Systems | Development | Analytics | API | Testing

Choosing the appropriate development tool can either improve or inhibit your coding efficiency. Two tools that can confuse developers are Cline and Cursor because they are intended for different use cases in the software development lifecycle. Developer’s must understand the difference between Cline vs Cursor so that they can improve their workflow and select the appropriate tool for their project requirements.

Are you still running Node.js 12, 14, or even older versions in production? If so, you’re facing a serious challenge: these versions have reached End-of-Life (EOL) and no longer receive official updates or security patches. For many organizations, especially those operating on legacy environments like RHEL 7 or Ubuntu 18.04, upgrading to the latest Node.js version isn’t always feasible.

Multiplayer is the only session recorder that combines frontend replays with unsampled backend traces, stitched together automatically. You don’t have to choose between drowning in noise or missing the critical data. Backend tracing is the backbone of understanding how modern distributed systems behave. Each request generates a chain of spans as it travels through your services and components: what happened, how long it took, and whether it failed.

This article originally appeared on DevPro Journal. We’re sharing it here for our audience who may have missed it. QA’s job has always been simple: find the bugs before your customers do. There was a time when that meant checking every corner of an application by hand, clicking through countless possible user scenarios. Today, with software moving faster and expectations higher, a tiny slip can cost your business. Testing that’s quick, precise, and thorough has never been more critical.

Turn quality into a strategic advantage—accelerate outcomes with Sauce intelligence.

Turn quality into a strategic advantage—accelerate outcomes with Sauce intelligence.

Your data warehouse holds untapped potential for generative AI (GenAI), but there's a problem: most systems lack the right connection to make this work seamlessly. Enter the Data AI Gateway - a middleware solution designed to bridge the gap between massive datasets and AI systems. This tool not only streamlines integration but also tackles key challenges like data security, real-time access, and cost management.

This is part one of a series exploring how Kong AI Gateway can be used in an AI Agent development with LangGraph. The series comprises three parts.

The Model Context Protocol (MCP) is quickly becoming a foundational layer for AI systems. It enables large language models and AI agents to interact with external tools and data sources over standardized JSON-RPC interfaces. By doing so, MCP transforms how intelligent applications consume APIs. Reading local files, controlling IoT devices, orchestrating backend workflows—MCP servers act as structured gateways between AI and your business logic.