Monitoring

Data for monitoring

Now we monitor two types of events for monitoring: request and * error*. First type is all requests, second is a failed requests only. Every event is a point in the time series. The point is represented as union of the following data:

• series name (now requests and errors)

• start request time

• tags, indexed data in storage, dictionary: keys - string tag names, values - string, integer, float

• fields, non indexed data in storage, dictionary: keys - string tag names, values - string, integer, float

‘Requests’ series. Triggered on every request. Each point contains a data about corresponding request ( execution time and etc).

• tags

  tag name	description
  service	always “luna-handlers”
  route	concatenation of a request method and a request resource (POST:/extractor)
  status_code	http status code of response

• fields

  fields	description
  request_id	request id
  execution_time	request execution time

‘Errors’ series. Triggered on failed request. Each point contains error_code of luna error.

• tags

  tag name	description
  service	always “luna-handlers”
  route	concatenation of a request method and a request resource (POST:/extractor)
  status_code	http status code of response
  error_code	luna error code

• fields

  fields	description
  request_id	request id

Every handler can add additional tags or fields. For example. Handler of resource /handlers/{handlerId}/events adds tag handler_id.

For a resource “/detector”, “/extractor”, “/handlers/{handler_id}/events” there are additional fields:

• fields

  fields	description
  download_images_time	images download from image store time
  load_face_samples_time	load face samples from image-store time
  load_body_samples_time	load body samples from image-store time
  load_images_for_processing_time	load images for processing time
  save_warps_time	save warp to image store
  save_samples_time	save samples to image store time
  save_face_attributes_time	save face attributes to luna-faces time
  save_event_attributes_time	save event attributes to luna-events time
  face_sample_storage_policy_time	save face samples to image store time
  body_sample_storage_policy_time	save body samples to image store time
  image_origin_storage_policy_time	save origin image to image store time
  face_attribute_storage_policy_time	save attributes to luna-faces time
  face_storage_policy_time	save face with avatar to luna-faces time
  match_policy_time	match by list processing time
  event_storage_policy_time	save event to luna-events time
  notification_storage_policy_time	send notification to luna-sender time

‘Usages_statistic’ series. Triggered on every request involving some SDK estimations. Each point contains data on the number of estimations performed.

• tags

  tag name	description
  service	always “luna-handlers”

• fields

  fields	description
  face_detector_usages	face detector usages count
  landmarks68_detector_usages	landmarks68 detector usages count
  head_pose_estimator_usages	head pose estimator usages count
  liveness_estimator_usages	liveness estimator usages count
  mask_estimator_usages	mask estimator usages count
  emotion_estimator_usages	emotion estimator usages count
  mouth_estimator_usages	mouth estimator usages count
  eye_estimator_usages	eyes estimator usages count
  gaze_estimator_usages	gaze estimator usages count
  glasses_estimator_usages	glasses estimator usages count
  face_warp_quality_estimator_usages	face warp quality estimator usages count
  face_basic_attributes_extractor_usages	face basic attributes extractor usages count
  face_descriptor_extractor_usages	face descriptor extractor usages count
  body_detector_usages	body detector estimator usages count
  body_descriptor_extractor_usages	body descriptor extractor usages count
  iso_estimator_usages	iso estimator usages count
  face_quality_estimator_usages	face quality estimator usages count
  body_basic_attributes_estimator_usages	body basic attribute estimator usages count
  body_upper_attributes_estimator_usages	body upper attribute estimator usages count
  body_accessories_estimator_usages	body accessory estimator usages count

‘Licensing’ series. Triggered on each request with liveness estimation if liveness balance expired. Each point contains license check data.

• tags

  tag name	description
  service	always “luna-handlers”
  license_status	license status (“ok”, “warning”, “error”, “exception”)

• fields

  fields	description
  liveness_balance	number of liveness estimations before the license expires
  warnings	license warning messages
  errors	license error messages

Database

Monitoring is implemented as data sending to an influx database. You can setup your database credentials in configuration file in section “monitoring”.

Plugins

You can realize your own plugin for sending monitoring data. See plugins

Module request monitoring plugin example

class luna_handlers.crutches_on_wheels.plugins.plugin_examples.request_monitoring_plugin_example.BaseRequestMonitoringPlugin(app)

Base class for requests monitoring.

abstract async flushPointToMonitoring(points, logger)

All plugins must realize this method.

This function call after end of request

Parameters:

• points – points for monitoring which corresponding the request

• logger – logger

Return type:

None

async handleEvent(points, logger)

Handle event

Parameters:

• *args – positional arg for event handler function

• **kwargs – named arg for event handler function

class luna_handlers.crutches_on_wheels.plugins.plugin_examples.request_monitoring_plugin_example.RequestMonitoringPlugin(app)

Example plugin sends a request data for monitoring to third-party source. Only one instance of this class exist during the program execution.

async close()

Stop plugin.

Close all open connections and ect

async flushPointToMonitoring(points, logger)

Callback for sending a request monitoring data.

Parameters:

• points – point for monitoring which corresponding the request

• logger – logger

Return type:

None

async initialize()

Initialize plugin.

Close all open connections and ect

Classes

Module contains points for monitoring’s.

class luna_handlers.crutches_on_wheels.monitoring.points.BaseMonitoringPoint(eventTime)

Abstract class for points

eventTime

event time as timestamp

Type:

float

abstract property fields: Dict[str, Union[int, float, str]]

Get tags from point. We supposed that fields are not indexing data

Returns:

dict with fields.

Return type:

Dict[str, Union[int, float, str]]

abstract property tags: Dict[str, Union[int, float, str]]

Get tags from point. We supposed that tags are indexing data

Returns:

dict with tags.

Return type:

Dict[str, Union[int, float, str]]

class luna_handlers.crutches_on_wheels.monitoring.points.BaseRequestMonitoringPoint(requestId, resource, method, requestTime, service, statusCode)

Base class for point which is associated with requests.

requestId

request id

Type:

str

route

concatenation of a request method and a request resource

Type:

str

service

service name

Type:

str

requestTime

a request processing start timestamp

Type:

float

statusCode

status code of a request response.

Type:

int

property fields: Dict[str, Union[int, float, str]]

Get fields

Returns:

“request_id”

Return type:

dict with following keys

Return type:

Dict[str, Union[int, float, str]]

property tags: Dict[str, Union[int, float, str]]

Get tags

Returns:

“route”, “service”, “status_code”

Return type:

dict with following keys

Return type:

Dict[str, Union[int, float, str]]

class luna_handlers.crutches_on_wheels.monitoring.points.DataForMonitoring(tags=<factory>, fields=<factory>)

Class fo storing an additional data for monitoring.

class luna_handlers.crutches_on_wheels.monitoring.points.RequestErrorMonitoringPoint(requestId, resource, method, errorCode, service, requestTime, statusCode, additionalTags=None, additionalFields=None)

Request monitoring point is suspended for monitoring requests errors (error codes)

errorCode

error code

Type:

int

additionalTags

additional tags which was specified for the request

Type:

dict

additionalFields

additional fields which was specified for the request

Type:

dict

property fields: Dict[str, Union[int, float, str]]

Get fields.

Returns:

dict with base fields and additional tags

Return type:

Dict[str, Union[int, float, str]]

series: str = 'errors'

series “errors”

property tags: Dict[str, Union[int, float, str]]

Get tags.

Returns:

dict with base tags, “error_code” and additional tags

Return type:

Dict[str, Union[int, float, str]]

class luna_handlers.crutches_on_wheels.monitoring.points.RequestMonitoringPoint(requestId, resource, method, executionTime, requestTime, service, statusCode, additionalTags=None, additionalFields=None)

Request monitoring point is suspended for monitoring all requests and measure a request time and etc.

executionTime

execution time

Type:

float

additionalTags

additional tags which was specified for the request

Type:

dict

additionalFields

additional fields which was specified for the request

Type:

dict

property fields: Dict[str, Union[int, float, str]]

Get fields.

Returns:

dict with base fields, “execution_time” and additional tags

Return type:

Dict[str, Union[int, float, str]]

series: str = 'requests'

series “request”

property tags: Dict[str, Union[int, float, str]]

Get tags.

Returns:

dict with base tags and additional tags

Return type:

Dict[str, Union[int, float, str]]

luna_handlers.crutches_on_wheels.monitoring.points.getRoute(resource, method)

Get a request route, concatenation of a request method and a request resource :param resource: resource :param method: method

Returns:

{resource}”

Return type:

“{method}

Return type:

str

luna_handlers.crutches_on_wheels.monitoring.points.monitorTime(monitoringData, fieldName)

Context manager for timing execution time.

Parameters:

• monitoringData – container for saving result

• fieldName – field name

Module implement base class for monitoring

class luna_handlers.crutches_on_wheels.monitoring.base_monitoring.BaseLunaMonitoring

Base class for monitoring

abstract flushPoints(points)

Flush point to monitoring.

Parameters:

points – point

Return type:

None

class luna_handlers.crutches_on_wheels.monitoring.base_monitoring.LunaRequestInfluxMonitoring(credentials, host='localhost', port=8086, ssl=False, flushingPeriod=1)

Class for sending data which is associated with request to influx .. attribute:: settings

influxdb settings

type:

InfluxSettings

flushingPeriod

period of flushing points (in seconds)

Type:

int

flushPoints(points)

Flush point to influx.

Parameters:

points – point

Return type:

None

initializeMonitoring()

Initialize monitoring

Return type:

None

static prepareSettings(credentials, host, port, ssl)

Prepare influxdb settings :param credentials: database credentials :param host: influx host :param port: influx port :param ssl: use or not ssl for connecting to influx

Returns:

influxdb settings container

Return type:

InfluxSettings

async stopMonitoring()

Stop monitoring.

Return type:

None

Module contains classes for sending a data to an influx monitoring.

class luna_handlers.crutches_on_wheels.monitoring.influx_adapter.BaseMonitoringAdapter(settings, flushingPeriod)

Base monitoring adapter.

client

influx client

Type:

InfluxDBClient

backgroundScheduler

runner for periodic flushing monitoring points

Type:

AsyncIOScheduler

_buffer

list of buffering points which is waiting sending to influx

Type:

List[BaseRequestMonitoringPoint]

flushingPeriod

period of flushing points (in seconds)

Type:

float

logger

logger

Type:

Logger

_influxSettings

current influx settings

Type:

InfluxSettings

_job

sending monitoring data job

Type:

Job

addPointsToBuffer(points)

Add points to buffer.

Parameters:

points – points

Return type:

None

static convertPointToDict(point)

Convert point to influx client point :param point: point

Returns:

• ‘time’ - timestamp in nanoseconds

• ’measurement’ - time series

• ’tags’ - dict of tags (values are str)

• ’fields’ - dict of fields

Return type:

dict

Return type:

dict

abstract static getClient(settings)

Prepare influx client.

initializeScheduler()

Start the loop for sending data from the buffer to monitoring.

Return type:

None

stopScheduler()

Stop monitoring.

Return type:

None

updateFlushingPeriod(newPeriod)

Update flushing period :param newPeriod: new period

class luna_handlers.crutches_on_wheels.monitoring.influx_adapter.InfluxMonitoringAdapter(settings, flushingPeriod)

Influx 2.x adaptor. Suspended to send points to an influxdb

client

influx 2.x client

Type:

InfluxDBClient

bucket

influx bucket name

Type:

str

static getClient(settings)

Initialize influx 2.x client. :param settings: influx 2.x settings

Returns:

influx 2.0 write api

Return type:

WriteApi

initializeMonitoring()

Initialize monitoring.

Return type:

None

stopMonitoring()

Stop monitoring (cancel all request and stop getting new).

Return type:

None

class luna_handlers.crutches_on_wheels.monitoring.influx_adapter.InfluxSettings(url, bucket, organization, token, ssl)

Container for influx 2.x settings