mock

README

Mock Data Input Plugin

The mock input plugin generates random data based on a selection of different algorithms. For example, it can produce random data between a set of values, fake stock data, sine waves, and step-wise values.

Additionally, users can set the measurement name and tags used to whatever is required to mock their situation.

Configuration

# 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
  ## [[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 Float - generate a random float, inclusive of min and max
• Sine Wave - produce a sine wave with a certain amplitude and period
• Step - always add the step value, negative values accepted
• Stock - generate fake, stock-like price values based on a volatility variable

Example Output

The following example shows all available algorithms configured with an additional two tags as well:

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

Documentation

Index

• type Mock
  • func (m *Mock) Gather(acc telegraf.Accumulator) error
  • func (m *Mock) Init() error
  • func (*Mock) SampleConfig() string

Types

type Mock

type Mock struct {
	MetricName string            `toml:"metric_name"`
	Tags       map[string]string `toml:"tags"`

	Constant []*constant `toml:"constant"`
	Random   []*random   `toml:"random"`
	Step     []*step     `toml:"step"`
	Stock    []*stock    `toml:"stock"`
	SineWave []*sineWave `toml:"sine_wave"`
	// contains filtered or unexported fields
}

func (*Mock) Gather

func (m *Mock) Gather(acc telegraf.Accumulator) error

func (*Mock) Init

func (m *Mock) Init() error

func (*Mock) SampleConfig

func (*Mock) SampleConfig() string