NewSegments

Description

'New Segments' verses configure Mona to find new segments in the data, meaning they started appearing in the data only lately and did not exist earlier. The period in which a new segment is searched for is configurable to support late updates.

Basic Params

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cadence

Name

Description

Type

Default

cadence

The cadence for evaluation of this verse. Only the following cadences are valid: Minutes: 1m, 5m, 10m, 15m, 20m, 30m. Hours: 1h, 2h, 3h, 4h, 6h, 8h, 12h. Days: 1d, 2d, 3d, 4d, 5d, 6d. Weeks: 1w, 2w, 3w, 4w, 5w.

CadenceType

1d

{ "cadence": "6h" }
default_urgency

Name

Description

Type

Default

default_urgency

The urgency class for insights created using this verse. Currently supports two values: "normal" (default) and "high". If set to "normal", then specific thresholds for "high" urgency can be set using other parameters prefixed with "highurgency". If set to "high", then threshold parameters prefixed with "highurgency" are not considered at all - since all insights of this verse will be considered as having a "high" urgency.

Urgency

normal

{ "default_urgency": "high" }
description

Name

Description

Type

Default

description

Verse description.

str

{ "description": "searches for asc drifts in output_score" }
min_segment_size

Name

Description

Type

Default

min_segment_size

Minimal segment size which a segment must have in order to be considered in the search.

PositiveInt

1

{ "min_segment_size": 100 }
min_segment_size_fraction

Name

Description

Type

Default

min_segment_size_fraction

Minimal segment size in fraction from baseline segment, which a segment must have in order to be considered in the search.

InclusiveFraction

0

{ "min_segment_size_fraction": 0.05 }
name

Name

Description

Type

Default

name

The name of the verse. If missing, this field defaults to "<stanza's name><verse's type>". Please note, a verse's name must be different from other verses in the same stanza. Therefore, in cases where there is more than one verse of the same type, using the default name ("<stanza's name><verse's type>") is not supported and custom names have to be provided for these verses.

None

None

{ "name": "confidence_outliers" }
segment_by

Name

Description

Type

Default

segment_by

The dimensions to use to segment the data in order to search for anomalies. This list must be a sublist of all arc class' dimensions. Limiting the possible values of a specific segmentation field on which insights can be generated can be done using the "avoid_values" and the "include_only_values" keys in the segmentation JSON object, as seen in the example.

SegmentationsListType

[]

{ "segment_by": [ "city", "bot_id", {"name": "provider-code", "avoid_values": ["zoom"]}, {"name": "selected-language", "avoid_values": ["eng", "spa"]}, {"name": "country", "include_only_values": ["jpn"]} ] }
time_period

Name

Description

Type

Default

time_period

Latest time period to look for new segments in. Expected format is "" where can be any positive integer, and options currently include: "d" (days), or "w" (weeks). e.g, "1d" means 1 day period.

TimePeriod

1d

{ "time_period": "1w" }

Advanced Misc Params

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backfill_points

Name

Description

Type

Default

backfill_points

Number of consecutive time periods backwards to search for new segments. This is useful if some of the data is delivered with a delay, and we still want to test whether or not in a previous time_period had new segments we have missed earlier. The difference between using this to increasing time_period, is that the new segment insights will include the time_period in which the new segment was found.

int

1

{ "backfill_points": 10 }
disabled

Name

Description

Type

Default

disabled

If set to True - this verse won't be used when searching for new insights.

bool

False

{ "disabled": true }
expire_after

Name

Description

Type

Default

expire_after

Insights detected by this verse will continue to be considered active for at least this amount of time after the last time they were detected.

TimePeriod

3d

{ "expire_after": "2d" }
timezone

Name

Description

Type

Default

timezone

The timezone used to aggregate daily data points. Accepts any IANA time zone ID: (https://en.wikipedia.org/wiki/List_of_tz_database_time_zones)

Timezone

UTC

{ "timezone": "Asia/Hong_Kong" }

Anomaly Thresholds Params

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high_urgency_min_anomaly_level

Name

Description

Type

Default

high_urgency_min_anomaly_level

Threshold for separating between "high" and "normal" urgency insights with regards to min_anomaly_level. See "min_anomaly_level" param for more details on the functionality of this param.

PositiveFloatOrNone

None

{ "high_urgency_min_anomaly_level": 1.5 }
high_urgency_min_score

Name

Description

Type

Default

high_urgency_min_score

Threshold for separating between "high" and "normal" urgency insights with regards to min_score. See "min_score" param for more details on the functionality of this param.

FloatOrNone

None

{ "high_urgency_min_score": 20 }

Data Filtering Params

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avoid_segmenting_on_missing

Name

Description

Type

Default

avoid_segmenting_on_missing

When true, insights will not be generated for segments which are (partially or fully) defined by a missing field.

bool

False

{ "avoid_segmenting_on_missing": true }
baseline_segment

Name

Description

Type

Default

baseline_segment

The baseline segment of this verse. This segment defines "the world" as far as this verse is concerned. Only data from this segment will be considered when finding insights.

Segment

{}

{ "baseline_segment": { "model_version": [ { "value": "V1" } ] } }
enhance_exclude_segments

Name

Description

Type

Default

enhance_exclude_segments

If True, when exclude segments are added to any level of configuration (either in the verse, the stanza or the stanzas_global_defaults) they are ADDED to the excluded segments of higher level defaults, if exists any. For example, if we have in stanzas_global_default a single excluded segment of {dimensionA: MISSING}, and the stanza (or verse) has a single excluded segment of {dimensionB: 0}, then if enhance_exclude_segments is True, the excluded segments will include both {dimensionA: MISSING} and {dimensionB: 0} and will filter either one. Otherwise (if enhance_exclude_segments is False) it will be overridden to just the one segment in the verse {dimensionB: 0}.

bool

False

{ "enhance_exclude_segments": true }
exclude_segments

Name

Description

Type

Default

exclude_segments

Segments to exclude in the baseline of this verse. Each data we search for will not include these segments - both tested segments as well as any benchmarks used to find the anomalies. Notice that whether or not this param will override definitions for exclude_segments in other levels is decided by enhance_exclude_segments.

SegmentsListType

[]

{ "exclude_segments": [ { "text_length": [ { "min_value": 0, "max_value": 100 } ] } ] }

Segmentation Params

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always_segment_baseline_by

Name

Description

Type

Default

always_segment_baseline_by

A list of dimensions to always segment the baseline segment by. This is useful when separating the world to completely unrelated parts - e.g., in a case where you have a different model developed for each customer and there's no need to look for insights across different customers. Limiting the possible values of a specific segmentation field on which insights can be generated can be done using the "avoid_values" and the "include_only_values" keys in the segmentation JSON object, as seen in the example.

SegmentationsListType

[]

{ "always_segment_baseline_by": [ "country", {"name": "city", "avoid_values": ["Tel Aviv"]}, ] }
avoid_segmenting_on_missing

Name

Description

Type

Default

avoid_segmenting_on_missing

When true, insights will not be generated for segments which are (partially or fully) defined by a missing field.

bool

False

{ "avoid_segmenting_on_missing": true }
max_segment_by_depth

Name

Description

Type

Default

max_segment_by_depth

The maximum number of fields Mona should combine to create sub-segments to search in. Baseline segment fields and parent fields are "free", and are not counted for depth. Notice this parameter has a exponential effect on the performance and should be kept within SLAs.

PositiveInt

2

{ "max_segment_by_depth": 3 }
min_segment_by_depth

Name

Description

Type

Default

min_segment_by_depth

The minimum number of fields Mona should combine to create sub-segments to search in.

NonNegativeInt

0

{ "min_segment_by_depth": 1 }
segment_by

Name

Description

Type

Default

segment_by

The dimensions to use to segment the data in order to search for anomalies. This list must be a sublist of all arc class' dimensions. Limiting the possible values of a specific segmentation field on which insights can be generated can be done using the "avoid_values" and the "include_only_values" keys in the segmentation JSON object, as seen in the example.

SegmentationsListType

[]

{ "segment_by": [ "city", "bot_id", {"name": "provider-code", "avoid_values": ["zoom"]}, {"name": "selected-language", "avoid_values": ["eng", "spa"]}, {"name": "country", "include_only_values": ["jpn"]} ] }

Size Thresholds Params

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baseline_min_segment_size

Name

Description

Type

Default

baseline_min_segment_size

Minimal segment size for the baseline segment.

PositiveFloat

1

{ "baseline_min_segment_size": 100 }
high_urgency_baseline_min_segment_size

Name

Description

Type

Default

high_urgency_baseline_min_segment_size

Threshold for separating between "high" and "normal" urgency insights with regards to baseline_min_segment_size. See "baseline_min_segment_size" param for more details on the functionality of this param.

PositiveFloatOrNone

None

{ "high_urgency_baseline_min_segment_size": 1000 }
high_urgency_min_segment_size

Name

Description

Type

Default

high_urgency_min_segment_size

Threshold for separating between "high" and "normal" urgency insights with regards to min_segment_size. See "min_segment_size" param for more details on the functionality of this param.

PositiveIntOrNone

None

{ "high_urgency_min_segment_size": 1000 }
high_urgency_min_segment_size_fraction

Name

Description

Type

Default

high_urgency_min_segment_size_fraction

Threshold for separating between "high" and "normal" urgency insights with regards to min_segment_size_fraction. See "min_segment_size_fraction" param for more details on the functionality of this param.

InclusiveFractionOrNone

None

{ "high_urgency_min_segment_size_fraction": 0.2 }
max_segment_size

Name

Description

Type

Default

max_segment_size

Maximal segment size which a segment must have (bigger segments won't be considered in the search). Leave empty to not have such a threshold.

PositiveIntOrNone

None

{ "max_segment_size": 10000 }
max_segment_size_fraction

Name

Description

Type

Default

max_segment_size_fraction

Maximal segment size in fraction from baseline segment, which a segment must have. Leave empty to not have such a threshold.

NonInclusiveFractionOrNone

None

{ "max_segment_size_fraction": 0.2 }
min_segment_size

Name

Description

Type

Default

min_segment_size

Minimal segment size which a segment must have in order to be considered in the search.

PositiveInt

1

{ "min_segment_size": 100 }
min_segment_size_fraction

Name

Description

Type

Default

min_segment_size_fraction

Minimal segment size in fraction from baseline segment, which a segment must have in order to be considered in the search.

InclusiveFraction

0

{ "min_segment_size_fraction": 0.05 }

Time Related Params

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cadence

Name

Description

Type

Default

cadence

The cadence for evaluation of this verse. Only the following cadences are valid: Minutes: 1m, 5m, 10m, 15m, 20m, 30m. Hours: 1h, 2h, 3h, 4h, 6h, 8h, 12h. Days: 1d, 2d, 3d, 4d, 5d, 6d. Weeks: 1w, 2w, 3w, 4w, 5w.

CadenceType

1d

{ "cadence": "6h" }
expire_after

Name

Description

Type

Default

expire_after

Insights detected by this verse will continue to be considered active for at least this amount of time after the last time they were detected.

TimePeriod

3d

{ "expire_after": "2d" }
time_period

Name

Description

Type

Default

time_period

Latest time period to look for new segments in. Expected format is "" where can be any positive integer, and options currently include: "d" (days), or "w" (weeks). e.g, "1d" means 1 day period.

TimePeriod

1d

{ "time_period": "1w" }
timezone

Name

Description

Type

Default

timezone

The timezone used to aggregate daily data points. Accepts any IANA time zone ID: (https://en.wikipedia.org/wiki/List_of_tz_database_time_zones)

Timezone

UTC

{ "timezone": "Asia/Hong_Kong" }

Urgency Params

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default_urgency

Name

Description

Type

Default

default_urgency

The urgency class for insights created using this verse. Currently supports two values: "normal" (default) and "high". If set to "normal", then specific thresholds for "high" urgency can be set using other parameters prefixed with "highurgency". If set to "high", then threshold parameters prefixed with "highurgency" are not considered at all - since all insights of this verse will be considered as having a "high" urgency.

Urgency

normal

{ "default_urgency": "high" }
high_urgency_baseline_min_segment_size

Name

Description

Type

Default

high_urgency_baseline_min_segment_size

Threshold for separating between "high" and "normal" urgency insights with regards to baseline_min_segment_size. See "baseline_min_segment_size" param for more details on the functionality of this param.

PositiveFloatOrNone

None

{ "high_urgency_baseline_min_segment_size": 1000 }
high_urgency_min_anomaly_level

Name

Description

Type

Default

high_urgency_min_anomaly_level

Threshold for separating between "high" and "normal" urgency insights with regards to min_anomaly_level. See "min_anomaly_level" param for more details on the functionality of this param.

PositiveFloatOrNone

None

{ "high_urgency_min_anomaly_level": 1.5 }
high_urgency_min_score

Name

Description

Type

Default

high_urgency_min_score

Threshold for separating between "high" and "normal" urgency insights with regards to min_score. See "min_score" param for more details on the functionality of this param.

FloatOrNone

None

{ "high_urgency_min_score": 20 }
high_urgency_min_segment_size

Name

Description

Type

Default

high_urgency_min_segment_size

Threshold for separating between "high" and "normal" urgency insights with regards to min_segment_size. See "min_segment_size" param for more details on the functionality of this param.

PositiveIntOrNone

None

{ "high_urgency_min_segment_size": 1000 }
high_urgency_min_segment_size_fraction

Name

Description

Type

Default

high_urgency_min_segment_size_fraction

Threshold for separating between "high" and "normal" urgency insights with regards to min_segment_size_fraction. See "min_segment_size_fraction" param for more details on the functionality of this param.

InclusiveFractionOrNone

None

{ "high_urgency_min_segment_size_fraction": 0.2 }
high_urgency_require_all_criteria

Name

Description

Type

Default

high_urgency_require_all_criteria

Decide if to use 'AND'/'OR' condition between all high_urgency threshold params.

bool

True

{ "high_urgency_require_all_criteria": false }

Visuals and Enrichments Params

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field_vectors

Name

Description

Type

Default

field_vectors

This attribute lists metric vectors for the FE to show on an insight card of this verse. A value in this field can either be a string (in which case the string should correspond to a kapi_vector name in the config) or an array (in which case the array should be treated as an ad-hoc kapi vector defined specifically for this verse).

FieldVectorsList

[]

{ "field_vectors": [ "field_vector_group_1", "field_vector_group_2", "field_vector_group_3" ] }
investigate_no_drill

Name

Description

Type

Default

investigate_no_drill

Dictates the link to the investigations page to add to the found insights. If True, the link will point to investigations page with a drilldown to the segment that was found. If it's false the link will point to the investigations page without drilldown, but with the found segment selected so it can be compared with a benchmark of a higher level.

bool

False

{ "investigate_no_drill": true }

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