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Add recipe for wmi_check (#499)
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@mlcooper @olivielpeau
mlcooper authored and olivielpeau committed Feb 13, 2018
1 parent d2c36c3 commit 582bad9
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111 changes: 111 additions & 0 deletions recipes/wmi_check.rb
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include_recipe 'datadog::dd-agent'

# see example configuration file here:
# https://github.com/DataDog/integrations-core/blob/master/wmi_check/conf.yaml.example

# node['datadog']['wmi_check'] =
# {
# "instances": [
# {
# "class": "Win32_OperatingSystem",
# "metrics": [
# [
# "NumberOfProcesses",
# "system.proc.count",
# "gauge"
# ],
# [
# "NumberOfUsers",
# "system.users.count",
# "gauge"
# ]
# ]
# },
# {
# "class": "Win32_PerfFormattedData_PerfProc_Process",
# "metrics": [
# [
# "ThreadCount",
# "my_app.threads.count",
# "gauge"
# ],
# [
# "VirtualBytes",
# "my_app.mem.virtual",
# "gauge"
# ]
# ],
# "filters": [
# {
# "Name": "myapp"
# }
# ],
# "constant_tags": [
# "role:test"
# ]
# },
# {
# "class": "Win32_PerfFormattedData_PerfProc_Process",
# "metrics": [
# [
# "ThreadCount",
# "proc.threads.count",
# "gauge"
# ],
# [
# "VirtualBytes",
# "proc.mem.virtual",
# "gauge"
# ],
# [
# "PercentProcessorTime",
# "proc.cpu_pct",
# "gauge"
# ]
# ],
# "filters": [
# {
# "Name": "app1"
# },
# {
# "Name": "app2"
# },
# {
# "Name": "app3"
# }
# ],
# "tag_by": "Name"
# },
# {
# "class": "Win32_PerfFormattedData_PerfProc_Process",
# "metrics": [
# [
# "IOReadBytesPerSec",
# "proc.io.bytes_read",
# "gauge"
# ]
# ],
# "filters": [
# {
# "Name": "app%"
# }
# ],
# "tag_by": "Name",
# "tag_queries": [
# [
# "IDProcess",
# "Win32_Process",
# "Handle",
# "CommandLine"
# ]
# ]
# }
# ],
# "logs": null
# }

datadog_monitor 'wmi_check' do
init_config node['datadog']['wmi_check']['init_config']
instances node['datadog']['wmi_check']['instances']
logs node['datadog']['wmi_check']['logs']
end
160 changes: 160 additions & 0 deletions spec/integrations/wmi_check_spec.rb
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describe 'datadog::wmi_check' do
context 'config wmi_check' do
expected_yaml = <<-EOF
init_config:
instances:
- class: Win32_OperatingSystem
metrics:
- [NumberOfProcesses, system.proc.count, gauge]
- [NumberOfUsers, system.users.count, gauge]
- class: Win32_PerfFormattedData_PerfProc_Process
metrics:
- [ThreadCount, my_app.threads.count, gauge]
- [VirtualBytes, my_app.mem.virtual, gauge]
filters:
- Name: myapp
constant_tags:
- 'role:test'
- class: Win32_PerfFormattedData_PerfProc_Process
metrics:
- [ThreadCount, proc.threads.count, gauge]
- [VirtualBytes, proc.mem.virtual, gauge]
- [PercentProcessorTime, proc.cpu_pct, gauge]
filters:
- Name: app1
- Name: app2
- Name: app3
tag_by: Name
- class: Win32_PerfFormattedData_PerfProc_Process
metrics:
- [IOReadBytesPerSec, proc.io.bytes_read, gauge]
filters:
- Name: 'app%'
tag_by: Name
tag_queries:
- [IDProcess, Win32_Process, Handle, CommandLine]
logs: ~
EOF

cached(:chef_run) do
ChefSpec::SoloRunner.new(step_into: ['datadog_monitor']) do |node|
node.automatic['languages'] = { 'python' => { 'version' => '2.7.2' } }
node.set['datadog'] = {
api_key: 'someapikey',
wmi_check: {
instances: [
{
class: 'Win32_OperatingSystem',
metrics: [
[
'NumberOfProcesses',
'system.proc.count',
'gauge'
],
[
'NumberOfUsers',
'system.users.count',
'gauge'
]
]
},
{
class: 'Win32_PerfFormattedData_PerfProc_Process',
metrics: [
[
'ThreadCount',
'my_app.threads.count',
'gauge'
],
[
'VirtualBytes',
'my_app.mem.virtual',
'gauge'
]
],
filters: [
{
Name: 'myapp'
}
],
constant_tags: [
'role:test'
]
},
{
class: 'Win32_PerfFormattedData_PerfProc_Process',
metrics: [
[
'ThreadCount',
'proc.threads.count',
'gauge'
],
[
'VirtualBytes',
'proc.mem.virtual',
'gauge'
],
[
'PercentProcessorTime',
'proc.cpu_pct',
'gauge'
]
],
filters: [
{
Name: 'app1'
},
{
Name: 'app2'
},
{
Name: 'app3'
}
],
tag_by: 'Name'
},
{
class: 'Win32_PerfFormattedData_PerfProc_Process',
metrics: [
[
'IOReadBytesPerSec',
'proc.io.bytes_read',
'gauge'
]
],
filters: [
{
Name: 'app%'
}
],
tag_by: 'Name',
tag_queries: [
[
'IDProcess',
'Win32_Process',
'Handle',
'CommandLine'
]
]
}
]
}
}
end.converge(described_recipe)
end

subject { chef_run }

it_behaves_like 'datadog-agent'

it { is_expected.to include_recipe('datadog::dd-agent') }

it { is_expected.to add_datadog_monitor('wmi_check') }

it 'renders expected YAML config file' do
expect(chef_run).to(render_file('/etc/dd-agent/conf.d/wmi_check.yaml').with_content { |content|
expect(YAML.safe_load(content).to_json).to be_json_eql(YAML.safe_load(expected_yaml).to_json)
})
end
end
end
77 changes: 4 additions & 73 deletions templates/default/wmi_check.yaml.erb
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<%= JSON.parse(({'logs' => @logs }).to_json).to_yaml %>

init_config:

instances:
# Each WMI query has 2 required options, `class` and `metrics` and two
# optional options, `filters` and `tag_by`.
#
# `class` is the name of the WMI class, for example Win32_OperatingSystem
# or Win32_PerfFormattedData_PerfProc_Process. You can find many of the
# standard class names on the MSDN docs at
# http://msdn.microsoft.com/en-us/library/windows/desktop/aa394084.aspx.
# The Win32_FormattedData_* classes provide many useful performance counters
# by default.
#
#
# `metrics` is a list of metrics you want to capture, with each item in the
# list being a set of [WMI property name, metric name, metric type].
#
# - The property name is something like `NumberOfUsers` or `ThreadCount`.
# The standard properties are also available on the MSDN docs for each
# class.
#
# - The metric name is the name you want to show up in Datadog.
#
# - The metric type is from the standard choices for all agent checks, such
# as gauge, rate, histogram or counter.
#
#
# `filters` is a list of filters on the WMI query you may want. For example,
# for a process-based WMI class you may want metrics for only certain
# processes running on your machine, so you could add a filter for each
# process name. See below for an example of this case.
#
#
# `tag_by` optionally lets you tag each metric with a property from the
# WMI class you're using. This is only useful when you will have multiple
# values for your WMI query. The examples below show how you can tag your
# process metrics with the process name (giving a tag of "name:app_name").


# Fetch the number of processes and users
- class: Win32_OperatingSystem
metrics:
- [NumberOfProcesses, system.proc.count, gauge]
- [NumberOfUsers, system.users.count, gauge]

# Fetch metrics for a single running application, called myapp
- class: Win32_PerfFormattedData_PerfProc_Process
metrics:
- [ThreadCount, my_app.threads.count, gauge]
- [VirtualBytes, my_app.mem.virtual, gauge]
filters:
- Name: myapp

# Fetch process metrics for a set of processes, tagging by app name.
- class: Win32_PerfFormattedData_PerfProc_Process
metrics:
- [ThreadCount, proc.threads.count, gauge]
- [VirtualBytes, proc.mem.virtual, gauge]
- [PercentProcessorTime, proc.cpu_pct, gauge]
filters:
- Name: app1
- Name: app2
- Name: app3
tag_by: Name

# Fetch process metrics for every available process, tagging by app name.
- class: Win32_PerfFormattedData_PerfProc_Process
metrics:
- [IOReadBytesPerSec, proc.io.bytes_read, gauge]
- [IOWriteBytesPerSec, proc.io.bytes_written, gauge]
tag_by: Name
# Generated by Chef, local modifications will be overwritten

<%= JSON.parse(({ 'instances' => @instances, 'logs' => @logs }).to_json).to_yaml %>

# Nothing to configure here
init_config:

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