. To increment a counter, use:Stats.incr("births")or
Stats.incr("widgets_sold", 5) -
gauges
A gauge is a value that has a discrete value at any given moment, like "
heap_used" or "current_temperature". It's usually a measurement that you only need to take when someone asks. To define a gauge, stick this code somewhere in the server initialization:Stats.addGauge("current_temperature") { myThermometer.temperature }A gauge method must always return a double.
-
metrics
A metric is tracked via distribution, and is usually used for timings, like so:
Stats.time("translation") { document.translate("de", "en") }But you can also add metrics directly:
Stats.addMetric("query_results", results.size)Metrics are collected by tracking the count, min, max, mean (average), and a simple bucket-based histogram of the distribution. This distribution can be used to determine median, 90th percentile, etc.
-
labels
A label is just a key/value pair of strings, usually used to report a subsystem's state, like "boiler=offline". They're set with:
Stats.setLabel("boiler", "online")They have no real statistical value, but can be used to raise flags in logging and monitoring.
If you build with standard-project
https://github.com/twitter/standard-project, RuntimeEnvironment can pull
build and environment info out of the build.properties file that's tucked
into your jar. Typical use is to pass your server object (or any object from
your jar) and any command-line arguments you haven't already parsed:
val runtime = RuntimeEnvironment(this, args)
The command-line argument parsing is optional, and supports only:
-
--versionto print out the jar's build info (name, version, build) -
-f <filename>to specify a config file manually -
--validateto validate that your config file can be compiled
Your server object is used as the home jar of the build.properties file.
Then the classpath is scanned to find that jar's home and the config files
that are located nearby.
A good example server is created by the scala-bootstrapper project here: https://github.com/twitter/scala-bootstrapper
Define a server config class:
class MyServerConfig extends ServerConfig[MyServer] {
var serverPort: Int = 9999
def apply(runtime: RuntimeEnvironment) = {
new MyServer(serverPort)
}
}
A ServerConfig class contains things you want to configure on your server,
as vars, and an apply method that turns a RuntimeEnvironment into your
server. ServerConfig is actually a helper for Config that adds logging
configuration, sets up the optional admin HTTP server if it was configured,
and registers your service with the ServiceTracker so that it will be
shutdown when the admin port receives a shutdown command.
Next, make a simple config file for development:
import com.twitter.conversions.time._
import com.twitter.logging.config._
import com.twitter.ostrich.admin.config._
import com.example.config._
new MyServerConfig {
serverPort = 9999
admin.httpPort = 9900
loggers = new LoggerConfig {
level = Level.INFO
handlers = new ConsoleHandlerConfig()
}
}
The config file will be evaluated at runtime by this code in your Main class:
object Main {
val log = Logger.get(getClass.getName)
def main(args: Array[String]) {
val runtime = RuntimeEnvironment(this, args)
val server = runtime.loadRuntimeConfig[MyServer]()
log.info("Starting my server!")
try {
server.start()
} catch {
case e: Exception =>
e.printStackTrace()
log.error(e, "Unexpected exception: %s", e.getMessage)
System.exit(0)
}
}
}
Your MyServer class should implement the Service interface so it can be
started and shutdown. The runtime environment will find your config file and
evaluate it, returning the MyServer object to you so you can start it. And
you're set!
The base trait of the stats API is StatsProvider, which defines methods for
setting and getting each type of collected stat. The concrete implementation
is StatsCollection, which stores them all in java concurrent hash maps.
To log or report stats, attach a StatsReporter to a StatsCollection. A
StatsReporter keeps its own state, and resets that state each time it
reports. You can attach multiple StatsReporters to track independent state
without affecting the StatsCollection.
The simplest (and most common) pattern is to use the global singleton named
Stats, like so:
import com.twitter.ostrich.stats.Stats
Stats.incr("cache_misses")
Stats.time("memcache_timing") {
memcache.set(key, value)
}
Stat names can be any string, though conventionally they contain only letters, digits, underline (_), and dash (-), to make it easier for reporting.
You can immediately see any reported stats on the admin web server, if you've activated it, through the "stats" command:
curl localhost:PPPP/stats.txt
(where PPPP is your configured admin port)
The global "shutdown" and "quiesce" commands work by talking to a global
ServiceTracker object. This is just a set of running Service objects.
Each Service knows how to start and shutdown, so registering a service with
the global ServiceTracker will cause it to be shutdown when the server as a
whole is shutdown:
ServiceTracker.register(this)
Some helper classes like BackgroundProcess and PeriodicBackgroundProcess
implement Service, so they can be used to build simple background tasks
that will be automatically shutdown when the server exits.
The easiest way to start the admin service is to construct an
AdminServiceConfig with desired configuration, and call apply on it.
To reduce boilerplate in the common case of configuring a server with an
admin port and logging, a helper trait called ServerConfig is defined with
both:
var loggers: List[LoggerConfig] = Nil
var admin = new AdminServiceConfig()
The apply method on ServerConfig will create and start the admin service
if a port is defined, and setup any configured logging.
You can also build an admin service directly from its config:
val adminConfig = new AdminServiceConfig {
httpPort = 8888
statsNodes = new StatsConfig {
reporters = new TimeSeriesCollectorConfig
}
}
val runtime = RuntimeEnvironment(this, Nil)
val admin = adminConfig()(runtime)
If httpPort isn't set, the admin service won't start, and admin will be
None. Otherwise it will be an Option[AdminHttpService].
statsNodes can attach a list of reporters to named stats collections. In the
above example, a time-series collector is added to the global Stats object.
This is used to provide the web graphs described below under "Web graphs".
Commands over the admin interface take the form of an HTTP "get" request:
GET /<command>[/<parameters...>][.<type>]
which can be performed using 'curl' or 'wget':
$ curl http://localhost:PPPP/shutdown
The result body may be json or plain-text, depending on . The default is json, but you can ask for text like so:
$ curl http://localhost:PPPP/stats.txt
For simple commands like shutdown, the response body may simply be the JSON
encoding of the string "ok". For others like stats, it may be a nested
structure.
The commands are:
-
ping
Verify that the admin interface is working; server should say "pong" back.
-
reload
Reload the server config file for any services that support it (most do not).
-
shutdown
Immediately shutdown the server.
-
quiesce
Close any listening sockets, stop accepting new connections, and shutdown the server as soon as the last client connection is done.
-
stats
Dump server statistics as 4 groups:
counters,gauges,metrics, andlabels.- If the
periodquery parameter is specified (e.g./stats.json?period=10), a StatsListener is acquired for that time period, and all requests with this period value will receive the same stats values throughout that period. - Otherwise, if the
namespaceargument is provided (e.g./stats.json?namespace=ganglia), a StatsListener is acquired for that namespace, and each request with this namespace value will reset the stats listener, effectively returning the delta since the prior request with that namespace. (Seesrc/scripts/json_stats_fetcher.rbfor an example.) - If neither
periodnornamespaceparameters are specified, the main stats object will be fetched, returning non-differerential counters and metrics over the life-time of the process.
- If the
-
server_info
Dump server info (server name, version, build, and git revision).
-
threads
Dump stack traces and stats about each currently running thread.
-
gc
Force a garbage collection cycle.
If TimeSeriesCollector is attached to a stats collection, the web interface
will include a small graph server that can be used to look at the last hour of
data on collected stats.
The url
http://localhost:PPPP/graph/
(where PPPP is your admin httpPort) will give a list of currently-collected
stats, and links to the current hourly graph for each stat. The graphs are
generated in javascript using flot.
If you're using heapster, you can generate a profile suitable for reading with google perftools
Example use:
curl -s 'localhost:9990/pprof/heap?pause=10' >| /tmp/prof
This will result in a file that you can be read with pprof
This started out as several smaller projects that began to overlap so much, we decided to merge them. Major contributers include, in alphabetical order:
- Alex Payne
- John Corwin
- John Kalucki
- Marius Eriksen
- Nick Kallen
- Oliver Gould
- Pankaj Gupta
- Robey Pointer
- Steve Jenson
If you make a significant change, please add your name to the list!
This library is released under the Apache Software License, version 2, which
should be included with the source in a file named LICENSE.
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