# Best Python Application Performance Monitoring (APM) Tools in 2026

Python Applications Performance Management and Monitoring tools enable
code-level observability, faster recovery, troubleshooting, and easier
maintenance of any python project. Measuring the performance of python
applications is handled by tracking logs and performance metrics from all around
the infrastructure. Subsequent data analysis helps developers to understand [errors](https://betterstack.com/community/guides/scaling-python/python-errors/) in context and trace them across the stack to the root cause.

Python is still gaining momentum and popularity, and the market is full of
various python APM tools. Let's take a look at some of the best of them in 2026.

## 1. [Better Stack](https://betterstack.com/logs)

![Better Stack dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/dffd7d5e-72f6-4a3f-1192-5a69e811dc00/orig =960x600)

[Better Stack](https://betterstack.com/) is a reliability platform that allows you to collect, analyze, and visualize logs from
[Python](https://docs.logtail.com/integrations/python) and Django in real-time.
Better Stack's advanced built-in collaboration features, resource-efficient
ClickHouse, and visually pleasing, dark-mode UI help you to spend less time
debugging and focus on shipping higher-quality software faster.

Better Stack also offers monitoring, incident management, and status pages. This functionality allows you to easily alert on-call team members of any
irregularities in your application's behavior. Be it a specific log message
error or a predefined usage trend.

## 2. [Sentry.io](https://sentry.io/)

![Sentry Dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/3842ce5d-6e0c-42b2-8783-9feead1e1700/public =1056x553) Sentry.io started out as a Django
monitoring side project and, after a while, became the backbone for tracking
errors and exceptions of one of the biggest industry players. It now offers
error tracking and performance monitoring for the most popular Languages and
Frameworks for app development.

## 3. [New Relic](https://newrelic.com/)

![New Relic dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/4dd8dfcb-b8ff-4419-3aa0-4513d1b66d00/public =1210x688) New Relic's Python Monitoring enables
visibility into python apps and helps with identifying and troubleshooting
performance issues. It tracks key transactions, monitors critical metrics, and
visualizes everything in dashboards. New Relic's Python monitoring promises
improved performance, query optimization, and instant observability.

## 4. [Site24x7](https://www.site24x7.com/)

![Site24x7 dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/9fb73769-d301-49be-c308-50e361a1a200/public =1352x710)

Site24x7's Python APM supports Django and Flask frameworks and multiple MySQL
and NoSQL databases. Its Python insights agent collects data about response
times, throughput, database operations, and errors of python applications.

## 5. [Paessler PRTG](https://www.paessler.com/prtg)

![Paessler dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/6f69a6ae-2943-4b8b-6e32-86220e268400/public =1366x686)

Paessler's python probes allow you to use probes to monitor Python applications
and create a complex and custom APM solution for python apps.

Paessler offers international support in multiple languages, allows you to
deploy custom scripts, and offers pay-as-you-go pricing. However, its
documentation often lacks even in English, and it recommends Windows as a
platform for best compatibility and performance.

## 6. [Dynatrace](https://www.dynatrace.com/)

![Dynatrace dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/03c48749-aa5a-4fa7-db7b-9780e2143b00/public =1366x768) Dynatrace's OneAgent allows for
python auto-instrumentation of Python applications. However, it requires
additional settings and configuration for frameworks, such as Django.

Dynatrace traces and extracts data about hosts, processes, and services used in
automated naming, tagging, and analysis. Dynatrace also has an [SLO](https://betterstack.com/community/guides/incident-management/sla-vs-slo-vs-sli/) monitor
built-in allowing you to keep track of the service's performance in terms of
SLO.

## 7. [AppOptics](https://www.appoptics.com/)

![AppOptics dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/c654ea15-c9ca-4080-3116-7772e1c4e600/public =575x300) AppOptics offers a python agent for
automated tracing and metric collection from Python Apps. AppOptics offers
on-prem, hybrid, and cloud-based, distributed applications monitoring. It allows
you to combine dashboards to visualize metrics from application and
infrastructure in one place.

Apart from Python, SolarWinds' AppOptics offers Monitoring for Java, .Net, PHP,
Scala, Node.js, Ruby, and Golang applications.

## 8. [Retrace](https://stackify.com/retrace/)

![Retrace Dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/c9290459-1b31-467d-21e7-a0f4d9991400/public =1366x668) Stackify's Retrace APM combines code
profiling, error tracking, and application log monitoring in one. It offers deep
insights into your infrastructure, dependencies, and code itself. It tracks
methods in application code via a lightweight profiling approach.

Retrace offers automatic instrumentation for Django, Redis cache, and flask, to
name a few.

Stackify's APM for Python supports [centralized logging](https://betterstack.com/community/guides/logging/log-aggregation/), code profiling, error
tracking, App and [Server Monitoring](https://betterstack.com/community/comparisons/server-monitoring-tools/), and RUM.

## 9. [Atatus](https://atatus.com/)

![Atatus Dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/624b3277-3409-4416-a719-cfd003314100/public =527x300) Atatus offers instant insight into Python
applications and frameworks. It enables end-to-end visibility for python
applications. Atatus allows you to monitor API failures, track python errors and
exceptions, trace transactions, monitor external requests, monitor databases
performance, and much more.

Atatus also offers auto instrumentation for the most popular frameworks, enables
smart notifications, compare the impact of different code versions, and is fully
scalable.

## 10. [AppDynamics](https://www.appdynamics.com/)

![AppDynamics dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/90122033-1320-426a-e4cd-ef8f89b75b00/public =1366x549) AppDynamics offers real-time
insights into Python apps and maps critical performance metrics and
transactions. During monitoring, it correlates transactions across environments
and platforms and offers comprehensive, contextual performance metrics of Python
apps in general.

It offers rapid root-cause identification and issue resolution, offers APIs for
extended compatibility and functionality, and works well both on-prem and in
hybrid environments.

## 11. [SigNoz](https://signoz.io/)

![Signoz Dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/a67184bf-4257-40d2-ed04-c29afb914900/public =1366x686) SigNoz supports OpenTelemetry as the
primary approach to instrumentation. It supports Python and some Python
Frameworks, such as Django. It runs on either Kafka+Druid or OLAP database
ClickHouse for the backend. The Query service is built-in GO, and the front-end
is Typescript-powered.

SigNoz offers a broad and vibrant community of contributors and well-written,
holistic documentation.

## 12. [Prometheus](https://prometheus.io/)

![Prometheus Dash](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/d0972f62-1f6e-4af8-eb7e-0775bcb70d00/public =994x768) Prometheus is an open-source
monitoring tool offering support for Python application monitoring. It offers an
official Python client library used for continuous monitoring.

You can monitor four python metrics using Prometheus - Counter, Gauge, Summary,
and Histogram. It's often deployed alongside open-sourced visualization tools
such as Grafana for visualizations of collected and monitored metrics.

## Conclusion

With the wide range of free, open-source, and reasonably priced, reliable SaaS
tools, there is no excuse for not having a python performance monitoring tool. A
proactive approach helps to prevent or mitigate issues before they hit the
end-user, while the reactive approach only hurts your reputation and drains
funds but also your engineers. For further resources on [not just Python APM tools](https://betterstack.com/community/comparisons/application-performance-monitoring-tools/) check our updated list.