1
0
Fork 0

Adding upstream version 1.34.4.

Signed-off-by: Daniel Baumann <daniel@debian.org>
This commit is contained in:
Daniel Baumann 2025-05-24 07:26:29 +02:00
parent e393c3af3f
commit 4978089aab
Signed by: daniel
GPG key ID: FBB4F0E80A80222F
4963 changed files with 677545 additions and 0 deletions

View file

@ -0,0 +1,88 @@
# Mock Data Input Plugin
The plugin generates mock-metrics based on different algorithms like sine-wave
functions, random numbers and more with the configured names and tags. Those
metrics are usefull during testing (e.g. processors) or if random data is
required.
⭐ Telegraf v1.22.0
🏷️ testing
💻 all
## Global configuration options <!-- @/docs/includes/plugin_config.md -->
In addition to the plugin-specific configuration settings, plugins support
additional global and plugin configuration settings. These settings are used to
modify metrics, tags, and field or create aliases and configure ordering, etc.
See the [CONFIGURATION.md][CONFIGURATION.md] for more details.
[CONFIGURATION.md]: ../../../docs/CONFIGURATION.md#plugins
## Configuration
```toml @sample.conf
# Generate metrics for test and demonstration purposes
[[inputs.mock]]
## Set the metric name to use for reporting
metric_name = "mock"
## Optional string key-value pairs of tags to add to all metrics
# [inputs.mock.tags]
# "key" = "value"
## One or more mock data fields *must* be defined.
# [[inputs.mock.constant]]
# name = "constant"
# value = value_of_any_type
# [[inputs.mock.random]]
# name = "rand"
# min = 1.0
# max = 6.0
# [[inputs.mock.sine_wave]]
# name = "wave"
# amplitude = 1.0
# period = 0.5
# phase = 20.0
# base_line = 0.0
# [[inputs.mock.step]]
# name = "plus_one"
# start = 0.0
# step = 1.0
# [[inputs.mock.stock]]
# name = "abc"
# price = 50.00
# volatility = 0.2
```
The mock plugin only requires that:
1) Metric name is set
2) One of the data field algorithms is defined
## Available Algorithms
The available algorithms for generating mock data include:
* `constant`: generate a field with the given value of type string, float, int
or bool
* `random`: generate a random float, inclusive of min and max
* `sine_wave`: produce a sine wave with a certain amplitude, period and baseline
* `step`: always add the step value, negative values accepted
* `stock`: generate fake, stock-like price values based on a volatility variable
## Metrics
Metrics are entirely based on the user's own configuration and settings.
## Example Output
The following example shows all available algorithms configured with an
additional two tags as well:
```text
mock_sensors,building=5A,site=FTC random=4.875966794516125,abc=50,wave=0,plus_one=0 1632170840000000000
mock_sensors,building=5A,site=FTC random=5.738651873834452,abc=45.095549448434774,wave=5.877852522924732,plus_one=1 1632170850000000000
mock_sensors,building=5A,site=FTC random=1.0429328917205203,abc=51.928560083072924,wave=9.510565162951535,plus_one=2 1632170860000000000
mock_sensors,building=5A,site=FTC random=5.290188595384418,abc=44.41090520217027,wave=9.510565162951536,plus_one=3 1632170870000000000
mock_sensors,building=5A,site=FTC random=2.0724967227069135,abc=47.212167806890314,wave=5.877852522924733,plus_one=4 1632170880000000000
```