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Statsite Build Status

Statsite is a metrics aggregation server. Statsite is based heavily on Etsy's StatsD https://github.com/etsy/statsd, and is wire compatible.

Features

  • Multiple metric types
    • Key / Value
    • Gauges
    • Counters
    • Timers
    • Sets
  • Efficient summary metrics for timer data:
    • Mean
    • Min/Max
    • Standard deviation
    • Median, Percentile 95, Percentile 99
    • Histograms
  • Dynamic set implementation:
    • Exactly counts for small sets
    • HyperLogLog for large sets
  • Binary protocol
  • TCP, UDP, and STDIN
  • Fast

Architecture

Statsite is designed to be both highly performant, and very flexible. To achieve this, it implements the stats collection and aggregation in pure C, using libev to be extremely fast. This allows it to handle hundreds of connections, and millions of metrics. After each flush interval expires, statsite performs a fork/exec to start a new stream handler invoking a specified application. Statsite then streams the aggregated metrics over stdin to the application, which is free to handle the metrics as it sees fit.

This allows statsite to aggregate metrics and then ship metrics to any number of sinks (Graphite, SQL databases, etc). There is an included Python script that ships metrics to graphite.

Statsite tries to minimize memory usage by not storing all the metrics that are received. Counter values are aggregated as they are received, and timer values are stored and aggregated using the Cormode-Muthurkrishnan algorithm from "Effective Computation of Biased Quantiles over Data Streams". This means that the percentile values are not perfectly accurate, and are subject to a specifiable error epsilon. This allows us to store only a fraction of the samples.

Histograms can also be optionally maintained for timer values. The minimum and maximum values along with the bin widths must be specified in advance, and as samples are recieved the bins are updated. Statsite supports multiple histograms configurations, and uses a longest-prefix match policy.

Handling of Sets in statsite depend on the number of entries received. For small cardinalities (<64 currently), statsite will count exactly the number of unique items. For larger sets, it switches to using a HyperLogLog to estimate cardinalities with high accuracy and low space utilization. This allows statsite to estimate huge set sizes without retaining all the values. The parameters of the HyperLogLog can be tuned to provide greater accuracy at the cost of memory.

The HyperLogLog is based on the Google paper, "HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm".

Install

Download and build from source. This requires scons to be available, available usually through a system package manager. Steps:

$ git clone https://github.com/armon/statsite.git
$ cd statsite
$ pip install SCons  # Uses the Scons build system, may not be necessary
$ make
$ ./statsite

Building the test code may generate errors if libcheck is not available. To build the test code successfully, do the following::

$ cd deps/check-0.9.8/
$ ./configure
$ make
# make install
# ldconfig (necessary on some Linux distros)
$ cd ../../
$ make test

At this point, the test code should build successfully.

Usage

Statsite is configured using a simple INI file. Here is an example configuration file::

[statsite]
port = 8125
udp_port = 8125
log_level = INFO
flush_interval = 10
timer_eps = 0.01
set_eps = 0.02
stream_cmd = python sinks/graphite.py localhost 2003

[histogram_api]
prefix=api
min=0
max=100
width=5

[histogram_default]
prefix=
min=0
max=200
width=20

Then run statsite, pointing it to that file::

statsite -f /etc/statsite.conf

A full list of configuration options is below.

Configuration Options

Each statsite configuration option is documented below. Statsite configuration options must exist in the statsite section of the INI file:

  • tcp_port : Integer, sets the TCP port to listen on. Default 8125. 0 to disable.

  • port: Same as above. For compatibility.

  • udp_port : Integer, sets the UDP port. Default 8125. 0 to disable.

  • bind_address : The address to bind on. Defaults to 0.0.0.0

  • parse_stdin: Enables parsing stdin as an input stream. Defaults to 0.

  • log_level : The logging level that statsite should use. One of: DEBUG, INFO, WARN, ERROR, or CRITICAL. All logs go to syslog, and stderr if that is a TTY. Default is DEBUG.

  • flush_interval : How often the metrics should be flushed to the sink in seconds. Defaults to 10 seconds.

  • timer_eps : The upper bound on error for timer estimates. Defaults to 1%. Decreasing this value causes more memory utilization per timer.

  • set_eps : The upper bound on error for unique set estimates. Defaults to 2%. Decreasing this value causes more memory utilization per set.

  • stream_cmd : This is the command that statsite invokes every flush_interval seconds to handle the metrics. It can be any executable. It should read inputs over stdin and exit with status code 0 on success.

  • input_counter : If set, statsite will count how many commands it received in the flush interval, and the count will be emitted under this name. For example if set to "numStats", then statsite will emit "counter.numStats" with the number of samples it has received.

  • daemonize : Should statsite daemonize. Defaults to 0.

  • pid_file : When daemonizing, where to put the pid file. Defaults to /var/run/statsite.pid

  • binary_stream : Should data be streamed to the stream_cmd in binary form instead of ASCI form. Defaults to 0.

In addition to global configurations, statsite supports histograms as well. Histograms are configured one per section, and the INI section must start with the work histogram. These are the recognized options:

  • prefix : This is the key prefix to match on. The longest matching prefix is used. If the prefix is blank, it is the default for all keys.

  • min : Floating value. The minimum bound on the histogram. Values below this go into a special bucket containing everything less than this value.

  • max: Floating value. The maximum bound on the histogram. Values above this go into a special bucket containing everything more than this value.

  • width : Floating value. The width of each bucket between the min and max.

Each histogram section must specify all options to be valid.

Protocol

By default, Statsite will listen for TCP and UDP connections. A message looks like the following (where the flag is optional)::

key:value|type[|@flag]

Messages must be terminated by newlines (\n).

Currently supported message types:

  • kv - Simple Key/Value.
  • g - Gauge, similar to kv but only the last value per key is retained
  • ms - Timer.
  • c - Counter.
  • s - Unique Set

After the flush interval, the counters and timers of the same key are aggregated and this is sent to the store.

Gauges also support "delta" updates, which are supported by prefixing the value with either a + or a -. This implies you can't explicitly set a gauge to a negative number without first setting it to zero.

Examples:

The following is a simple key/value pair, in this case reporting how many queries we've seen in the last second on MySQL::

mysql.queries:1381|kv

The following is a timer, timing the response speed of an API call::

api.session_created:114|ms

The next example is increments the "rewards" counter by 1::

rewards:1|c

Here we initialize a gauge and then modify its value::

inventory:100|g
inventory:-5|g
inventory:+2|g

Sets count the unique items, so if statsite gets::

users:abe|s
users:zoe|s
users:bob|s
users:abe|s

Then it will emit a count 3 for the number of uniques it has seen.

Writing Statsite Sinks

Statsite only ships with a graphite sink by default, but ANY executable or script can be used as a sink. The sink should read its inputs from stdin, where each metric is in the form::

key|val|timestamp\n

Each metric is separated by a newline. The process should terminate with an exit code of 0 to indicate success.

Here is an example of the simplest possible Python sink:

#!/usr/bin/env python
import sys

lines = sys.stdin.read().split("\n")
metrics = [l.split("|") for l in lines]

for key, value, timestamp in metrics:
    print key, value, timestamp

Binary Protocol

In addition to the statsd compatible ASCII protocol, statsite includes a lightweight binary protocol. This can be used if you want to make use of special characters such as the colon, pipe character, or newlines. It is also marginally faster to process, and may provide 10-20% more throughput.

Each command is sent to statsite over the same ports with this header:

<Magic Byte><Metric Type><Key Length>

Then depending on the metric type, it is followed by either:

<Value><Key>
<Set Length><Key><Set Key>

The "Magic Byte" is the value 0xaa (170). This switches the internal processing from the ASCII mode to binary. The metric type is one of:

  • 0x1 : Key value / Gauge
  • 0x2 : Counter
  • 0x3 : Timer
  • 0x4 : Set
  • 0x5 : Gauge
  • 0x6 : Gauge Delta update

The key length is a 2 byte unsigned integer with the length of the key, INCLUDING a NULL terminator. The key must include a null terminator, and it's length must include this.

If the metric type is K/V, Counter or Timer, then we expect a value and a key. The value is a standard IEEE754 double value, which is 8 bytes in length. The key is provided as a byte stream which is Key Length long, terminated by a NULL (0) byte.

If the metric type is Set, then we expect the length of a set key, provided like the key length. The key should then be followed by an additional Set Key, which is Set Length long, terminated by a NULL (0) byte.

All of these values must be transmitted in Little Endian order.

Here is an example of sending ("Conns", "c", 200) as hex:

0xaa 0x02 0x0600 0x0000000000006940 0x436f6e6e7300

Binary Sink Protocol

It is also possible to have the data streamed to be represented in a binary format. Again, this is used if you want to use the reserved characters. It may also be faster.

Each command is sent to the sink in the following manner:

<Timestamp><Metric Type><Value Type><Key Length><Value><Key>[<Count>]

Most of these are the same as the binary protocol. There are a few. changes however. The Timestamp is sent as an 8 byte unsigned integer, which is the current Unix timestamp. The Metric type is one of:

  • 0x1 : Key value
  • 0x2 : Counter
  • 0x3 : Timer
  • 0x4 : Set
  • 0x5 : Gauge

The value type is one of:

  • 0x0 : No type (Key/Value)
  • 0x1 : Sum (Also used for Sets)
  • 0x2 : Sum Squared
  • 0x3 : Mean
  • 0x4 : Count
  • 0x5 : Standard deviation
  • 0x6 : Minimum Value
  • 0x7 : Maximum Value
  • 0x8 : Histogram Floor Value
  • 0x9 : Histogram Bin Value
  • 0xa : Histogram Ceiling Value
  • 0x80 OR percentile : If the type OR's with 128 (0x80), then it is a percentile amount. The amount is OR'd with 0x80 to provide the type. For example (0x80 | 0x32) = 0xb2 is the 50% percentile or medium. The 95th percentile is (0x80 | 0xdf) = 0xdf.

The key length is a 2 byte unsigned integer representing the key length terminated by a NULL character. The Value is an IEEE754 double. Lastly, the key is a NULL-terminated character stream.

The final <Count> field is only set for histogram values. It is always provided as an unsigned 32 bit integer value. Histograms use the value field to specify the bin, and the count field for the entries in that bin. The special values for histogram floor and ceiling indicate values that were outside the specified histogram range. For example, if the min value was 50 and the max 200, then HISTOGRAM_FLOOR will have value 50, and the count is the number of entires which were below this minimum value. The ceiling is the same but visa versa. For bin values, the value is the minimum value of the bin, up to but not including the next bin.

To enable the binary sink protocol, add a configuration variable binary_stream to the configuration file with the value yes. An example sink is provided in sinks/binary_sink.py.