GitHub
github.com › Kludex › fastapi-prometheus-grafana
GitHub - Kludex/fastapi-prometheus-grafana: FasAPI + Prometheus + Grafana! :tada: · GitHub
Grafana: http://localhost:3000/ FastAPI: http://localhost:8000/ On the FastAPI, you can access /metrics endpoint to see the data Prometheus is scraping from it. Prometheus FastAPI Instrumentator · Generate and Track Metrics for Flask API Applications Using Prometheus and Grafana ·
Author: Kludex
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Monitor Python FastAPI in Real-Time with Prometheus & Grafana | ...
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PROMETHEUS Metrics for your Python FastAPI App - YouTube
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Add custom metrics to FastAPI Server with prometheus_client | Python ...
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УРОКИ FASTAPI НА БОЕВОМ СЕРВИСЕ 11. GRAFANA ...
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Instrumenting applications for Prometheus - YouTube
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Introduction to Python monitoring with Prometheus - YouTube
DEV Community
dev.to › ken_mwaura1 › getting-started-monitoring-a-fastapi-app-with-grafana-and-prometheus-a-step-by-step-guide-3fbn
Getting Started: Monitoring a FastAPI App with Grafana and Prometheus - A Step-by-Step Guide - DEV Community
January 30, 2025 - With Prometheus now installed and configured in a Docker container, and your FastAPI app instrumented with Prometheus metrics, you are ready to move on to the next steps of integrating Grafana for visualization and analysis.astapi@db/hello_fastapi_dev depends_on: - db db: image: postgres:13.1-alpine volumes: - postgres_data:/var/lib/postgresql/data/ environment: - POSTGRES_USER=hello_fastapi - POSTGRES_PASSWORD=hello_fastapi - POSTGRES_DB=hello_fastapi_dev ports: - "5432:5432" prometheus: image: prom/prometheus container_name: prometheus ports: - 9090:9090 volumes: - ./prometheus_data/promethe
Binadit
binadit.com › home › tutorials › monitor fastapi applications with prometheus grafana
FastAPI Prometheus Grafana Monitoring Guide - Binadit Tutorials
May 19, 2026 - sudo useradd --no-create-home --shell /bin/false monitoring sudo mkdir -p /etc/prometheus /etc/grafana /var/lib/prometheus /var/lib/grafana sudo chown monitoring:monitoring /etc/prometheus /var/lib/prometheus sudo chown monitoring:monitoring /etc/grafana /var/lib/grafana · Install the required Python packages to add Prometheus metrics to your FastAPI application. pip3 install prometheus-client prometheus-fastapi-instrumentator uvicorn[standard]
DevOps.dev
blog.devops.dev › monitoring-fastapi-using-grafana-and-prometheus-bc9a58c54cf2
Monitoring FastAPI Using Grafana and Prometheus | by Mohit Rathore | DevOps.dev
October 1, 2024 - In this guide, we’ll walk through setting up monitoring for a FastAPI application using Prometheus and Grafana. We’ll use Docker Compose to bring up the entire stack: FastAPI, Prometheus, and Grafana. We’ll create a simple FastAPI app with one example endpoint. We’ll use the prometheus_fastapi_instrumentator to collect metrics.
Medium
techkamar.medium.com › tracking-fastapi-url-hit-count-over-a-period-of-time-using-grafana-and-prometheus-4b30540e56b0
Tracking FastApi URL hit count over a period of time using Grafana and Prometheus | by tech kamar | Medium
September 4, 2024 - instrumentator = Instrumentator().instrument(app) @app.on_event("startup") async def _startup(): instrumentator.expose(app) ... from fastapi import FastAPI from prometheus_fastapi_instrumentator import Instrumentator from prometheus_client import Counter import time app = FastAPI() instrumentator = Instrumentator().instrument(app) @app.on_event("startup") async def _startup(): instrumentator.expose(app) REQUEST_COUNT = Counter( 'app_request_count', 'Application Request Count', ['method', 'endpoint', 'http_status'] ) @app.get("/") async def root(): start_time = time.time() REQUEST_COUNT.labels('GET', '/', 200).inc() return {"message": "Hello World"}
LinkedIn
linkedin.com › pulse › monitoring-airflow-fastapi-using-prometheus-grafana-dalmas-otieno-h9trf
monitoring airflow and fastapi using prometheus and grafana
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Read Medium
readmedium.com › monitoring-fastapi-using-grafana-and-prometheus-bc9a58c54cf2
Monitoring FastAPI Using Grafana and Prometheus
It begins with creating a simple FastAPI app and instrumenting it with prometheus_fastapi_instrumentator to collect metrics. The setup is orchestrated using Docker Compose, which defines services for FastAPI, Prometheus, and Grafana, ensuring they run concurrently.
Reddit
reddit.com › r/fastapi › monitoring and observability in fastapi
r/FastAPI on Reddit: Monitoring and Observability in FastAPI
May 1, 2026 -
I am trying to understand the best practices for monitoring and Observability in fastAPI. Does it come with different metrics and otel out of the box? Also, how are you using other tools and library along with it to make it production ready?
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I would take a look at Pydantic’s Logfire. Wraps open telemetry, and kinda just works without a lot of setup. https://pydantic.dev/logfire
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HI, I just shared an article here a couple days back. I have written a comprehensive observability guide for fastapi web apps with an example repo that you can clone and explore. Basically you have to you use agents to auto instrument your app which then generates telemetry from the app. The telemetry is routed to an opentelemetry backend (like SigNoz, the company I work for), which helps you visualize the data and understand what's happening. Here's the link to the post: https://www.reddit.com/r/FastAPI/s/4PZaTTEjm1
Markaicode
markaicode.com › home › devops › grafana, prometheus & kubernetes: ai inference monitoring
Grafana, Prometheus & Kubernetes: AI Inference Monitoring | Markaicode
May 22, 2026 - Layer responsibilities: FastAPI/LangChain routes requests and exposes its own latency metrics natively via prometheus_fastapi_instrumentator. Ollama does not — a small polling collector reads its per-request JSON timing fields and re-exposes them in Prometheus format. Prometheus scrapes both. Grafana renders the result.
PyPI
pypi.org › project › prometheus-fastapi-instrumentator
prometheus-fastapi-instrumentator · PyPI
It also features a modular approach to metrics that should instrument all FastAPI endpoints. You can either choose from a set of already existing metrics or create your own. And every metric function by itself can be configured as well. This chapter contains an example on the advanced usage of the Prometheus FastAPI Instrumentator to showcase most of it's features.