Top Tools for Python Monitoring
Helios, Prometheus, Datadog, New Relic, and more
Python has undoubtedly taken the programming world by storm, captivating developers with its elegant syntax, extensive libraries, and remarkable versatility. As predicted, it has become the world’s 4th most popular programming language. However, with the expanding Python community, developers need to remain vigilant in areas such as monitoring, debugging, and security to ensure the creation of high-performing and robust Python applications. Thus, this article aims to delve into monitoring Python applications, presenting a comprehensive list of top tools available. Whether you are a developer, a DevOps engineer, or a system administrator, this invaluable compilation will equip you with the knowledge to select the most suitable tools, enabling effective monitoring and optimization of your Python projects.
1. Helios
Source: https://gethelios.dev/
Helios is a powerful observability platform that provides actionable insight into your Python application flow. It offers end-to-end visibility across microservices and serverless functions, databases, and 3rd party APIs while providing customizable alerts and notifications to help you stay on top of critical issues. You can check out their sandbox or use it for free by signing up here.
Features of Helios
- Acts as a single source of truth for your application.
- Workflow recreations for Lambda invocations, HTTP requests, Kafka, and RabbitMQ messages.
- Performance bottleneck analysis.
- Provides visualizations on complex sync and async flows (HTTP requests, gRPC calls, serverless invocations, messaging queues, event streams, and more).
- Supports various programming languages, including Python, JavaScript, Node.js, Java, Ruby, .NET, Go, C++, and Collector.
- Provides real-time visibility into the performance and health of your Python applications.
2.
Source: https://www.datadoghq.com/
Datadog is another popular monitoring tool that helps developers collect important information like stack traces, logs, and metrics. With Datadog APM, you can quickly find and fix any issues that might slow down your Python code. In addition, it works well with many other tools and databases so that you can use it with your favorite frameworks and databases without any trouble.
Features of Datadog
- Real-time monitoring for servers, databases, containers, cloud services, and more.
- Customizable and interactive dashboards to create visualizations and reports based on monitoring data.
- Alerting rules to notify you when certain conditions are met, like high CPU usage.
- Offers a wide range of integrations with third-party tools and services, including cloud providers.
3. New Relic
Source: https://newrelic.com/instant-observability/python
New Relic is a complete monitoring platform that allows you to monitor, troubleshoot, and optimize software applications and infrastructure. In addition, you can get real-time insights into application performance and behavior to deliver reliable and high-performing user experiences.
Features of New Relic
- Programmatically analyzes transaction, error, and database query traces to identify performance bottlenecks.
- Supports multiple Python frameworks like Django, Flask, CherryPy, and more.
- Supports mobile device monitoring.
- Provides customizable visualizations.
- Can handle large-scale deployments and high data volumes.
4. Prometheus
Source: https://prometheus.io/
Prometheus is a widely used open-source monitoring and alerting toolkit for monitoring Python applications. It is designed for time series data collection, querying, and alerting. Prometheus offers a flexible data model and supports rich query expressions. It has a vibrant community and a large ecosystem of exporters and plugins.
Features of Prometheus
- Collects four Python core metrics types: Counter, Gauge, Histogram, and Summary.
- Utilizes PromQL to generate graphs, tables, and alerts based on the collected time-series data.
- Seamlessly integrates with Python frameworks such as Django and Flask.
- Benefits from built-in browser and Grafana integration for creating visually appealing visualizations.
5. AppDynamics
Source: https://www.appdynamics.com/supported-technologies/python
AppDynamics is an application performance monitoring tool that offers Python monitoring capabilities. It provides end-to-end visibility into the performance of your Python applications, including code-level insights and transaction tracing.
Features of AppDynamics
- Python code-level diagnostics for enhanced debugging and troubleshooting.
- Visualizes application topology and map dependencies.
- Real-time detection of errors and exceptions to ensure timely resolution.
- Automatically discovers and monitors business transactions for improved visibility.
- Supports popular Python frameworks, including Django, Flask, and Pyramid.
6. Sentry
Source: https://sentry.io/for/python/?original_referrer=https%3A%2F%2Fsentry.io%2Ffor%2Fpython%2F#
Sentry is an open-source error tracking and tracing platform with Python support. Apart from that, Sentry supports profiling, integrations, session replay, performance monitoring, and code coverage report generation, making it a complete package for your application. Sentry can be used as a Software-as-a-Service (SaaS) or an on-premise solution.
Features of Sentry
- Real-time application monitoring.
- Automatically detects crashes and provides comprehensive crash reports.
- Supports customized queries.
- Seamlessly integrates with various collaboration tools such as GitHub, Slack, and Jira.
- End-to-end distributed tracing.
- Supports over 30 programming languages, including JavaScript, Python, Ruby, Node.js, Go, .Net, Andriod, and iOS.
7. Site24x7
Source: https://img.site24x7static.com/images/custom-linux-windows-plugins.png
Site24x7 is a cloud-based monitoring platform with real-time insights, customizable dashboards, and alert mechanisms. You can use Site24x7 with your websites, servers, applications, networks, and cloud infrastructure to enhance their performance and user experience.
Features of Site 24x7
- Highly customizable dashboards.
- Tracks website performance across various geographic locations for a global perspective.
- Records and simulate multi-step user interactions.
- Supports Java, .NET, Ruby, PHP, Node.js, and mobile platforms.
- Supports cloud cost management.
Conclusion
In conclusion, monitoring plays a pivotal role in enhancing the performance and dependability of Python applications. Throughout this article, we explored seven top tools for Python monitoring, each bringing its distinctive features and capabilities to the table. For instance, tools like Helios offer comprehensive application visibility, empowering developers to swiftly identify and resolve any encountered issues with minimal time and effort. Additionally, Sentry presents an all-in-one monitoring solution by amalgamating various tools. By incorporating these suggestions into your monitoring practices, you can effectively monitor and optimize your Python projects easily and efficiently. Thank you for reading, and may your Python endeavors be successful and seamless.
