Python monitoring without the stack-trace archaeology
One SDK for Python error tracking and request monitoring across FastAPI, Flask, and Django — plus logs, uptime, and infrastructure on the same platform. Initialize once at startup and every exception arrives with the context to fix it.
Why Python teams need real monitoring
A traceback in a terminal is fine in development. In production, that same traceback lands in a log file nobody is watching, on one of several instances, minutes before the log rotates. Was it a new bug or a known one? Did it start with the last deploy? Which requests hit it, and how often? Without proper Python error tracking, every one of those answers costs an engineer an afternoon.
AllStak answers them automatically. The Python SDK (Python 3.9+) initializes in a few lines, auto-instruments FastAPI and Starlette after init, integrates with Flask and Django through framework extras, and captures exceptions with the release and environment they came from. Errors, requests, logs, uptime, and host metrics live on one platform with one bill — so the picture is complete without stitching tools together.
Full-stack Python monitoring
From the first unhandled exception to the host it ran on, AllStak covers your Python services across every layer.
Error tracking
Capture exceptions with full Python tracebacks, environment, and release — grouped so a thousand occurrences of the same bug read as one issue, not a thousand.
Framework integrations
FastAPI and Starlette are auto-instrumented after init; Flask wires in with AllStakFlask(app) and Django by adding allstak to INSTALLED_APPS — each via its framework extra.
Request tracking
Inbound requests are recorded automatically by the framework integration, and outbound HTTP can be recorded too — so you see which endpoints fail and which dependencies drag.
Log management
Centralize logs from every Python service next to the errors they relate to, searchable from the same dashboard instead of scattered files.
Infrastructure monitoring
A lightweight host agent reports CPU, memory, disk, network, and Docker — so you can tell an app bug from a worker starved of resources.
Alerts & incidents
Get notified on new errors, spikes, and threshold breaches, with incidents that keep the on-call response organized instead of chaotic.
Add AllStak in minutes
Install from PyPI and initialize at application startup — framework extras like allstak[fastapi], allstak[flask], and allstak[django] wire in the integrations.
pip install allstak
import os
import allstak
allstak.init(
api_key=os.getenv("ALLSTAK_API_KEY"),
environment=os.getenv("APP_ENV", "production"),
release=os.getenv("ALLSTAK_RELEASE"),
)Call allstak.init() before creating the app instance — FastAPI/Starlette is auto-instrumented after init, and capture_exception() reports handled errors. full setup guide · SDK reference.
What you see in AllStak
Error detail with full context
Open any issue to a full Python traceback, the environment and release it came from, and how often and how recently it fired — everything triage needs on one screen.
Requests & performance
Per-endpoint latency and error rates across FastAPI, Flask, or Django show exactly which route degraded and when — no log spelunking required.
Unified real-time dashboard
Errors, requests, logs, and host health for all your Python services update live on one dashboard — in English or Arabic — so the whole team shares the same picture.
Why teams pick AllStak for Python
- One platform for errors, requests, logs, uptime, and infrastructure — one bill, no tool sprawl.
- FastAPI auto-instrumented after init; Flask and Django integrate through framework extras.
- A few lines at startup — api_key even falls back to the ALLSTAK_API_KEY environment variable.
- Releases and environments separate your data, so a regression points at the deploy that caused it.
- Predictable SAR pricing with a genuine free tier — start without a credit card.
- Data stays in Saudi Arabia, with an English and Arabic dashboard for the whole team.
Python monitoring FAQ
How do I add error tracking to a Python app?
Install allstak from PyPI and call allstak.init() with your API key before creating the app instance. FastAPI/Starlette is auto-instrumented after init; Flask uses AllStakFlask(app) and Django adds allstak to INSTALLED_APPS. Handled exceptions go through allstak.capture_exception() — the setup guide covers each framework.
Which Python versions and frameworks are supported?
The SDK supports Python 3.9 and newer, with framework extras for FastAPI, Flask, and Django (allstak[fastapi], allstak[flask], allstak[django]) — and it works in any Python app even without a framework integration.
Is AllStak free for Python?
Yes. AllStak has a free tier you can start on without a credit card, and predictable SAR pricing as you grow. The Python SDK itself is free to use.
Is AllStak a Sentry alternative for Python?
Yes. You get Python error tracking with grouping, releases, and framework integrations — plus request tracking, logs, uptime, and infrastructure monitoring that Sentry would require extra tools for, consolidated on one platform with SAR pricing and data stored in Saudi Arabia.
Will the SDK slow down my Python app?
The SDK is built for production and captures telemetry with minimal overhead. Instrumentation hooks into your framework once at startup rather than wrapping every call, so you get visibility without meaningfully impacting request latency.
Explore more
Start monitoring Python today
pip install, initialize at startup, and watch errors, requests, and host health flow into one dashboard. Start free — no credit card required.