rules_complete.yaml

############################
## Sampling Rules Config ##
############################

# DryRun - If enabled, marks traces that would be dropped given current sampling rules,
# and sends all traces regardless
DryRun: false

# DryRunFieldName - the key to add to use to add to event data when using DryRun mode above, defaults to trace_proxy_kept
DryRunFieldName: trace_proxy_kept

# DeterministicSampler is a section of the config for manipulating the
# Deterministic Sampler implementation. This is the simplest sampling algorithm
# - it is a static sample rate, choosing traces randomly to either keep or send
# (at the appropriate rate). It is not influenced by the contents of the trace.
Sampler: DeterministicSampler

# SampleRate is the rate at which to sample. It indicates a ratio, where one
# sample trace is kept for every n traces seen. For example, a SampleRate of 30
# will keep 1 out of every 30 traces. The choice on whether to keep any specific
# trace is random, so the rate is approximate.
# Eligible for live reload.
SampleRate: 1

dataset1:

  # Note: If your dataset name contains a space, you will have to escape the dataset name
  # using single quotes, such as ['dataset 1']

  # DynamicSampler is a section of the config for manipulating the simple Dynamic Sampler
  # implementation. This sampler collects the values of a number of fields from a
  # trace and uses them to form a key. This key is handed to the standard dynamic
  # sampler algorithm which generates a sample rate based on the frequency with
  # which that key has appeared in the previous ClearFrequencySec seconds.
  Sampler: DynamicSampler

  # SampleRate is the goal rate at which to sample. It indicates a ratio, where
  # one sample trace is kept for every n traces seen. For example, a SampleRate of
  # 30 will keep 1 out of every 30 traces. This rate is handed to the dynamic
  # sampler, who assigns a sample rate for each trace based on the fields selected
  # from that trace.
  SampleRate: 2

  # FieldList is a list of all the field names to use to form the key that will be handed to the dynamic sampler.
  # The combination of values from all of these fields should reflect how interesting the trace is compared to
  # another. A good field selection has consistent values for high-frequency, boring traffic, and unique values for
  # outliers and interesting traffic. Including an error field (or something like HTTP status code) is an excellent
  # choice. Using fields with very high cardinality (like `k8s.pod.id`), is a bad choice. If the combination of
  # fields essentially makes them unique, the dynamic sampler will sample everything. If the combination of fields is
  # not unique enough, you will not be guaranteed samples of the most interesting traces. As an example, consider a
  # combination of HTTP endpoint (high-frequency and boring), HTTP method, and status code (normally boring but can
  # become interesting when indicating an error) as a good set of fields since it will allowing proper sampling
  # of all endpoints under normal traffic and call out when there is failing traffic to any endpoint.
  # For example, in contrast, consider a combination of HTTP endpoint, status code, and pod id as a bad set of
  # fields, since it would result in keys that are all unique, and therefore results in sampling 100% of traces.
  # Using only the HTTP endpoint field would be a **bad** choice, as it is not unique enough and therefore
  # interesting traces, like traces that experienced a `500`, might not be sampled.
  # Field names may come from any span in the trace.
  FieldList:
    - request.method
    - http.target
    - response.status_code

  # UseTraceLength will add the number of spans in the trace in to the dynamic
  # sampler as part of the key. The number of spans is exact, so if there are
  # normally small variations in trace length you may want to leave this off. If
  # traces are consistent lengths and changes in trace length is a useful
  # indicator of traces you'd like to see in OpsRamp, set this to true.
  UseTraceLength: true

  # AddSampleRateKeyToTrace when this is set to true, the sampler will add a field
  # to the root span of the trace containing the key used by the sampler to decide
  # the sample rate. This can be helpful in understanding why the sampler is
  # making certain decisions about sample rate and help you understand how to
  # better choose the sample rate key (aka the FieldList setting above) to use.
  AddSampleRateKeyToTrace: true

  # AddSampleRateKeyToTraceField is the name of the field the sampler will use
  # when adding the sample rate key to the trace. This setting is only used when
  # AddSampleRateKeyToTrace is true.
  AddSampleRateKeyToTraceField: meta.tracing-proxy.dynsampler_key

  # ClearFrequencySec is the name of the field the sampler will use to determine
  # the period over which it will calculate the sample rate. This setting defaults
  # to 30.
  ClearFrequencySec: 60
dataset2:

  # EMADynamicSampler is a section of the config for manipulating the Exponential
  # Moving Average (EMA) Dynamic Sampler implementation. Like the simple DynamicSampler,
  # it attempts to average a given sample rate, weighting rare traffic and frequent
  # traffic differently so as to end up with the correct average.
  #
  # EMADynamicSampler is an improvement upon the simple DynamicSampler and is recommended
  # for most use cases. Based on the DynamicSampler implementation, EMADynamicSampler differs
  # in that rather than compute rate based on a periodic sample of traffic, it maintains an Exponential
  # Moving Average of counts seen per key, and adjusts this average at regular intervals.
  # The weight applied to more recent intervals is defined by `weight`, a number between
  # (0, 1) - larger values weight the average more toward recent observations. In other words,
  # a larger weight will cause sample rates more quickly adapt to traffic patterns,
  # while a smaller weight will result in sample rates that are less sensitive to bursts or drops
  # in traffic and thus more consistent over time.
  #
  # Keys that are not found in the EMA will always have a sample
  # rate of 1. Keys that occur more frequently will be sampled on a logarithmic
  # curve. In other words, every key will be represented at least once in any
  # given window and more frequent keys will have their sample rate
  # increased proportionally to wind up with the goal sample rate.
  Sampler: EMADynamicSampler

  # GoalSampleRate is the goal rate at which to sample. It indicates a ratio, where
  # one sample trace is kept for every n traces seen. For example, a SampleRate of
  # 30 will keep 1 out of every 30 traces. This rate is handed to the dynamic
  # sampler, who assigns a sample rate for each trace based on the fields selected
  # from that trace.
  GoalSampleRate: 2

  # FieldList is a list of all the field names to use to form the key that will be handed to the dynamic sampler.
  # The combination of values from all of these fields should reflect how interesting the trace is compared to
  # another. A good field selection has consistent values for high-frequency, boring traffic, and unique values for
  # outliers and interesting traffic. Including an error field (or something like HTTP status code) is an excellent
  # choice. Using fields with very high cardinality (like `k8s.pod.id`), is a bad choice. If the combination of
  # fields essentially makes them unique, the dynamic sampler will sample everything. If the combination of fields is
  # not unique enough, you will not be guaranteed samples of the most interesting traces. As an example, consider a
  # combination of HTTP endpoint (high-frequency and boring), HTTP method, and status code (normally boring but can
  # become interesting when indicating an error) as a good set of fields since it will allowing proper sampling
  # of all endpoints under normal traffic and call out when there is failing traffic to any endpoint.
  # For example, in contrast, consider a combination of HTTP endpoint, status code, and pod id as a bad set of
  # fields, since it would result in keys that are all unique, and therefore results in sampling 100% of traces.
  # Using only the HTTP endpoint field would be a **bad** choice, as it is not unique enough and therefore
  # interesting traces, like traces that experienced a `500`, might not be sampled.
  # Field names may come from any span in the trace.
  FieldList:
    - request.method
    - http.target
    - response.status_code

  # UseTraceLength will add the number of spans in the trace in to the dynamic
  # sampler as part of the key. The number of spans is exact, so if there are
  # normally small variations in trace length you may want to leave this off. If
  # traces are consistent lengths and changes in trace length is a useful
  # indicator of traces you'd like to see in OpsRamp, set this to true.
  UseTraceLength: true

  # AddSampleRateKeyToTrace when this is set to true, the sampler will add a field
  # to the root span of the trace containing the key used by the sampler to decide
  # the sample rate. This can be helpful in understanding why the sampler is
  # making certain decisions about sample rate and help you understand how to
  # better choose the sample rate key (aka the FieldList setting above) to use.
  AddSampleRateKeyToTrace: true

  # AddSampleRateKeyToTraceField is the name of the field the sampler will use
  # when adding the sample rate key to the trace. This setting is only used when
  # AddSampleRateKeyToTrace is true.
  AddSampleRateKeyToTraceField: meta.tracing-proxy.dynsampler_key

  # AdjustmentInterval defines how often (in seconds) we adjust the moving average from
  # recent observations. Default 15s
  AdjustmentInterval: 15

  # Weight is a value between (0, 1) indicating the weighting factor used to adjust
  # the EMA. With larger values, newer data will influence the average more, and older
  # values will be factored out more quickly.  In mathematical literature concerning EMA,
  # this is referred to as the `alpha` constant.
  # Default is 0.5
  Weight: 0.5

  # MaxKeys, if greater than 0, limits the number of distinct keys tracked in EMA.
  # Once MaxKeys is reached, new keys will not be included in the sample rate map, but
  # existing keys will continue to be be counted. You can use this to keep the sample rate
  # map size under control.
  MaxKeys: 0

  # AgeOutValue indicates the threshold for removing keys from the EMA. The EMA of any key
  # will approach 0 if it is not repeatedly observed, but will never truly reach it, so we have to
  # decide what constitutes "zero". Keys with averages below this threshold will be removed
  # from the EMA. Default is the same as Weight, as this prevents a key with the smallest
  # integer value (1) from being aged out immediately. This value should generally be <= Weight,
  # unless you have very specific reasons to set it higher.
  AgeOutValue: 0.5

  # BurstMultiple, if set, is multiplied by the sum of the running average of counts to define
  # the burst detection threshold. If total counts observed for a given interval exceed the threshold
  # EMA is updated immediately, rather than waiting on the AdjustmentInterval.
  # Defaults to 2; negative value disables. With a default of 2, if your traffic suddenly doubles,
  # burst detection will kick in.
  BurstMultiple: 2

  # BurstDetectionDelay indicates the number of intervals to run after Start is called before
  # burst detection kicks in.
  # Defaults to 3
  BurstDetectionDelay: 3
dataset3:
  Sampler: DeterministicSampler
  SampleRate: 10
dataset4:
  Sampler: RulesBasedSampler
  CheckNestedFields: false
  rule:
    - name: drop healthchecks
      drop: true
      condition:
        - field: http.route
          operator: '='
          value: /health-check
    - name: keep slow 500 errors
      SampleRate: 1
      condition:
        - field: status_code
          operator: '='
          value: 500
        - field: duration_ms
          operator: '>='
          value: 1000.789
    - name: dynamically sample 200 responses
      condition:
        - field: status_code
          operator: '='
          value: 200
      sampler:
        EMADynamicSampler:
          Sampler: EMADynamicSampler
          GoalSampleRate: 15
          FieldList:
            - request.method
            - request.route
          AddSampleRateKeyToTrace: true
          AddSampleRateKeyToTraceField: meta.tracing-proxy.dynsampler_key
    - name: dynamically sample 200 string responses
      condition:
        - field: status_code
          operator: '='
          value: '200'
          datatype: int
      sampler:
        EMADynamicSampler:
          Sampler: EMADynamicSampler
          GoalSampleRate: 15
          FieldList:
            - request.method
            - request.route
          AddSampleRateKeyToTrace: true
          AddSampleRateKeyToTraceField: meta.tracing-proxy.dynsampler_key
    - name: sample traces originating from a service
      Scope: span
      SampleRate: 5
      condition:
        - field: service name
          operator: '='
          value: users
        - field: meta.span_type
          operator: '='
          value: root
    - SampleRate: 10
dataset5:
  Sampler: TotalThroughputSampler
  GoalThroughputPerSec: 100
  FieldList: '[request.method]'