Optimizing Node.js applications often involves sifting through complex performance data, trying to uncover hidden inefficiencies or bottlenecks. With N|Solid’s AI-powered profiling tools, you gain more than just data—you get actionable recommendations to diagnose and resolve issues with precision and speed. By leveraging predefined prompts and AI-powered analysis, the copilot not only highlights bottlenecks, inefficiencies, or anomalies but also provides clear guidance on how to address them.

We’re thrilled to announce an exciting new release of N|Solid, bringing powerful updates designed to enhance Node.js performance and scalability. This release introduces two major features: These updates mark important advancements for Node.js developers and operations teams. The gRPC transition ensures a solid foundation for scaling and future-proofing your applications, while the AI-powered profiling tools empower you to fine-tune your performance with increased precision.

At NodeSource, we are always striving to enhance the resilience, scalability, and openness of our tooling. Recently, we took a significant step forward by adopting gRPC in N|Solid —a widely used open-source protocol for efficient communication between systems. This move represents a major shift in how we transmit data internally while ensuring seamless continuity for our users.

AWS Lambda has become a cornerstone of serverless architecture, enabling developers to run code without provisioning or managing servers. However, as applications grow, managing shared code, dependencies, and runtime configuration across multiple Lambda functions becomes challenging. This is where Lambda Layers step in to streamline development and deployment. In this blog we will explore what Lambda Layers are, why they are needed, how they work, and much more.

Releasing a beta version of a Node.js package is a common practice when you want to share a new feature or a breaking change with testers or early adopters without affecting your stable users. Beta releases are tagged with a special version identifier (like 1.0.0-beta.0), making it clear that the version is pre-release and not production-ready. In this guide, we will cover the steps to release a beta version of your package using npm, ensuring a smooth and controlled release process.

In this article, you'll learn about N+1 queries, how to detect them with AppSignal, and how to fix them to speed up your Django apps significantly. We'll start with the theoretical aspects and then move on to practical examples. The practical examples will mirror scenarios you might encounter in a production environment. Let's get started!

Ever commit code and wonder how it’s faring in the pipeline? Let's make every status update as clear as day. Every time you push new code, a series of automated CI builds and checks spring into action, each telling a part of your project's story. This is where git commit statuses come in—they transform the complex results of these processes into clear, actionable insights. Think of them as real-time signals that indicate whether your code is ready to go live or needs a little more attention.

Efficient handling of asynchronous data streams is an important tool of modern application development. Kotlin Flows, part of the Kotlin Coroutines library, provide a flexible and elegant solution for working with such data streams. Kotlin Flows are part of Kotlin Coroutines – unlike traditional callbacks or RxJava handling, which can be clunkier and may not directly integrate with your existing code structure easily.

Platform engineering is a software development approach that combines DevOps principles to elevate the developer experience. It focuses on designing and constructing toolchains and workflows that promote self-service capabilities for software engineering teams. By addressing security, compliance, and operational efficiency, platform engineering enables organizations to build robust internal systems tailored to the needs of both developers and operations teams.