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feat: Add noise plugin (influxdata#10057)
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| Original file line number | Diff line number | Diff line change |
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| # Noise Processor | ||
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| The *Noise* processor is used to add noise to numerical field values. For each field a noise is generated using a defined probability densitiy function and added to the value. The function type can be configured as _Laplace_, _Gaussian_ or _Uniform_. | ||
| Depending on the function, various parameters need to be configured: | ||
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| ## Configuration | ||
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| Depending on the choice of the distribution function, the respective parameters must be set. Default settings are `noise_type = "laplacian"` with `mu = 0.0` and `scale = 1.0`: | ||
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| ```toml | ||
| [[processors.noise]] | ||
| ## Specified the type of the random distribution. | ||
| ## Can be "laplacian", "gaussian" or "uniform". | ||
| # type = "laplacian | ||
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| ## Center of the distribution. | ||
| ## Only used for Laplacian and Gaussian distributions. | ||
| # mu = 0.0 | ||
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| ## Scale parameter for the Laplacian or Gaussian distribution | ||
| # scale = 1.0 | ||
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| ## Upper and lower bound of the Uniform distribution | ||
| # min = -1.0 | ||
| # max = 1.0 | ||
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| ## Apply the noise only to numeric fields matching the filter criteria below. | ||
| ## Excludes takes precedence over includes. | ||
| # include_fields = [] | ||
| # exclude_fields = [] | ||
| ``` | ||
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| Using the `include_fields` and `exclude_fields` options a filter can be configured to apply noise only to numeric fields matching it. | ||
| The following distribution functions are available. | ||
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| ### Laplacian | ||
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| * `noise_type = laplacian` | ||
| * `scale`: also referred to as _diversity_ parameter, regulates the width & height of the function, a bigger `scale` value means a higher probability of larger noise, default set to 1.0 | ||
| * `mu`: location of the curve, default set to 0.0 | ||
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| ### Gaussian | ||
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| * `noise_type = gaussian` | ||
| * `mu`: mean value, default set to 0.0 | ||
| * `scale`: standard deviation, default set to 1.0 | ||
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| ### Uniform | ||
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| * `noise_type = uniform` | ||
| * `min`: minimal interval value, default set to -1.0 | ||
| * `max`: maximal interval value, default set to 1.0 | ||
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| ## Example | ||
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| Add noise to each value the *Inputs.CPU* plugin generates, except for the _usage\_steal_, _usage\_user_, _uptime\_format_, _usage\_idle_ field and all fields of the metrics _swap_, _disk_ and _net_: | ||
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| ```toml | ||
| [[inputs.cpu]] | ||
| percpu = true | ||
| totalcpu = true | ||
| collect_cpu_time = false | ||
| report_active = false | ||
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| [[processors.noise]] | ||
| scale = 1.0 | ||
| mu = 0.0 | ||
| noise_type = "laplacian" | ||
| include_fields = [] | ||
| exclude_fields = ["usage_steal", "usage_user", "uptime_format", "usage_idle" ] | ||
| namedrop = ["swap", "disk", "net"] | ||
| ``` | ||
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| Result of noise added to the _cpu_ metric: | ||
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| ```diff | ||
| - cpu map[cpu:cpu11 host:98d5b8dbad1c] map[usage_guest:0 usage_guest_nice:0 usage_idle:94.3999999994412 usage_iowait:0 usage_irq:0.1999999999998181 usage_nice:0 usage_softirq:0.20000000000209184 usage_steal:0 usage_system:1.2000000000080036 usage_user:4.000000000014552] | ||
| + cpu map[cpu:cpu11 host:98d5b8dbad1c] map[usage_guest:1.0078071583066057 usage_guest_nice:0.523063861602435 usage_idle:95.53920223476884 usage_iowait:0.5162661526251292 usage_irq:0.7138529816101375 usage_nice:0.6119678488887954 usage_softirq:0.5573585443688622 usage_steal:0.2006120911289802 usage_system:1.2954475820198437 usage_user:6.885664792615023] | ||
| ``` |
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| Original file line number | Diff line number | Diff line change |
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| package noise | ||
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| import ( | ||
| "fmt" | ||
| "math" | ||
| "reflect" | ||
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| "github.com/influxdata/telegraf" | ||
| "github.com/influxdata/telegraf/filter" | ||
| "github.com/influxdata/telegraf/plugins/processors" | ||
| "gonum.org/v1/gonum/stat/distuv" | ||
| ) | ||
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| const ( | ||
| defaultScale = 1.0 | ||
| defaultMin = -1.0 | ||
| defaultMax = 1.0 | ||
| defaultMu = 0.0 | ||
| defaultNoiseType = "laplacian" | ||
| ) | ||
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| const sampleConfig = ` | ||
| ## Specified the type of the random distribution. | ||
| ## Can be "laplacian", "gaussian" or "uniform". | ||
| # type = "laplacian | ||
| ## Center of the distribution. | ||
| ## Only used for Laplacian and Gaussian distributions. | ||
| # mu = 0.0 | ||
| ## Scale parameter for the Laplacian or Gaussian distribution | ||
| # scale = 1.0 | ||
| ## Upper and lower bound of the Uniform distribution | ||
| # min = -1.0 | ||
| # max = 1.0 | ||
| ## Apply the noise only to numeric fields matching the filter criteria below. | ||
| ## Excludes takes precedence over includes. | ||
| # include_fields = [] | ||
| # exclude_fields = [] | ||
| ` | ||
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| type Noise struct { | ||
| Scale float64 `toml:"scale"` | ||
| Min float64 `toml:"min"` | ||
| Max float64 `toml:"max"` | ||
| Mu float64 `toml:"mu"` | ||
| IncludeFields []string `toml:"include_fields"` | ||
| ExcludeFields []string `toml:"exclude_fields"` | ||
| NoiseType string `toml:"type"` | ||
| Log telegraf.Logger `toml:"-"` | ||
| generator distuv.Rander | ||
| fieldFilter filter.Filter | ||
| } | ||
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| func (p *Noise) SampleConfig() string { | ||
| return sampleConfig | ||
| } | ||
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| func (p *Noise) Description() string { | ||
| return "Adds noise to numerical fields" | ||
| } | ||
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| // generates a random noise value depending on the defined probability density | ||
| // function and adds that to the original value. If any integer overflows | ||
| // happen during the calculation, the result is set to MaxInt or 0 (for uint) | ||
| func (p *Noise) addNoise(value interface{}) interface{} { | ||
| n := p.generator.Rand() | ||
| switch v := value.(type) { | ||
| case int: | ||
| case int8: | ||
| case int16: | ||
| case int32: | ||
| case int64: | ||
| if v > 0 && (n > math.Nextafter(float64(math.MaxInt64), 0) || int64(n) > math.MaxInt64-v) { | ||
| p.Log.Debug("Int64 overflow, setting value to MaxInt64") | ||
| return int64(math.MaxInt64) | ||
| } | ||
| if v < 0 && (n < math.Nextafter(float64(math.MinInt64), 0) || int64(n) < math.MinInt64-v) { | ||
| p.Log.Debug("Int64 (negative) overflow, setting value to MinInt64") | ||
| return int64(math.MinInt64) | ||
| } | ||
| return v + int64(n) | ||
| case uint: | ||
| case uint8: | ||
| case uint16: | ||
| case uint32: | ||
| case uint64: | ||
| if n < 0 { | ||
| if uint64(-n) > v { | ||
| p.Log.Debug("Uint64 (negative) overflow, setting value to 0") | ||
| return uint64(0) | ||
| } | ||
| return v - uint64(-n) | ||
| } | ||
| if n > math.Nextafter(float64(math.MaxUint64), 0) || uint64(n) > math.MaxUint64-v { | ||
| p.Log.Debug("Uint64 overflow, setting value to MaxUint64") | ||
| return uint64(math.MaxUint64) | ||
| } | ||
| return v + uint64(n) | ||
| case float32: | ||
| return v + float32(n) | ||
| case float64: | ||
| return v + n | ||
| default: | ||
| p.Log.Debugf("Value (%v) type invalid: [%v] is not an int, uint or float", v, reflect.TypeOf(value)) | ||
| } | ||
| return value | ||
| } | ||
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| // Creates a filter for Include and Exclude fields and sets the desired noise | ||
| // distribution | ||
| func (p *Noise) Init() error { | ||
| fieldFilter, err := filter.NewIncludeExcludeFilter(p.IncludeFields, p.ExcludeFields) | ||
| if err != nil { | ||
| return fmt.Errorf("creating fieldFilter failed: %v", err) | ||
| } | ||
| p.fieldFilter = fieldFilter | ||
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| switch p.NoiseType { | ||
| case "", "laplacian": | ||
| p.generator = &distuv.Laplace{Mu: p.Mu, Scale: p.Scale} | ||
| case "uniform": | ||
| p.generator = &distuv.Uniform{Min: p.Min, Max: p.Max} | ||
| case "gaussian": | ||
| p.generator = &distuv.Normal{Mu: p.Mu, Sigma: p.Scale} | ||
| default: | ||
| return fmt.Errorf("unknown distribution type %q", p.NoiseType) | ||
| } | ||
| return nil | ||
| } | ||
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| func (p *Noise) Apply(metrics ...telegraf.Metric) []telegraf.Metric { | ||
| for _, metric := range metrics { | ||
| for _, field := range metric.FieldList() { | ||
| if !p.fieldFilter.Match(field.Key) { | ||
| continue | ||
| } | ||
| field.Value = p.addNoise(field.Value) | ||
| } | ||
| } | ||
| return metrics | ||
| } | ||
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| func init() { | ||
| processors.Add("noise", func() telegraf.Processor { | ||
| return &Noise{ | ||
| NoiseType: defaultNoiseType, | ||
| Mu: defaultMu, | ||
| Scale: defaultScale, | ||
| Min: defaultMin, | ||
| Max: defaultMax, | ||
| } | ||
| }) | ||
| } |
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