Monitoring

The Metrics module in ASAB serves to produce data - metrics. It does not store nor analyze the data. To get some overview, you must collect the metrics in a time-series database, or choose some custom way of monitoring. InfluxDB and Prometheus databases are supported by ASAB, and several endpoints can be used for data monitoring or collecting as well.

InfluxDB

Metrics can be collected in the Influx time-series database. Metrics are being sent in 60s intervals to configured Influx instance.

Configuration example

[asab:metrics]
target=influxdb

[asab:metrics:influxdb]
url=http://localhost:8086/
bucket=my_bucket
org=my_org
token=my_token

InfluxDB 2.0 API parameters:

• url - (required) URL string of your InfluxDB.
• bucket - (required) Destination bucket for writing.
• org - (required) Destination organization for writing.
• orgid - (optional) ID of the destination organization for writing. : (NOTE: If both orgID and org are specified, org takes precedence)
• token - (required) API token to authenticate to the InfluxDB

InfluxDB \<1.8 API parameters: - url - (required) URL string of your InfluxDB. - username - (required) name of InfluxDB user. - password - (required) password of InfluxDB user.

Prometheus

Prometheus is a "pull model" time-series database. Prometheus accesses asab/v1/metrics endpoint of ASAB ApiService. Thus, connecting ASAB to Prometheus requires APIService initialization. All other configuration is required on the Prometheus side. ASAB metrics are presented to Prometheus in OpenMetrics standard format.

ApiService initialization

class MyApplication(asab.Application):
    async def initialize(self):
        from asab.metrics import Module
        self.add_module(Module)
        self.MetricsService = self.get_service('asab.MetricsService')
        self.MyCounter = self.MetricsService.create_counter("mycounter", tags={'foo': 'bar'}, init_values={'v1': 0, 'v2': 0})

        # Initialize API service
        self.ApiService = asab.api.ApiService(self)
        self.ApiService.initialize_web()

if __name__ == '__main__':
    app = MyApplication()
    app.run()

prometheus.yaml configuration file example

global:
scrape_interval: 15s
scrape_timeout: 10s
evaluation_interval: 15s

scrape_configs:
- job_name: 'metrics_example'
metrics_path: '/asab/v1/metrics'
scrape_interval: 10s
static_configs:
- targets: ['127.0.0.1:8080']

Note

To satisfy the OpenMetrics format required by Prometheus, you should follow the instructions below:

• Metrics names must fit regex [a-zA-Z:][a-zA-Z0-9_:]*. (Any other characters are replaced by an underscore. Leading underscores and numbers are stripped. These changes proceed without warning.)
• Metrics names MUST NOT end with "total" or "created".
• Tags SHOULD contain items "unit" and "help" providing metadata to Prometheus.
• Values MUST be float or integer.

Metrics Endpoints

The API Service in ASAB offers several endpoints that monitor internal ASAB functionality. Some of them present the current state of metrics. Check for Swagger documentation of your ASAB Application REST API by visiting the /doc endpoint.

/asab/v1/metrics

• This endpoint returns metrics in OpenMetrics format and its primary purpose is to satisfy Prometheus database needs.

/asab/v1/metrics.json

• This endpoint presents metrics data in JSON format.

/asab/v1/watch_metrics

• Use this endpoint for developing or monitoring your app from the terminal. It returns a simple table of ASAB metrics. You can filter metrics by name using the filter parameter and tags parameter to show or hide tags.

Example

watch curl localhost:8080/asab/v1/watch_metrics

watch curl localhost:8080/asab/v1/watch_metrics?name=web_requests_duration_max,tags=True

HTTP Target

For use cases requiring a push model of metrics digestion, there is an HTTP Target. HTTP Target creates a POST request every 60 seconds to configured URL with the current metrics state sent as JSON body. Configuration is required.

Configuration example

[asab:metrics]
target=http

[asab:metrics:http]
url=http://consumer_example:8080/consume