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, nonindexed 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-admin”
  route	concatenation of a request method and a request resource (GET:/accounts)
  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-admin”
  route	concatenation of a request method and a request resource (GET:/accounts)
  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.

Database

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

Aggregated statistics

For statistical purposes monitoring data is being aggregated and downsampled. Data includes average response time, total responses count, 95 and 99 percentiles, errors counts, sdk estimators usage. To perform this task influx tasks are used. Each task runs around 1am Moscow time, fetches all points from the previous day and performs required calculations. To change schedule either edit flux scripts in base_scripts/flux before creating tasks or edit tasks in the Influx UI after creating them. Resulting data is stored in the bucket luna_monitoring_aggregated, its created along with the tasks. To create tasks run: python base_scripts/influx2_cli.py create_usage_task –token=”INFLUX TOKEN” –host=localhost –org=luna Additionally, the script supports getting parameters from the configurator: python base_scripts/influx2_cli.py create_usage_task –luna-config http://configurator:5070/1

Classes

Module contains points for monitoring’s.

class luna_admin.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 tags 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_admin.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, 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_admin.crutches_on_wheels.cow.monitoring.points.DataForMonitoring(tags=<factory>, fields=<factory>)

Class fo storing an additional data for monitoring.

class luna_admin.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_admin.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, 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_admin.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_admin.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_admin.crutches_on_wheels.cow.monitoring.base_monitoring.BaseLunaMonitoring

Base class for monitoring

abstract flushPoints(points)

Flush point to monitoring.

Parameters:

points (List[BaseMonitoringPoint]) – point

Return type:

None

class luna_admin.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

async close()

Stop monitoring.

Return type:

None

flushPoints(points)

Flush point to influx.

Parameters:

points (Iterable[BaseMonitoringPoint]) – point

Return type:

None

async initialize()

Initialize monitoring

Return type:

None

static prepareSettings(credentials, host, port, ssl)

Prepare influxdb settings :type credentials: ~T_INFLUX_CREDENTIALS :param credentials: database credentials :type host: str :param host: influx host :type port: int :param port: influx port :type ssl: bool :param ssl: use or not ssl for connecting to influx

Return type:

InfluxSettings

Returns:

influxdb settings container

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

class luna_admin.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

Retruns:

line protocol string

Return type:

str

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_admin.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_admin.crutches_on_wheels.cow.monitoring.influx_adapter.InfluxSettings(url, bucket, organization, token, ssl)

Container for influx 2.x settings