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stats collector & reporter for scala servers
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Ostrich is a small library for collecting and reporting runtime statistics and debugging info from a scala server. It can collect counters, gauges, and timings, and it can report them via log files or a simple web interface that includes graphs. A server can also be asked to shutdown or reload its config files using these interfaces. The idea is that it should be simple and straightforward, allowing you to plug it in and get started quickly.

This library is released under the Apache Software License, version 2, which should be included with the source in a file named LICENSE.


Use sbt (simple-build-tool) to build:

$ sbt clean update package-dist

The finished jar will be in dist/.

Counters, Gauges, Metrics, and Labels

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("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.getTemperatureInCelcius() }

    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")

    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.

Stats API

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.

--- everything below here needs work.

Web/socket commands

Commands over the web interface take the form of a "get" request:

GET /<command>[/<parameters...>][.<type>]

which can be performed using 'curl' or 'wget':

$ curl http://localhost:9990/shutdown

while over the plain-text socket, commands are simply typed as-is, followed by a linefeed:

<command>[/<type>] <parameters...>

The result body may be json or plain-text, depending on . Over the web interface, the default is json, but over the socket interface, the default is plain-text. You can override these defaults like so:

$ curl http://localhost:9990/stats/reset.txt


stats/json reset

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 with Configgy.reload()

  • 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 [reset]

    dump server statistics as 4 groups: JVM-specific, gauges, counters, and timings; if "reset" is added, the counters and timings are atomically cleared as they are dumped

  • server_info

    dump server info (server name, version, build, and git revision)

  • threads

    dump stack traces and stats about each currently running thread

Web graphs

The web interface also includes a small graph server that can be used to look at the last hour of data on collected stats. (See "Stats API" below for how to track stats.)

The url


(where PPPP is your admin_http_port) 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.

Admin API

To startup the admin interfaces, call:

ServiceTracker.startAdmin(config, runtimeEnvironment)

RuntimeEnvironment comes from configgy, and is used to display the server info.

Config is usually your root server config (but doesn't have to be) and is used to determine which admin interfaces to start up. If admin_text_port exists, the socket interface will start up there. If admin_http_port exists, the web interface will start up. If neither is set, no admin services will be started.

In order to shutdown your server from the admin port, you must implement Service and register it:


Service contains only the methods shutdown and quiesce, both of which are always called from dedicated temporary threads (so it's okay to do slow things, but be careful of thread safety). You can implement quiesce as a call to shutdown if the distinction makes no sense for your server.

An example:

import com.twitter.ostrich.{Server, ServerInterface}
import net.lag.configgy.{Configgy, RuntimeEnvironment}

object Main extends Service {
  val runtime = new RuntimeEnvironment(getClass)
  val config = Configgy.config
  ServiceTracker.startAdmin(config, runtime)

Config keys

  • admin_http_port

    port for the web server interface (default: no web interface)

  • admin_text_port

    port for the interactive text interface (default: no text interface)

  • admin_jmx_package

    package to use for reporting stats & config through JMX (default: no JMX)

  • admin_timeseries

    true/false, whether to expose the hourly graphs through the web interface (default: true)


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 Kalucki
  • Nick Kallen
  • Pankaj Gupta
  • Robey Pointer
  • Steve Jenson
  • John Corwin

If you make a significant change, please add your name to the list!

Quick Start

This is all you need to know to use the library:

import net.lag.configgy.Configgy
import net.lag.logging.Logger

// load our config file and configure logfiles:

// read hostname and port:
val config = Configgy.config
val hostname = config.getString("hostname", "localhost")
val port = config.getInt("port", 3000)

// log an error:
val log = Logger.get
log.error("Unable to listen on %s:%d!", hostname, port)

// or an exception:
try {
} catch {
  case e: IOException => log.error(e, "IOException while doodling")

The following config file will setup a logfile at debug level, that rolls every night, and also sets a few simple config values:

log {
  filename = "/var/log/pingd.log"
  roll = "daily"
  level = "debug"

hostname = ""
port = 3000

The rest of this README just describes the config file format, the logging options, and how to use the library in more detail.

Basic Use


Logging is configured in a special log block. The main logging options are described below.

  • filename - the file to write log entries into (optional)
  • level - the lowest severity log entry that should be written to the logfile (defaults to INFO) (described below)
  • console - true (on) if logs should be written to the stderr console
  • syslog_host - hostname (or hostname:port) to send syslog formatted log data to (optional)
  • syslog_server_name - server name to attach to log messages when sending to a syslog (optional)
  • roll - when the logfile should be rolled (described below)

Logging severities are:

Severity   Description
=========  ================
FATAL      the server is about to exit
CRITICAL   something happened that is so bad that someone should probably
             be paged
ERROR      an error occurred that may be limited in scope, but was
WARNING    a coder may want to be notified, but the error was probably not
INFO       normal informational logging
DEBUG      coder-level debugging information
TRACE      intensive debugging information

Logfile rolling policies are:

Name     Description
=======  =================
never    always use the same logfile
hourly   roll to a new logfile at the top of every hour
daily    roll to a new logfile at midnight every night
sunday   roll to a new logfile at midnight between saturday and sunday,
           once a week

You can omit a rolling policy, or use policy "never", to avoid rolling the logfiles. For weekly logfile rolling, you may use any day of the week ("monday", "tuesday", etc), not just "sunday".

When a logfile is rolled, the current logfile is renamed to have the date (and hour, if rolling hourly) attached, and a new one is started. So, for example, test.log may become test-20080425.log, and test.log will be reopened as a new file.

So, for example:

log {
  filename = "test.log"
  level = "warning"
  roll = "tuesday"

creates a logfile test.log that captures log entries only at warning, error, critical, or fatal levels. It's rolled once a week, at midnight on Tuesday morning.

None of filename, console, or syslog_host are mutually exclusive, so you can define any or all of those targets, to have log messages sent to any possible combination of places.

Advanced Features

There are a few features you may not use right away, but you'll usually start wanting after the code matures a bit.


There are a handful of options to tune logging more directly:

  • utc - on to log in UTC (previously known as GMT) time instead of local time (default: off)
  • truncate - number of characters to allow in a single log line before eliding with "..." (default: 0 = never truncate)
  • truncate_stack_traces - number of lines of a stack trace to show before eliding (default: 30)
  • syslog_use_iso_date_format - set off to use old-style BSD date format in syslog messages (default: on)
  • use_full_package_names - set on to use full package names in log lines ("net.lag.configgy") instead of the toplevel node ("configgy") (default: off)
  • append - set off to create a new logfile each time the app starts (default: on, meaning to append to any existing logfile)
  • format - sets the overall output format. bare means no formatting. exception_json logs throwables in json format. (default: use a generic formatter, which honors prefix_format)
  • prefix_format - when using the generic formatter, customize the format of log line prefixes (see below)
  • throttle_period_msec, throttle_rate - throttle log messages going to this output. throttle_rate defines the number of lines per throttle_period_msec to allow before squelching. The messages are uniquely identified by their pre-printf formatting pattern.
  • handle_sighup - if set to true, attaches a handler to the HUP signal which causes the logger to reopen its logfile. This allows configgy to work well with external log rotation tools.

The logging options are usually set on the root node of java's "logging tree", at "". You can set options or logging handlers at other nodes by putting them in config blocks inside <log>, and specifying a node name. For example:

log {
  filename = "test.log"
  level = "warning"
  utc = true

  squelch_noisy {
    node = "com.example.libnoise"
    level = "critical"

(You don't have to name the block "squelch_noisy"; they can have any name.)

The "com.example.libnoise" node will log at "critical" level (presumably to silence a noisy library), while everything else will log at "warning" level. You can put any of the logging options inside these blocks, including those for logging to files or syslog nodes. Also, you can have multiple blocks per node, so you can attach multiple output files and handlers to a single log node. In this way you can create multiple logfiles, or have log lines go to multiple places, such as syslog or scribe.

The extra options you can use in these inner blocks are:

  • node - define the log node name (as a string). (default: use the root "" logger)
  • use_parents - whether to fall back to parent log-node configuration (java's setUseParentHandlers) (default: on)

A custom log line prefix format can be set with prefix_format. The date format should be between < angle brackets > in the form used by java's SimpleDateFormat and the rest of the string is passed through java's String.format(), with the log level as the first parameter and the logger name as the second. For example, a format string of:

%.3s [<yyyyMMdd-HH:mm:ss.SSS>] %s:

will generate a log line prefix of:

ERR [20080315-18:39:05.033] julius:

Logging with scribe

A config node can be directed to a scribe server instead of, or in addition to, a file or console. To do this, configure a scribe server on the node:

log {
  scribe_server = "scribe1.corp"
  scribe_category = "echod"
  level = "info"

Configgy will try to keep a persistent connection open to the designated scribe server, and bundle up log messages to limit the number of thrift API requests. If the scribe server disconnects, configgy will automatically try to reconnect. If the server is persistently down, configgy will only retry periodically, and buffer as much as it reasonably can.

The following options can be set for scribe logging:

  • scribe_server - scribe server hostname, with optional port number ("localhost:9463")
  • scribe_category - server name to use (default is "scala")
  • scribe_buffer_msec - how long to buffer log messages before flushing them to the scribe server (default: 100 msec)
  • scribe_max_packet_size - maximum number of log lines to send to the scribe server in a single request (default: 1000)
  • scribe_max_buffer - maximum number of log lines to buffer for scribe before dropping them (default: 10000)
  • scribe_backoff_msec - if the scribe server goes offline, don't try to reconnect more often than this (default: 15000 msec, or 15 sec)


To access a logger from within a class or object, you can usually just use:

import net.lag.logging.Logger
private val log = Logger.get

This creates a Logger object that uses the current class or object's package name as the logging node, so class "" will log to node "" (generally showing "foo" as the name in the logfile). You can also get a logger explicitly by name:

private val log = Logger.get("")

Logger objects wrap everything useful from "java.util.logging.Logger", as well as adding some convenience methods:

// log a string with sprintf conversion:"Starting compaction on level %d...", level)

try {
} catch {
  // log an exception backtrace with the message:
  case x: IOException =>, "I/O exception: %s", x.getMessage)

Each of the log levels (from "fatal" to "trace") has these two convenience methods. You may also use log directly:

log(Logger.DEBUG, "Logging %s at debug level.", name)

An advantage to using sprintf ("%s", etc) conversion, as opposed to:

log(Logger.DEBUG, "Logging " + name + " at debug level.")

is that java & scala perform string concatenation at runtime, even if nothing will be logged because the logfile isn't writing debug messages right now. With sprintf parameters, the arguments are just bundled up and passed directly to the logging level before formatting. If no log message would be written to any file or device, then no formatting is done and the arguments are thrown away. That makes it very inexpensive to include excessive debug logging which can be turned off without recompiling and re-deploying.

If you prefer, there are also variants that take lazy-evaluated parameters, and only evaluate them if logging is active at that level:

log.ifDebug("Login from " + name + " at " + date + ".")

The logging classes are done as an extension to the java.util.logging API, and so if you want to use the java interface directly, you can. Each of the java classes (Logger, Handler, Formatter) is just wrapped by a scala class with a cleaner interface.

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