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The source for Datadog's documentation site.

Home Page: http://docs.datadoghq.com

License: Other

Ruby 1.64% Shell 5.50% Python 12.76% JavaScript 33.05% HTML 32.80% Makefile 0.72% SCSS 11.16% CSS 0.44% Mako 0.05% HCL 0.66% Go 1.23%
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documentation's Issues

The difference between graphite metric queries and datadog

In terms of metric naming, we differ a little with Graphite in that a metric query is defined by a metric name and a scope, where a scope is one or more tags. To translate:

<application>.requests.<HTTP Method>.<Handler Class>.<Handler Method>.mean_90

into Datadog, we'd probably say:

<application>.requests.mean_90{http_method:<HTTP Method>, handler_class:<Handler Class>, handler_method:<Handler Method>}

Where <application>.requests.mean_90 is the metric name, and http_method:, handler_class:, handler_method: are tags, so a concrete example might look like:

sync.requests.mean_90{http_method:GET, handler_class:ItemHandler, handler_method:list}

To do aggregation, we can specify an aggregator as part of the metric query:

avg:sync.requests.mean_90{http_method:GET, handler_class:ItemHandler, handler_method:list}

This will graph a single series that's the average of that metric across the intersection of those tags. We support avg, sum, min, max aggregators. If you wanted to see all the possible series for a given tag facet, you can say:

avg:sync.requests.mean_90{handler_class:ItemHandler, handler_method:list} by {http_method}

Which would graph stacked area series for each http_method value like GET, POST, etc.

API navigation bar should always be visible

I like the way the sidebar stays visible for the guides. It would be great it the same was true of the API Reference bar so I could switch languages and jump around without scrolling back to the top.

What are valid tags?

Metric names must start with a letter, and after that may contain alphanumerics, underscores, minuses, colons, periods and slashes. Other characters will get converted to underscores. Tags can be up to 200 characters long and support unicode.

How do I get the list of hosts and their IDs?

Other API endpoints require the host_id to be passed, yet there is no clear way to get these IDs without clicking around on the infrastructure overview.

This will drive API changes, but it's probably a good place to start.

Where is datadog.conf located?

*nix: /etc/dd-agent/datadog.conf
osx (source install): ~/.datadog-agent/agent/datadog.conf
Windows 2008: C:\ProgramData\Datadog
Windows (other): C:\Documents and Settings\All Users\Application Data\Datadog\

Duplicate "happened"

In Counters:

Counters

Counters track how many times something _happened happened_, like the number of database requests or page views.

dog.increment('database.query.count')
dog.increment('page_view.count', 10)

What are valid metric names?

Metric names must start with a letter, and after that may contain ascii alphanumerics, underscore and periods. Other characters will get converted to underscores. There is no max length

How do I share graphs on other sites?

currently we allow the embedding of specific graphs on other sites
if you open the editor on the graph you want to share, and click on the Share tab
you can generate an html snippet you can put on other sites

How do I get the version of the agent?

On linux, < 3.4.0:

cd /usr/share/datadog/agent && python -c 'import config; print config.get_version()'

Linux, >= 3.4.0:

/etc/init.d/datadog-agent status

Windows: ...

Windows: interactively test the agent

Run the agent's shell by navigating to C:\Program Files (x86)\Datadog\Datadog Agent and running shell.exe. From here you can run parts of the agent.

To test IIS:

ipaddress = 'blah'
import wmi
w = wmi.WMI(ipaddress, user=None, password=None)
wmi_cls = w.Win32_PerfFormattedData_W3SVC_WebService(name="_Total")[0]
print wmi_cls.BytesSentPerSec

Document the metric query language and data model

For example, the differences between functions and aggregators:

Yes, min, max and avg aren't functions per se, they're aggregators. We haven't documented our model as well as we should, but we consider functions as transforms of a single metric series, whereas aggregators combine many metric series's across tags. For example, if we had a metric called foo with values:

host:a = 1,1,4,1,1
host:b = 2,2,0,2,2

Using the min aggregator like min:foo{*} would turn the two series into a single series:

1,1,0,1,1

If we added a min function like min(foo{host:a}), we would get just a single value of 1.

If we had min(foo{*}), we'd still need an aggregator, in this case avg is assumed, so that would be:

avg:foo{} = 1.5, 1.5, 2, 1.5, 1.5
min(avg:foo{
}) = 1.5

If we wanted the hosts in tact, we would say min(foo{*} by {host}), then we'd apply the function to each series:

min(host:a) = 1
min(host:b) = 0

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