StatsD¶

Buckets¶

In StatsD, whether it’s a counter, a timing, or a gauge, each metric is placed in a bucket. A bucket is just a representative name for a metric that acts as the key used to store it. When using the statsd Librato backend, each bucket is used as the metric name when that bucket is submitted to Librato Metrics. Therefore, users should ensure that buckets follow the same naming conventions for Librato Metrics metric names and users should not use the same name for a counter and a gauge, for example.

Counting¶

One of the more basic use cases for StatsD is counting the number of times an event occurs. You might count every time a user signs in, every time an application controller is invoked, or number of elements received in POST requests. Using a statsd client you simply invoke the increment operation each time you want to count something. You can specify an integer increment value, or let it default to one, and the client will send that increment to the statsd daemon over UDP. Multiple entities (processes or servers) can increment a single counter and the statsd daemon will update the total count of the counter bucket. On each flush interval statsd will push the current value of each counter to the upstream metrics service.

When used with Librato’s backend, StatsD will push counter metrics to Librato as gauges. The gauge value will represent the aggregate of all increment and decrement operations since the last flush interval. For example, if you perform ten increment(1) operations within a flush interval, the gauge value will be ‘10’ for that interval of time. When the measurements are rolled up to the higher level resolutions, the rollups will still be an aggregate of all operations during that period of time.

Timing¶

Oftentimes you’ll want to record a sampling of a particular metric multiple times and track the average rate of those samplings over time. For example, you might track average response time to your web application by sampling how long each request takes. StatsD supports this type of sampling with the timing interface. While it is commonly used for tracking values that are actual times (e.g., nginx response time), it can also be used to sample any type of value, e.g. the byte size of every nginx response. Statsd clients send each sampled value to the statsd daemon.

Internally, statsd keeps each timing sample point until the next flush interval. At the flush interval, statsd will record the min, max, sum, and count for each timing bucket. Using the Librato backend, these values are composed into the complex gauge type and sent to Librato Metrics as a gauge.

Statsd also supports the capability to calculate an arbitrary number of percentiles for timing buckets. By default, the 90th percentile is automatically calculated for each timing bucket, but the user can override that with one or more percentile thresholds. The Librato backend will publish a complex gauge measurement for each defined percentile threshold, by suffixing the percentile onto the metric name. For example, for the metric name api-response-times, the 90th percentile will be sent as the additional metric api-response-times.90. The percentile gauge measurement will include the sum of all values below the percentile, the max value at the percentile, and the count number of samples below the percentile.

Gauges¶

Statsd also supports the concept of gauges. In Statsd, gauges are single metric readings that are recorded and published to the upstream service. They are different from timings in that only the last gauge reading in a single flush interval is sent to the upstream service. This can be useful if you want to track the current temperature or the current price of a stock where only the most recent version is required in a given flush interval. However, for anything that is request driven – requiring measuring samples on each request – the timing interface is preferable.

The Librato backend will submit statsd gauge reading as single-value Librato Metrics gauges. At higher rollups levels those single-value readings will be combined into complex gauges that can be used to track averages across the longer rollup periods.

Sets¶

Sets are a relatively new concept in recent versions of StatsD. Sets track the number of unique elements belonging to a group. This could be used to track the number of unique visitors to your site at any point in time. At each flush interval, the Librato statsd backend will push the number of unique elements in the set as a single gauge value. Be aware that if you are tracking the same set across multiple statsd servers, there is no guarantee of uniqueness across the individual statsd servers.

Setting a source name¶

By default, StatsD will set the source name for all metrics to the hostname of the node that it is running on. If you would like to override that, just set the “source” parameter in the “librato” section of the configuration file.

Enabling per-metric source names¶

In addition to setting a default source name for all metrics sent by the StatsD daemon, you can now configure source names on a per-metric basis. See this section of the README file for instructions on enabling per-metric sources.

Reducing zero-fill measurements¶

Some Statsd backends require that metrics are reported at fixed frequencies. This means that by default Statsd will push zeroes for metrics that haven’t had an update during a flush interval. Librato doesn’t require that, so to reduce the number of measurements that Statsd will push to your Librato account (and hey, that’s extra cost) you can tell Statsd to not push idle stats. See this section of the README for instructions.

Upgrading from the older Statsd backend¶

If you are upgrading from the statsd-librato-backend before version 0.1.0, the default representation for counter metrics has changed. Starting with 0.1.0, statsd counters are now represented as Librato gauges by default. If you were using the default configuration prior to 0.1.0, then you may run into conflicts when you try to push statsd counter metrics to Librato as gauges. To fix this, you have two options: 1. Keep the prior behavior of sending statsd counters as Librato counters. Just set the countersAsGauges configuration variables to false in your statsd config. 2. After upgrading to 0.1.0, remove all counter metrics that were published by statsd. You can use the API pattern DELETE route to mass delete metrics. To delete only counter metrics, add the parameter metric_type=counter.