prometheus-flask-instrumentator 4.1.1

Instruments Flask API transparently

Prometheus Flask Instrumentator

Small package to instrument your Flask app transparently.

pip install prometheus-flask-instrumentator

Fast Track

from prometheus_flask_instrumentator import Instrumentator

Instrumentator().instrument(app).expose(app)

With this the Flask app is instrumented and all Prometheus metrics can be scraped via the /metrics endpoint.

The exporter includes the single metric http_request_duration_seconds. Basically everything around it can be configured and deactivated. These options include:

• Status codes are grouped into 2xx, 3xx and so on.
• Requests without a matching template are grouped into the handler none.
• Renaming of labels and the metric.
• Regex patterns to ignore certain routes.
• Decimal rounding of latencies.

See the Example with all parameters for all possible options or check out the documentation itself.

Example with all parameters

from prometheus_flask_instrumentator import PrometheusFlaskInstrumentator

PrometheusFlaskInstrumentator(
    should_group_status_codes=False,
    should_ignore_untemplated=False,
    should_group_untemplated=False,
    should_round_latency_decimals=True,
    excluded_handlers=[
        "admin",            # Unanchored regex.
        "^/secret/.*$"],    # Full regex example.  
    buckets=(1, 2, 3, 4,),
    metric_name="flask_http"
    label_names=("flask_method", "flask_handler", "flask_status",),
    round_latency_decimals=3,
).instrument(app).expose(app, "/prometheus_metrics")

It is important to notice that you don't have to use the expose() method if adding the endpoint directly to the Flask app does not suit you. There are many other ways to expose the metrics.

The defaults are the following:

should_group_status_codes: bool = True,
should_ignore_untemplated: bool = False,
should_group_untemplated: bool = True,
should_round_latency_decimals: bool = False,
excluded_handlers: list = ["/metrics"],
buckets: tuple = Histogram.DEFAULT_BUCKETS,
metric_name: str = "http_request_duration_seconds",
label_names: tuple = ("method", "handler", "status",),
round_latency_decimals: int = 4,

Prerequesites

• python = "^3.6" (tested with 3.6 and 3.8)
• flask = "^1" (tested with 1.1.2)
• prometheus-client = "^0.8.0" (tested with 0.8.0)

Development

Developing and building this package on a local machine requires Python Poetry. I recommend to run Poetry in tandem with Pyenv. Once the repository is cloned, run poetry install and poetry shell. From here you may start the IDE of your choice.

For formatting, the black formatter is used. Run black . in the repository to reformat source files. It will respect the black configuration in the pyproject.toml.