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  1. Names
    • Describe the measurement being collected
    • Use camelCase
    • Static
    • Succinct
  2. Tags
    • Should be used for dimensional filtering
    • Be careful about combinatorial explosion
    • Tag keys should be static
    • Use id to distinguish between instances
  3. Use Base Units


Describe the Measurement

Use camelCase

The main goal here is to promote consistency, which makes it easier for users. The choice of style is somewhat arbitrary, but camelCase was chosen because:

  • Used by SNMP
  • Used by Java
  • It was commonly used at Netflix when the guideline was written

The exception to this rule is where there is an established common case. For example, with Amazon regions, it is preferred to use us-east-1 rather than usEast1 as it is the more common form.


There should not be any dynamic content in a metric name, such as requests.$APP_NAME. Metric names and tag keys are how users interact with the data, and dynamic values make them difficult to use. Dynamic information is better suited for tag values, such as or status.


Long names should be avoided. In many cases, long names are the result of combining many pieces of information together into a single string. In this case, consider either discarding information that is not useful or encoding the information in tag values.


Historically, tags have been used to play one of two roles:

  • Dimensions. This is the primary use of tags and this feature allows the data to be filtered into subsets by values of interest.
  • Namespace. Similar to packages in Java, this allows grouping related data. This type of usage is discouraged.

As a general rule, it should be possible to use the name as a pivot. If only the name is selected, then the user should be able to use other dimensions to filter the data and successfully reason about the value being shown.

As a concrete example, suppose we have two metrics:

  1. The number of threads currently in a thread pool.
  2. The number of rows in a database table.

Discouraged Approach

Id poolSize = registry.createId("size")
  .withTag("class", "ThreadPool")
  .withTag("id", "server-requests");

Id poolSize = registry.createId("size")
  .withTag("class", "Database")
  .withTag("table", "users");  

In this approach, if you select the name size, then it will match both the ThreadPool and Database classes. This results in a value that is the an aggregate of the number of threads and the number of items in a database, which has no meaning.

Id poolSize = registry.createId("threadpool.size")
  .withTag("id", "server-requests");

Id poolSize = registry.createId("db.size")
  .withTag("table", "users");  

This variation provides enough context, so that if just the name is selected, the value can be reasoned about and is at least potentially meaningful.

This variation provides enough context in the name so that the meaning is more apparent and you can successfully reason about the values. For example, if you select threadpool.size, then you can see the total number of threads in all pools. You can then group by or select an id to further filter the data to a subset in which you have an interest.

Use Base Units

Keep measurements in base units where possible. It is better to have all timers in seconds, disk sizes in bytes, and network rates in bytes/second. This allows any SI unit prefixes applied to tick labels on a graph to have an obvious meaning, such as 1k meaning 1 kilobyte, as opposed to 1 kilo-megabyte.