Systems | Development | Analytics | API | Testing

Real-Time Observability for Node.js - Without Code Changes

Observability isn’t a luxury, it’s a necessity. But for teams managing large Node.js applications, getting real-time visibility into performance, memory usage, async behavior, and security can be a complex and risky endeavor, especially if it means modifying your production code. That’s where N|Solid by NodeSource changes the game. Imagine getting deep, real-time insights into your Node.js applications without touching a single line of your business logic.

Ultimate Guide to API Latency and Throughput

Latency and throughput are the two most important metrics for API performance. If your API feels slow or struggles with heavy traffic, understanding these is your first step to fixing it. Latency: The time it takes for a request to go to the server and back (measured in milliseconds). Think of it as how quickly a single request is handled. Throughput: How many requests your API can handle in a second (measured in requests per second). It's about your system's capacity.

What is Alpha Testing?

What’s the difference between a software launch that builds customer confidence and one that becomes a costly disaster? Often, it comes down to how thoroughly the product was tested internally before anyone outside the company ever saw it. he irony is that alpha testing is often the most cost-effective phase for catching serious issues, yet it’s frequently the first thing cut when timelines get tight.

P2P Payments Space And What Caused Its Rapid Growth?

Have you ever paused to think about how fast money moves today? No paperwork, no waiting in line, just a few taps, and it’s done. For industry leaders, this raises a crucial question: Are we doing enough to keep pace with the evolving consumer expectations in the P2P payments space? Global’s peer-to-peer (P2P) payments landscape has seen an extraordinary transformation over the last few years.

New With Confluent Platform 8.0: Stream Securely, Monitor Easily, and Scale Endlessly

At Confluent, we’re committed to building the world's leading data streaming platform, which gives you the ability to stream, connect, process, and govern all of your data and make it available wherever it’s needed—however it’s needed—in real time. Today, we're excited to announce the release of Confluent Platform 8.0! This release builds on Apache Kafka 4.0, reinforcing our core capabilities as a data streaming platform.

How To Reduce Regression Testing Time? 5 Actionable Strategies

Regression testing is indeed one of the most time-consuming part of software testing: repetitive, tedious, and requiring high volume of executions. And yet, you can't ignore regression testing. It is the guardrail preventing bugs from slipping into production. But if you don't try to reduce the time it takes to do regression testing, it becomes counter-productive, very soon.

Vibe-Coding Meets QA: What Happens When AI Writes 30% of Your Code?

With the rapid adoption of AI-driven coding tools, software development is experiencing a seismic shift. Increasingly, developers rely on tools like GitHub Copilot and other generative AI solutions (collectively termed “vibe-coding”) that now account for roughly 30% of code output in leading organizations. This trend raises significant questions for QA teams: What happens when AI significantly contributes to the codebase, and how does this reshape the landscape of software testing?

Tricentis unveils three major steps in AI-powered software testing

Tricentis has just introduced three industry-first innovations that mark a major leap forward in autonomous software testing. Whether you’re already using Tricentis solutions or exploring smarter ways to scale your testing strategy, these advancements unlock a new level of flexibility, intelligence, and productivity for enterprise software quality.

Measuring the Value of Data Products

Today’s savviest business organizations rightfully recognize data as an essential asset. However, measuring data value across the entire data estate is challenging due to its inherent complexity. By breaking data down into smaller units that are business-outcome centric — data products — organizations can more accurately and reliably assess their value.