Monitoring

Data for monitoring

  Now we monitor two types of events for monitoring: request and error. The first type is all requests, second is failed requests only. Every event is a point in the time series. The point is represented as the 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 route status_code	“luna-python-matcher” or “luna-matcher-proxy” concatenation of a request method and a request resource (POST:/matcher) http status code of response

• fields

  fields	description
  request_id execution_time	request id request execution time

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

• tags

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

• fields

  fields	description
  request_id	request id

Every handler can add additional tags or fields.

Database

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

Classes

Module contains points for monitoring’s.

class luna_python_matcher.crutches_on_wheels.cow.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_python_matcher.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

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_python_matcher.crutches_on_wheels.cow.monitoring.points.DataForMonitoring(tags=<factory>, fields=<factory>)

Class fo storing an additional data for monitoring.

class luna_python_matcher.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, 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_python_matcher.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 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_python_matcher.crutches_on_wheels.cow.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_python_matcher.crutches_on_wheels.cow.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_python_matcher.crutches_on_wheels.cow.monitoring.base_monitoring.BaseLunaMonitoring

Base class for monitoring

abstract flushPoints(points)

Flush point to monitoring.

Parameters:

points – point

Return type:

None

class luna_python_matcher.crutches_on_wheels.cow.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_python_matcher.crutches_on_wheels.cow.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_python_matcher.crutches_on_wheels.cow.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_python_matcher.crutches_on_wheels.cow.monitoring.influx_adapter.InfluxSettings(url, bucket, organization, token, ssl)

Container for influx 2.x settings