Python is a popular programming language used to create desktop GUI applications, web apps, and interactive websites. This programming language comes with simple syntax, so it helps to create a readable codebase. Also, it supports multiple platforms and programming paradigms, which is probably why many well-known applications are built on Python.
As with any software or hardware, these Python applications also have to be monitored to ensure they are working the way they should. So now, you might wonder what metrics you should look for and how you can watch the health and performance of these applications.
Here is our list of the best Python monitoring tools:
- AppOptics Python Application Performance Monitoring – FREE TRIAL This tool from SolarWinds handles all aspects of Python application monitoring. Its advanced features streamline tracing, code profiling, exception tracking, performance monitoring, and more. Get a 30-day-free trial.
- Site24x7 APM – FREE TRIAL Insight Python agent monitors and optimizes the performance of your Python applications and provides information on a wide range of metrics. Start a 30-day free trial.
- Paessler PRTG – FREE TRIAL This is a sensor-based tool where different sensors analyze different aspects of your Python applications. These metrics are combined to give you a comprehensive view of the performance of your Python applications. Access a 30-day free trial.
- Datadog APM Monitors Python application data and analyzes stack traces to give detailed insights into the health and performance of Python applications.
- ManageEngine OpManager Comes with advanced script and code monitoring features to help you stay on top of errors, code changes, and the resultant performance of your Python applications.
- Dynatrace Discovers and resolves performance issues in your Python code and applications for improved performance and traceability.
- AppDynamics This tool monitors the end-to-end performance of Python applications and provides the necessary metrics for tracking important aspects of their performance.
- NewRelic Monitors your Python applications, identifies performance issues, and helps you to resolve the same at the earliest.
- Stackify Proactively improves application performance by retracing users and observing applications in production environments.
- Atatus Provides complete visibility into the performance of your Python applications.
Let’s now jump into a detailed review of each of these tools.
The Best Python Monitoring Tools
1. AppOptics Python Application Performance Monitoring – FREE TRIAL
AppOptics Python Application Performance Monitoring is an application monitoring tool with advanced capabilities to monitor Python applications and their health and performance. Besides, it also tracks code-level changes, tracing, and exceptions.
Below are the salient features of this tool.
- Its root cause summaries make it easy to identify the source of the problem
- Works well on both legacy applications and modern ones that run on Kubernetes
- Automatically evaluates service metrics so that you can see essential aspects such as the average response time, error rate, CPU utilization levels, error rate, and more.
- It’s a handy tool during both development and testing phases to help create well-optimized Python applications
- Suggests code-level changes to ease the task for developers
- Provides the reason for the poor performance of applications so that they can be addressed at the earliest
- Supports distributed transaction tracing by following a request as it moves through multiple services and modules
- Traces exceptions to give a service context for each
- Offers live code profiling
- Troubleshoots transactions to help you understand the poor-performing ones
- Analyzes logs to give you in-depth insights
- Combines data across different stacks to give you a contextual view of the problem
- Isolates individual requests across systems for better diagnostics
- Monitors systems across all environments, from on-prem to highly distributed cloud apps
- Consolidates the monitoring of all applications and environments and presents the results in a single intuitive dashboard.
Pricing: AppOptics comes in two pricing plans, and they are
- Infrastructure monitoring – $9.99 per host per month
- Infrastructure and application monitoring – $24.99 per host per month
Download: Click here for an AppOptics Python Application Performance Monitoring fully functional 30-day free trial.
2. Site24x7 APM – FREE TRIAL
Site24x7’s APM Insight Python Agent monitors Python applications and provides many metrics around them, such as the response time, throughput, database operations, and more. You can track these metrics and optimize them for enhanced performance.
Below are the salient features of the APM Insight Python Agent.
- Supports Django and Flask frameworks, and jinja2, SQLite, pymysql, psycopg2, and pymemcache databases
- Requires Python version 3.5.0 and above to work
- Provides the option to mark key transactions, traces, and deployments for detailed analysis
- Comes with many configuration options to suit your preferences
- Provides accurate insights into end-user experience
- Gives visibility into the hidden aspects of application performance and monitoring
- Visualizes interaction patterns
- Offers an in-depth understanding of real-world problems impacting users
- Analyzes performance across browsers, platforms, ISPs, geographies, and more
- Supports single-user application monitoring through AJAX calls
- Monitors web pages built using the MVC frameworks.
- Enables you to isolate performance issues and resolve them at the earliest
Pricing: Site24X7 offers four pricing plans, namely
- Starter – $9 per month. Supports ten websites/servers and one synthetic web transaction
- PRO – $35 per month. Supports 40 websites/servers and three synthetic web transaction
- Classic – $89 per month. Supports 100 websites/servers and five synthetic web transaction
- Enterprise – $225 per month. Custom
Download: Start a 30-day free trial.
3. Paessler PRTG – FREE TRIAL
Paessler PRTG is an advanced sensor that can monitor different aspects of your Python applications and give you a comprehensive view of the health and performance of these applications.
Here’s a look at the PRTG features related to Python monitoring.
- Supports many languages such as Dutch, French, German, Spanish, Russian, Japanese, Portuguese, and Chinese
- This sensor returns a JSON value that can use in further processing
- The values are displayed in a visually appealing graph
- Paessler recommends Windows 2012 R2 or higher versions for best compatibility
- Easy to install and use
- Allows you to extend its functionality through custom scripts
- Supports the following channel types: bandwidth, memory, disk, custom, and file
- Offers extensive configuration options
- Allows many scanning interval choices
- Provides granular control through user access
Pricing: With PRTG, you pay for what you use. Typically, it is one sensor per metric per device, and you pay to depend on the number of metrics and devices you use. The pricing slab is as follows
- First 100 – FREE
- Up to 500 – $1,750
- Up to 1000 – $3,200
- Up to 2500 – $6,500
- Up to 5000 – $11,500
- Unlimited – $15,500
- 20,000+ sensors – custom quote
Download:You can work out what your network requirements are with a 30-day free trial.
4. Datadog APM
Datadog APM is a full-stack Python monitoring tool that analyzes stack traces and gives detailed information on the performance of your Python applications, so you can make the necessary changes to optimize their performance.
The features of Datadog APM related to Python monitoring are:
- Monitors Python performance to meet SLA requirements
- Identifies application dependencies
- Automatically generates service maps
- Analyzes stack traces to give insights
- Troubleshoots Python issues at the application and end-point levels
- Highlights error requests in the trace view
- Correlates Python data from traces and logs to pinpoint the root cause
- Analyzes log patterns for repetitive errors
- Provides built-in support for Python platforms such as Django and Flask
- Troubleshoots Python queries that impact performance
- Correlates information from 600+ integrations to provide a comprehensive view
- Automatically tracks Python data from auto-scaling infrastructure
- Auto-detects Python performance problems without the need for additional configurations
- Searches, filters, and analyzes Python stack traces
- Maps Python applications and their supporting architecture in real-time.
- Traces asynchronous Python code
Pricing: Datadog offers many plans, so you can pick the one that’s right for you. For example, the Infrastructure management plan comes in three flavors – Free, Pro ($15/host/month), and Enterprise ($23/host/month). Similarly, log management has two flavors – Ingest that starts at $0.10.ingested or scanned GB/month, and Retain or Rehydrate starts at $1.70/million logs/month.
Download: Click here to get started for free.
5. ManageEngine OpManager
OpManager is an application performance monitoring tool that provides visibility into the health and performance of your Python applications. Its advanced features help you to isolate and resolve performance issues at the earliest.
Here’s a look at what OpManager offers.
- Its byte-code instrumentation feature provides code-level insights to improve performance
- Monitors end-user experience and strive to improve them with appropriate metrics
- Provides visibility into applications hosted on private, public, and hybrid cloud, and on-prem environments
- Supports the use of custom scripts for monitoring
- Automatically discovers applications
- Maps dependencies for easy reference
- Comes with 500+ pre-built reports that can be used in many situations
- Reduces the Mean Time to Repair (MTTR), so issues can be fixed at the earliest.
- Improves the overall DevOps performance
- Helps you to respond to incidents faster
Pricing: OpManager comes in two editions – Professional and Enterprise. Contact the sales team for a custom quote.
Download: Click here to start a free trial.
Dynatrace specializes in discovering and solving performance problems in your Python code and applications so that you can benefit from its increased performance and optimization.
The features of Dyntace’s Python monitoring are:
- Provides a detailed view into all application and service dependencies
- Keeps track of all the Python processes
- Automatically tracks changes in Python’s live processes
- Monitor Python applications and services at the process level
- Makes a list of the calls made to and fro by your Python applications
- Focuses on process-specific context
- Displays only the essential metrics that have a significant impact on the application’s performance
- Pinpoints to the root cause of problems
Pricing: Dynatrace offers six pricing plans, so choose the one that best fits your needs.
- Full-stack monitoring ($69/month for an 8-GB host) – Provides full-stack observability for apps, microservices, and infrastructure.
- Infrastructure monitoring ($21/month for an 8GB host) – Provides observability across cloud platforms, containers, and data center technologies.
- Digital experience monitoring ($11/month for 10K digital experience monitoring units) – Optimizes user experience across mobile, web, hybrid, and IoT applications.
- Application security ($10/month for an 8GB host) – Provides runtime application vulnerability detection and is optimized for the cloud and Kubernetes
- Open Ingestion ($25/month for 100K Davis Data Units) – Extends observability with log monitoring, custom metrics, and events, and FaaS traces
- Cloud automation – Custom
Download: Click here to start a 15-day free trial.
AppDynamics monitors the end-to-end performance of Python applications and handles the mapping and tracking of the critical performance metrics of these applications, even across the most complex and distributed environments.
Here’s a look at the salient features of AppDyanmics’s Python monitoring capabilities.
- Monitors Python applications in real-time
- Correlates transactions across complex and distributed environments to provide a comprehensive view of the performance of Python applications and even your network in general
- Auto-discovers business transactions
- Ensures rapid identification and resolution of issues to avoid any impact on end-user experience
- Works well on applications that run on-premises or on the cloud
- Provides complete support for various frameworks and platforms, including Django, Flask, and Pyramid.
- Its APIs can be used to extend its functionality
- Enables you to manually instrument code for custom environments
- Visualizes and prioritizes performance issues
- Creates detailed call graphs to locate hot and slow spots in your network quickly
- Fixes errors proactively
- Pinpoints the specific queries that cause performance bottlenecks
Pricing: AppDynamics comes in four plans, and they are
- Infrastructure Monitoring Edition – $6 per month per CU core
- Premium Edition – $60 per month per CU core
- Enterprise Edition – $90 per month per CU core
- Accurate user Monitoring – $.06 per 1000 tokens
You can also click here for a custom quote.
Download: Click here for a free trial.
NewRelic for Python monitors your Python applications, collects the necessary metrics for analysis, and helps identify the performance bottlenecks, so the same can be resolved at the earliest.
Below are the features of NewRelic related to Python monitoring.
- Collects and analyzes business data to improve the performance of your applications
- Provides a ton of configuration options for easy customization
- Offers APIs to customize and extend the instrumentation
- Supports many frameworks and servers such as uWSGI and Gunicorn WSGI
- Provides distributed tracing if needed
- Generates multiple building blocks to customize your data
- Drives business decisions with the correct data
Pricing: NewRelic comes in four editions, and they are
Contact the sales team for custom pricing.
Download: Click here to get started.
Stackify is a tool that proactively monitors application performance by retracing users and constantly observing the behavior and performance of applications in production environments.
Here are the characteristics of Stackify:
- Aggregates all the logs in a central place for easy traceability
- Makes it easy to view and search through all the logs in a central location
- Configures and monitors automated log queries
- Identifies bottlenecks to improve your application continuously
- Tracks deployments
- Identifies slow dependencies
- Discovers your app’s performance
- Helps you to find and fix exceptions in the code
- Monitors exception rates
- Supports common reporting frameworks
- Provides code-level insights to retrace through your code
- Tracks the usage and performance of HTTP requests
- Creates custom dashboards to track the important events
- Aligns dashboards with your business goals
- Helps to create an engaging experience for your end-users
- Optimize resource performance with the resource breakdown report.
Pricing: Stackify offers four pricing plans to meet your custom needs, and they are
- Logs and Errors – $35 per month
- Retrace Essentials – $79 per month
- Retrace Standard – $199 per month
- Retrace Enterprise – Custom quote.
Download: Click here for a free 14-day trial.
Atatus is a full-stack python monitoring tool that provides complete visibility into the performance of your Python applications. It also helps to identify and solve issues related to your applications.
The features of this tool are:
- Captures all requests to your Python applications without requiring any changes to the source code
- Provides a clear picture of how your methods, database statements, and external requests impact your user’s experience
- Offers a complete picture of the most time-consuming database queries with a focus on the slow queries
- Instantly lists all the external requests that impact performance
- Visualizes transaction traces
- Provides a detailed overview of all HTTP failures
- Collects Python exceptions and crashes with full-stack frames
- Makes it easy to analyze the problem areas and address them quickly
- Diagnoses and fixes API failures
- Sends notifications through Slack, teams, Emails, PagerDuty, and more.
Pricing: The pricing depends on your needs, and there are four options to choose from, namely,
- APM plans – $49 per month per host
- RUM plans – $49 per month for 250,000 views
- Infrastructure plans – $7 per month per host
- Logs plan – $10 per month for 5GB per month and a retention period of seven days.
Download: Click here to get started.
Thus, these are some of the best Python monitoring tools available today. But, of course, the choice depends on your business needs, budgets, and the number and criticality of your Python applications.
These tools scale well to meet your requirements, and hence, choosing anyone can add value to your organization. That said, our editors suggest the ones that have the edge over the others.