The Python programming language is very flexible. The system can be used in conjunction with other programming languages and its libraries of useful functions make it quick to implement. However, those libraries and the object-oriented nature of Python can make its code execution hard to track.

There are two types of businesses that need to be able to monitor Python performance – those that develop software and those that use them. Clearly, those groups encompass just about every business in the developed world.

Here is our list of the six best Python monitoring tools:

  • SolarWinds AppOptics EDITOR’S CHOICE This cloud-based application performance monitor can track the execution of code anywhere and that includes application programs written in Python. This tool traces program execution and identifies resource locks and shortages that could be the cause of poor performance. Start a 30-day free trial.
  • Datadog APM An application performance monitor that offers code analysis and distributed tracing, identifying resource usage by applications as it switches between languages and executes APIs including code written in Python. This is a cloud-based service.
  • Dynatrace An AI-driven system monitor that includes code tracking and execution tracing. The capabilities of this cloud-based system include Python monitoring.
  • Site24x7 APM A cloud-based monitoring service that offers network server, and application monitoring and has Python code monitoring capabilities.
  • ManageEngine OpManager A monitoring system for servers and networks that is able to track the execution of Python code. It is available for Linux and Windows Server.
  • AppDynamics This cloud-based monitor searches through a system for all applications and maps their activities. This function extends to the distributed processes of APIs written in Python.

Python monitoring tools for software users

Software procedures rarely write in their sales documentation what programming languages their software is written in. the advent of Application Programming Interfaces (APIs) means that a non-Python program might very well rely on Python elements contributing towards a plugin element deep within the software. So, it is impossible for software buyers to know where or when they use Python code.

Businesses that subscribe to Software-as-a-Service (SaaS) products have even less knowledge of which programming languages contribute to their systems. Ultimately, you just want to track the performance of your applications and it probably doesn’t matter to you how those applications were written.

Fortunately, you don’t have to email all of your software providers in order to work out whether or not you deploy Python programs. Application performance monitors are able to track all code, no matter which language it was written in.

Python monitoring tools for software developers

As a software developer, you will be attracted to any services that enable you to speed up the completion of a program and cut costs. Software reuse is a major aid to efficiency and the ability to acquire libraries of functions off the shelf cuts costs and saves time.

If you get the code for a function library or if you compile that library yourself, you can work out whether that code is efficient just by looking at it. If you use functions that are delivered as APIs, their underlying structure is hidden. Those functions might be badly written and use system resources inefficiently. Those APIs might get the code delivered, but they could end up dragging down the whole application’s response time by running slowly, hanging while waiting for resources, or just falling over.

When you are developing code, you need to test each unit and then test them in combination before you can release the new module as completed. Every development manager knows that there is no better test environment than real life, so you also need to track the performance of your software in the field. DevOps monitoring packages will help you produce software and then Beta release it for technical and functional examination.

Python implementations

As a high-level, object-oriented language, Python is particularly suited to producing user interfaces. Libraries of functions take care of the lower-level tasks involved in delivering an effect, such as drag-and-drop functionality, or a long list of visual effects.

As a result of its suitability for use in creating interfaces, Python can be found in many, many different implementations. It is used in on-premises software packages, it contributes to the creation of websites, it is often part of many mobile apps, thanks to the Kivy framework, and it even builds environments for cloud services. It is everywhere.

Python monitoring issues

With any programming language, a key issue is how that system manages resource access. In object-oriented systems, such as Python, resource management is an even bigger issue. Object-oriented modules can be called many times over during the execution of a running program. Not only that, but the same code can be running many times over simultaneously.

When the same process is run in parallel, the issue of resource locks has to be dealt with. It could be that several different applications that are live on the same system were produced by different developers but use the same functions from a widely-used, publicly available, third-party library or API. So, these modules will be rapidly trying to acquire the same resources simultaneously and end up locking each other out.

Another major issue with object-oriented languages that are hidden behind APIs is that the developers that integrate them into new programs don’t know whether those functions are any good at cleaning up, terminating processes gracefully, tracking the half-life of spawned process, and releasing memory.

As a user of software and services, you have no hope of creating a meaningful strategy for managing all of these issues without an automated application monitoring tool. Even as a developer, you will spend a lot of time trying to work out operating system interactions manually. Anyway, the whole point of using functions written by other people is to save time, so you don’t want to get bogged down trying to trace the activities of those functions. It is better to get a monitoring tool to do that for you.

The best Python monitoring tools

Whether you work in development, run IT operations, or operate a DevOps environment, you need to track the performance of Python code and you need to get an automated tool to do that monitoring work for you.

There are many monitoring systems that cater to developers and users and some that work well for both communities. However, it can take a long time to identify the best tools and then narrow down the list to a few candidates that are worth trialing. This guide identifies the best options available so you can cut straight to the trial phase.

With these selection criteria in mind, we picked APM systems that can cover a range of Web programming languages because a monitoring system that covers a range of services is more cost-effective than a monitor that just covers Python.

Our methodology for selecting Python monitoring tools 

We reviewed the market for Python monitoring solutions and analyzed tools based on the following criteria:

  • Code profiling
  • Application dependency mapping
  • Distributed tracing
  • Log creation
  • System resource usage correlation
  • A free trial or a demo package for a cost-free assessment opportunity
  • Value for money from an API with a code profiler that is offered at a reasonable price

1. SolarWinds AppOptics EDITOR’S CHOICE

SolarWinds AppOptics is a SaaS system so you don’t have to install its software on your site or maintain its code. As a remote system, this service is not constrained by the boundaries of one single network – necessary freedom in this world of distributed processing and microservices.

Key Features:

  • SaaS package
  • Application dependency mapping
  • Distributed tracing
  • Code profiler
  • Infrastructure monitoring

Any application, particularly website pages and Web services might be calling in processes executed on remote servers without your knowledge. The tracing functions of AppOptics watch every application execute and tracks back through the calls to the original, underlying processes, identifying its programming language and exposing its code on the screen.

The dashboard code analyzer steps through executable code, detailing its resource usage and watching its access to resources. This service can spot bugs, code inefficiencies, resource locks, and orphaned processes. AppOptics is an excellent monitoring tool both for developers and IT operations support teams.

The AppOptics service is charged for by subscription with a rate per server and it is available in two editions. The lower of these is called Infrastructure Monitoring and it will track the supporting services of your system. To get Python monitoring, you need the higher plan, which is called Infrastructure and Applications Monitoring.  You can examine the service on 30-day free trial.

Pros:

  • Integrates into frameworks, such as Tornado, Django, Flask, and Pyramid to record each transaction
  • Customizable tracking features
  • Also monitoring PHP, Node.js, Go, .NET, Java, and SCALA
  • Root cause analysis that identifies the relevant line of code
  • Resource usage correlation

Cons:

  • You need the higher of the two plans to get Python monitoring

2. Datadog APM

EDITOR’S CHOICE

SolarWinds AppOptics is our top pick for a Python monitoring tool because it automatically detects Python code no matter where it is launched from and traces its activities, checking for code glitches and resource misuse. The AppOptics system is a SaaS service and, from its cloud location, it can follow code anywhere in the world – it is not bound by the limits of your network. This service offers excellent visualization of all Python frameworks and it can identify the execution of code written in other languages alongside Python.

Get 30-day Free Trial: my.appoptics.com/sign_up

OS: Cloud-based

Datadog APM has a battery of monitoring tools for tracking Python performance. This cloud platform is able to monitor code on your site and in operation on any server anywhere. This makes the tool great for DevOps environments. You can check on the code that your own team develops and also trace the actions of any APIs you integrate into your own applications. The Datadog service can track programs written in many languages, not just Python.

  • Cloud-based
  • Development testing
  • Operations monitoring
  • Code tracking

This system includes testing utilities, such as tracing and synthetic monitoring. The synthetic monitoring service is an extra module that you would need to add to your APM account. The code-level tracing facility is part of the higher of Datadog APM’s two editions. The lower edition is just called APM and that includes a system of dependency mapping. The higher plan is APM & Continuous Profiler, which gives you the code analysis function.

The code tracking service continues working once your code goes live. If you aren’t a developer of applications, the operations phase is where you begin your use of Datadog APM.

This system provides insights into the interplay between your Python system, modules programmed in other languages, and system resources. You can get a 14-day free trial of Datadog APM.

  • Provides application dependency mapping through to underlying resources
  • Distributed tracing that can cross coding languages
  • Code profiling that records the effects of each line
  • Root cause analysis and performance alerts

3. Dynatrace

Dynatrace integrates AI detection techniques in the monitoring services that it delivers from its cloud platform. The “trace” part of the Dynatrace name is very apt because this system is able to trace all of the processes that contribute to your applications. The system performs constant sweeps, identifying applications and services and how they interact. It then drills down through each application to discover all contributing modules.

  • Cloud-based
  • AI deteciton processes
  • Multi-language capabilities

When the Dynatrace system examines each module, it detects which programming language it was written in. It will then watch the performance of each module and looks at how it interacts with resources. The service can even track down which server the code is run on – this is a difficult task for API-fronted modules.

Dynatrace is a great tool for development teams and is also very useful for systems administrators tasked with supporting complicated systems, such as websites. The dashboard is based in the cloud and can be accessed through any standard browser. It includes some great interactive data visualizations that map out your entire system and demonstrate the performance of each element.

Dynatrace offers several packages of its service and you need the Full-stack Monitoring plan in order to get Python tracing. You can get a 15-day free trial of Dynatrace.

  • Scans all Web apps and detects the language of each module

  • Distributed tracing and application dependency mapping

  • Good for development testing and operations monitoring

  • No self hosting option

4. Site24x7 APM

Site24x7 has a module called APM Insight. This is able to identify all the applications running on a system and identify the interactions between them. The cloud service builds up a live map of interactions between those applications. It then dives into each application and identifies each operating module.

  • Cloud platform
  • Combined packages
  • Application dependency mapping

The component analysis of the APM is able to identify the language that the code is written in and watch its use of resources. These modules might be supporting applications running on your site, websites, or mobile apps. The programming languages that this system is able to analyze include Python. The service not only watches the code as it runs but also examines the contribution of the various Python frameworks that contribute to the management of those modules.

The Site24x7 service is also useful for development environments. It helps you validate the Python frameworks and APIs that you intend to use in the creation of your applications. You need to ensure that the components you call in to speed up your application development don’t end up dragging down the performance of your new system. The tool offers good support during the unit, integration, and Beta testing.

The APM Insight service is blended into the APM package, which is a platform of cloud monitoring systems. The APM not only gives you application tracking but network and server monitoring as well. These extra services allow you to monitor the full stack of systems and spot performance issues.

  • Combines Web, network, server, and application monitoring

  • Application mapping to infrastructure usage

  • Validates frameworks and APIs

  • Extra testing volume requirements can rack up the bill

You can get a 30-day free trial of Site24x7.

5. ManageEngine Applications Manager

ManageEngine Applications Manager covers the operations of applications and also the servers that support them. Similar to the other application performance monitors on this list, the Applications Manager is able to draw up an application dependency map that identifies the connections between different applications.

  • On-premises
  • Application dependency mapping
  • Code profiling

The monitor is able to examine the code of modules and performs distributed tracing to watch the activities of code that is hidden behind APIs and supporting frameworks., It isn’t possible to identify where exactly cloud services are running or what other elements they call in. However, the Applications Manager can watch the execution of Python code no matter where it is hosted. The monitor can also see the interactions between Python modules and those written in other languages.

Other performance testing services included in the Applications Manager include synthetic transaction monitoring facilities that exercise the interactive features in a Web page. The performance of cloud services can be blended in with the monitoring of applications running on your own servers. This system is able to watch over databases performance, virtualizations, and containers, plus Web servers, file servers, and mail servers.

ManageEngine Applications Manager is delivered as on-premises software that will install on Windows Server or Linux. You can get a 30-day free trial of this package.

  • Automatic discovery of supporting modules for Web applications, frameworks, and APIs

  • Distributed tracing and root cause analysis

  • Cross-language code profiling

  • No SaaS option

6. AppDynamics

AppDynamics is a cloud platform that includes extensive AI processes and provides analysis and testing functions as well as monitoring services. The AppDynamics system is organized into services. Python monitoring and tracing are available in the Infrastructure and Application Performance Monitoring systems. You can get the Infrastructure Monitoring service by itself or opt for the Premium plan, which includes Infrastructure, Application, and Database monitoring. Or you can get the Enterprise edition, which has those three modules plus Business Performance Monitoring.

  • SaaS package
  • AI-based
  • Application dependency mapping

The core of the AppDynamics system is its application dependency mapping service. This identifies all of the applications contributing to a system and examines the links between them. The service then gets into each application and identifies where its contributing modules are running. Users can select a specific node and then analyze all of its components.

The Python monitoring system within AppDynamics exposes the interactions of each Python object with other modules and also system resources. It doesn’t matter where those Python programs are running, AppDynamics will find them.

The AI service built into AppDynamics is called Cognition Engine. This assesses the performance requirements of each module and also predicts the resources that it will need in order to reach its target response time. If Cognition Engine predicts that resource availability will not be enough to support each running module, it raises an alert.

The tracing features in AppDynamics are ideal for development teams and testing engineers. The tools of this service are suitable for use from project planning to IT operations.

AppDynamics is a subscription service with a rate per month for each edition. The service is available for a 15-day free trial.

  • Automatically discovers backing microservices

  • Identifies potential resource shortages

  • Distributed tracing and root cause analysis

  • Use for operation monitoring not development testing