Monitoring¶

Data for monitoring¶

Now we monitor two types of events for monitoring: request and error. First type is all requests, second is 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-events”

route

concatenation of a request method and a request resource (POST:/events)

status_code

http status code of response

fields

fields

description

request_id

request id

execution_time

request execution time

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

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-events”

route

concatenation of a request method and a request resource (POST:/events)

status_code

http status code of response

error_code

luna error code

fields

fields

description

request_id

request id

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

fields	description
request_id	request id

Every handler can add additional tags or fields.

‘event_copy’ series. Triggered on events copy into database. Each point contains event_count and copy_time.

tags

tag name

description

service

always “luna-events”

status

events copy execution status: 1 means success, 0 - fail

fields

fields

description

copy_time

events copy time

event_count

events count

tag name	description
service	always “luna-events”
status	events copy execution status: 1 means success, 0 - fail

fields	description
copy_time	events copy time
event_count	events count

Database¶

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

Classes¶

Module contains points for monitoring.

class luna_events.crutches_on_wheels.cow.monitoring.points.BaseMonitoringPoint(eventTime)¶

Abstract class for points

eventTime¶

event time as timestamp

Type:: float

abstract property fields: Dict[str, int | float | str]¶

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

Return type:: Dict[str, Union[int, float, str]]
Returns:: dict with fields.

abstract property tags: Dict[str, int | float | str]¶

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

Return type:: Dict[str, Union[int, float, str]]
Returns:: dict with tags.

class luna_events.crutches_on_wheels.cow.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

statusCode¶

status code of a request response.

Type:: int

property fields: Dict[str, int | float | str]¶

Get fields

Returns:: “request_id”
Return type:: dict with following keys

property tags: Dict[str, int | float | str]¶

Get tags

Returns:: “route”, “service”, “status_code”
Return type:: dict with following keys

class luna_events.crutches_on_wheels.cow.monitoring.points.DataForMonitoring(tags=<factory>, fields=<factory>)¶: Class fo storing an additional data for monitoring.

class luna_events.crutches_on_wheels.cow.monitoring.points.InfluxFormatter¶: Format any point filed into inline format

class luna_events.crutches_on_wheels.cow.monitoring.points.MonitoringPointInfluxFormatBuilder(name, bases, namespace, /, **kwargs)¶

Complement point class with explicit fields formatting function for the sake of better performance

To perform type format building target class must have ‘fields’ property return value annotated with TypedDict.

Target class might be configured via ‘Config’ class. Available options:

extraFields: whether class should handle additional fields or not

>>> from typing import TypedDict
>>>
>>> class MonitoringFields(TypedDict):
...     field1: str
...     field2: int
...     field3: float
...     field4: bool
>>>
>>> class BasePoint(BaseMonitoringPoint, metaclass=MonitoringPointInfluxFormatBuilder):
...
...     def __init__(self, fields: dict):
...         self._fields = fields
...
...     @property
...     def tags(self):
...         return {}
...
...     @property
...     def fields(self) -> MonitoringFields:
...         return self._fields
...
>>> class TestPointNoExtra(BasePoint):
...
...     class Config:
...         extraFields = False
...
>>> class TestPointWithExtra(BasePoint):
...     class Config:
...         extraFields = True
>>>
>>>
>>> point1 = TestPointNoExtra({"field1": "data", "field2": 1, "field3": 1.0, "field4": False})
>>> point2 = TestPointWithExtra({"field1": "data", "field2": 1, "field3": 1.0, "field4": False, "extra": True})
>>> print(point1.convertFieldsToInfluxLineProtocol())
field1="data",field2=1i,field3=1.000000,field4=False
>>> print(point2.convertFieldsToInfluxLineProtocol())
field1="data",field2=1i,field3=1.000000,field4=False,extra=True

classmethod buildInfluxFormats(annotations, extraFields)¶

Build map with influx formats for corresponding fields

Parameters:

annotations (dict) – point fields type annotations
extraFields (bool) – whether point uses extra fields or not

Return type:

dict

Returns:

dict of fields with their format

static convertFieldsToInfluxLineProtocolNoExtra(point)¶: Convert point fields into influx line protocol format without extra fields

static convertFieldsToInfluxLineProtocolWithExtra(point)¶: Convert point fields into influx line protocol format with extra fields

static getTypeFormat(_type, _field, extraFields)¶

Get field type format

Parameters:

_type (type) – field type
_field (str) – field name
extraFields (bool) – whether point uses extra fields or not

Return type:

str

Returns:

string format of the field

class luna_events.crutches_on_wheels.cow.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, int | float | str]¶

Get fields.

Return type:: Dict[str, Union[int, float, str]]
Returns:: dict with base fields and additional tags

series: str = 'errors'¶: series “errors”

property tags: Dict[str, int | float | str]¶

Get tags.

Return type:: Dict[str, Union[int, float, str]]
Returns:: dict with base tags, “error_code” and additional tags

class luna_events.crutches_on_wheels.cow.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 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, int | float | str]¶

Get fields.

Return type:: Dict[str, Union[int, float, str]]
Returns:: dict with base fields, “execution_time” and additional tags

series: str = 'requests'¶: series “request”

property tags: Dict[str, int | float | str]¶

Get tags.

Return type:: Dict[str, Union[int, float, str]]
Returns:: dict with base tags and additional tags

luna_events.crutches_on_wheels.cow.monitoring.points.getRoute(resource, method)¶

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

Returns:: {resource}”
Return type:: “{method}

luna_events.crutches_on_wheels.cow.monitoring.points.monitorTime(monitoringData, fieldName)¶

Context manager for timing execution time.

Parameters:

monitoringData (DataForMonitoring) – container for saving result
fieldName (str) – field name

Module implement base class for monitoring

class luna_events.crutches_on_wheels.cow.monitoring.manager.LunaMonitoringManager(settings, pluginManager)¶

Monitoring manager. Sends data to the monitoring storage and monitoring plugins. .. attribute:: settings

monitoring storage settings

async close()¶

Stop monitoring.

Return type:: None

flushPoints(points)¶

Flush point to monitoring.

Parameters:: points (Iterable[~T_MONITORING_POINT]) – point
Return type:: None

async initialize()¶

Initialize monitoring

Return type:: None

class luna_events.crutches_on_wheels.cow.monitoring.manager.MonitoringSettings(*args, **kwargs)¶

Monitoring settings protocol

class InfluxCredentials¶: Monitoring credentials

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

class luna_events.crutches_on_wheels.cow.monitoring.influx_adapter.BaseMonitoringAdapter(settings, flushingPeriod)¶

Base monitoring adapter.

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 (Iterable[BaseMonitoringPoint]) – points
Return type:: None

static convertFieldsToInfluxLineProtocol(fields)¶

Convert field value to influx line protocol format

Parameters:: fields (dict) – dict with values to convert
Return type:: str
Returns:: line protocol string

generatePointStr(point)¶

Generate string from point

Parameters:: point (BaseMonitoringPoint) – point
Return type:: str
Returns:: influx line protocol string

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 :type newPeriod: int :param newPeriod: new period

class luna_events.crutches_on_wheels.cow.monitoring.influx_adapter.InfluxMonitoringAdapter(settings, flushingPeriod)¶

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

bucket¶

influx bucket name

Type:: str

initializeMonitoring()¶

Initialize monitoring.

Return type:: None

async stopMonitoring()¶

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

Return type:: None

class luna_events.crutches_on_wheels.cow.monitoring.influx_adapter.InfluxSettings(url, bucket, organization, token)¶: Container for influx 2.x settings