Microservices are now the architecture of choice for many developers when crafting cloud-native applications. A microservices application is a collection of loosely coupled services that communicate with each other, enhancing collaboration, maintainability, scalability, and deployment. There are several options for enabling this communication between microservices. When it comes to Python, gRPC and REST are two extremely popular directions to go.

Python's logging system provides powerful tools for application monitoring, debugging, and maintenance. This comprehensive guide covers everything from basic setup to advanced implementation strategies, helping you build robust logging solutions for your Python applications.

Sentry is committed to helping developers fix broken code quickly and effectively. In this article, we’ll cover a range of intermediate to advanced techniques for debugging Python code using VS Code and the Sentry Python SDK.

Master Python logging with structlog! Learn how structured logs improve debugging, observability, and performance in your apps.

An audit and error trail is one of the core pillars of a well-designed software application, regardless of the programming language used to build it. This trail typically comes in the form of logging. When your application produces useful, rich logs, you are better equipped to successfully maintain a production-grade system and troubleshoot any issues that might arise. When it comes to distributed Python applications, having correlated logs for each system is important for debugging.

Here comes the long-awaited release of three new Python Connectors for Dynamics 365 Business Central, Excel Online, and Google Sheets. These Connectors are designed to simplify data integration and maximize productivity for developers working with these platforms. From now on, it will be extremely easy to connect Python applications directly to Dynamics 365 Business Central, Excel Online, and Google Sheets, enabling accurate create, read, update, and delete operations on stored data.

At Sentry, we don't just build debugging tools for developers—we use them ourselves. This story demonstrates how we leveraged our own platform to solve a mysterious performance issue that was causing significant latency spikes in our critical infrastructure which is used in nearly every backend request.

In the first part of this series, we explored how AppSignal can significantly enhance the robustness of Open edX platforms. We saw the challenges that Open edX faces as it scales and how AppSignal's features — including real-time performance monitoring and automated error tracking — provide essential tools for DevOps teams. Our walkthrough covered the initial setup and integration of AppSignal with Open edX, highlighting the immediate benefits of this powerful observability framework.

Debugging Python code is crucial for guaranteeing the uptime and performance of your application, and logging in Python is a great solution to streamline your debugging workflow. Python, a general-purpose programming language, includes a logging module in its standard library, offering a flexible framework for generating log messages from Python programs.

Designed in the early 1990s Python was built to emphasize code readability and on the principle that there should be one way to do things. Python is one of the most popular programming languages and is utilized for a range of purposes including machine learning, web applications, and data analysis.