Best Python Application Performance Monitoring (APM) Tools in 2023
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 understsand 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 2023.
Logtail is a part of the Better Stack ecosystem, and together with Better Uptime, they create a complete observability solution with incident management built-in. With one-click Better Uptime integration, you can 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.
3. New Relic
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
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.
Dynatrace traces and extracts data about hosts, processes, and services used in automated naming, tagging, and analysis. Dynatrace also has an SLO monitor built-in allowing you to keep track of the service's performance in terms of SLO.
Apart from Python, SolarWinds' AppOptics offers Monitoring for Java, .Net, PHP, Scala, Node.js, Ruby, and Golang applications.
Retrace offers automatic instrumentation for Django, Redis cache, and flask, to name a few.
Stackify's APM for Python supports centralized logging, code profiling, error tracking, App and Server Monitoring, and RUM.
Atatus also offers auto instrumentation for the most popular frameworks, enables smart notifications, compare the impact of different code versions, and is fully scalable.
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.
SigNoz offers a broad and vibrant community of contributors and well-written, holistic documentation.
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.
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.
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