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

‘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)[source]

Base class for requests monitoring.

abstract async flushPointToMonitoring(points, logger)[source]

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)[source]

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)[source]

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()[source]

Stop plugin.

Close all open connections and ect

async flushPointToMonitoring(points, logger)[source]

Callback for sending a request monitoring data.

Parameters:
  • points – point for monitoring which corresponding the request

  • logger – logger

Return type:

None

async initialize()[source]

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)[source]

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)[source]

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>)[source]

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)[source]

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)[source]

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)[source]

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)[source]

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[source]

Base class for monitoring

abstract flushPoints(points)[source]

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)[source]

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)[source]

Flush point to influx.

Parameters:

points – point

Return type:

None

initializeMonitoring()[source]

Initialize monitoring

Return type:

None

static prepareSettings(credentials, host, port, ssl)[source]

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()[source]

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)[source]

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)[source]

Add points to buffer.

Parameters:

points – points

Return type:

None

static convertPointToDict(point)[source]

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)[source]

Prepare influx client.

initializeScheduler()[source]

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

Return type:

None

stopScheduler()[source]

Stop monitoring.

Return type:

None

updateFlushingPeriod(newPeriod)[source]

Update flushing period :param newPeriod: new period

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

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)[source]

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

Returns:

influx 2.0 write api

Return type:

WriteApi

initializeMonitoring()[source]

Initialize monitoring.

Return type:

None

stopMonitoring()[source]

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)[source]

Container for influx 2.x settings