August 22, 2024 - FROM python:3.11-alpine # This ... AWS ECR for that purpose. We have written the exporter itself using prometheus-client, dockerized the application, and pushed it to the remote repository....

September 7, 2024 - They enable the collection of metrics that Prometheus doesn’t natively support, empowering you to gain deeper visibility into the behavior of your applications and infrastructure. To demonstrate the creation of a custom exporter, we’ll use Python along with two key libraries: the Prometheus_client library for defining and exposing metrics, and the Openshift.Dynamic library for interacting with the Openshift Container Platform API.

February 25, 2023 - Currently, we use Blackbox Exporter to monitor it, but later we want to expand the capabilities a bit, so we will try to create an exporter that for now will simply check the response code of this endpoint. #!/usr/bin/env python import os import requests import time from prometheus_client import start_http_server, Enum, Histogram hitl_psql_health_status = Enum("hitl_psql_health_status", "PSQL connection health", states=["healthy", "unhealthy"]) hitl_psql_health_request_time = Histogram('hitl_psql_health_request_time', 'PSQL connection response time (seconds)') def get_metrics(): with hitl_psql_health_request_time.time(): resp = requests.get(url=os.environ['HITL_URL']) print(resp.status_code) if not (resp.status_code == 200): hitl_psql_health_status.state("unhealthy") if __name__ == '__main__': start_http_server(9000) while True: get_metrics() time.sleep(1)

In this case, Prometheus should still do service discovery, and pass on the target to be scraped. See the blackbox and SNMP exporters for examples. Note that it is only currently possible to write this type of exporter with the Go, Python and Java client libraries.

May 21, 2023 - Currently, we use Blackbox Exporter to monitor it, but later we want to expand the capabilities a bit, so we will try to create an exporter that for now will simply check the response code of this endpoint. #!/usr/bin/env python import os import requests import time from prometheus_client import start_http_server, Enum, Histogram hitl_psql_health_status = Enum("hitl_psql_health_status", "PSQL connection health", states=["healthy", "unhealthy"]) hitl_psql_health_request_time = Histogram('hitl_psql_health_request_time', 'PSQL connection response time (seconds)') def get_metrics(): with hitl_psql_health_request_time.time(): resp = requests.get(url=os.environ['HITL_URL']) print(resp.status_code) if not (resp.status_code == 200): hitl_psql_health_status.state("unhealthy") if __name__ == '__main__': start_http_server(9000) while True: get_metrics() time.sleep(1)

December 6, 2024 - Set up the environment (e.g., ports to expose, entry points). FROM --platform=linux/amd64 python:3.8-slim-buster as build WORKDIR /app RUN pip3 install prometheus_client COPY custom_exporter.py .

July 13, 2024 - In this tutorial, you will learn the process of developing a custom Prometheus Exporter in Python. We will create an exporter to monitor an API endpoint and expose selected data as Prometheus metrics.

December 5, 2025 - Include a health check - Helps with monitoring the exporter itself · Use appropriate metric types - Counter, Gauge, Histogram, Summary · Follow naming conventions - namespace_subsystem_name_unit · Include useful labels - But avoid high cardinality · package main import ( "log" "net/http" "github.com/prometheus/client_golang/prometheus" "github.com/prometheus/client_golang/prometheus/promhttp" ) // Collector implements prometheus.Collector interface type MyCollector struct { upMetric *prometheus.Desc requestsMetric *prometheus.Desc latencyMetric *prometheus.Desc } func NewMyCollector() *MyC

January 3, 2021 - Let’s see a small but complete exporter implemented in Python (notes and explanation in comments and below the snippet): ... In the above code, I defined a helper class AppMetrics to contain the Prometheus metrics and app metric loop logic. Creating the class wasn’t necessary, but I think it is a bit cleaner and more future-proof to start this way and keep the logic and data contained in an object.

May 11, 2022 - Like below: It exposes the data on a specific port e.g http://myurl:8000. Let’s take a very basic example, Suppose there is one script (Daemon service) is running with the name myprocess.go.

September 13, 2022 - Despite all the exporters (https://prometheus.io/docs/instrumenting/exporters/) that Prometheus and its community can offer, in some particular use cases, you may want to design your own exporter to run your custom checks. No worries, Prometheus has got you covered! If you check this GitHub repository, you will find a Python Prometheus client that you can use and abuse to build up your exporter.

This an example of a custom exporter that you can write in Python - sd416/simple-prometheus-exporter

February 11, 2023 - In fact, it’s very easy to build a new Prometheus exporter using Prometheus python client. Therefore, we’ll develop custom Prometheus exporter in Python and show how to debug it fast.

May 27, 2024 - In this article, we first discussed the basic concepts of Prometheus exporters and then went through two documented examples of implementation using Python. Those examples leverage Prometheus’s best practices and serve as a starting point for building your exporters according to your specific application needs.

June 8, 2023 - In the exporter, we will have gauge and counter metrics exposed. For this, I ‘ll use the prometheus_client to import the libraries. I have the repository on Github you can check it here. ... Writing the custom exporter in python for Prometheus.

It’s important to note that Prometheus provides several libraries to define and expose your metrics based on the language your exporter uses: ... And other unofficial libraries can be found here. Now, let’s move on to the practical side, let’s begin by setting up a basic HTTP server. For this tutorial, I’ll use the python language and the official client library.

In this scenario, once the Prometheus server is started, it invokes a custom exporter after each 15sec, as specified in the scraping interval. api_endpoint and api_name (unique identifier for a job) are passed to the exporter as parameters.

January 25, 2026 - Access the Sample Page Once the ... simply a directory where you’ll write your exporter. For this example, the directory will be named httpd-exporter....

async def on_application_startup(self, application: aiohttp.web.Application) -> None: # ... application[EXPORTER_APP_KEY].set_metric_update_handler(self._update_handler) async def _update_handler(self, metrics: dict[str, prometheus_client.metrics.MetricWrapperBase]): for name, metric in metrics.items(): metric.set(...) See prometheus_aioexporter.sample for a complete example (that can be run with python -m prometheus_aioexporter.sample).

February 27, 2024 - Let’s start by creating and activating a virtual env named “envcbexp” for our exporter in desired OS; python3 -m venv envcbexp source ./envcbexp/bin/activate · Secondly, we will install prometheus_client and requests to get and parse ...