The Trillion-Dollar Questions Every Engineering Leader is Asking
Companies already spend more than $1 trillion a year trying to catch bad code before it ships. AI is making that job a lot more difficult.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Release Assurance vs. Test Automation: What's the Difference?
Test automation tells you what happened. Release assurance empowers you to decide what to do about it, closing the loop from business intent to production confidence.
How to access mainframe data stored in Db2 on z/OS
Automated data integration enables AI and analytics based on mission-critical operational data stored in IBM Z.
The "open" in Open Data Infrastructure means interoperability
Interoperability means the optionality to adapt to rapidly changing future demands.
Node.js Versions Explained: Why Running an Outdated Release Is a Business Risk
A Node.js application can continue starting, accepting traffic, and passing health checks long after the runtime underneath it has become unsupported. That creates a dangerous assumption: In reality, “running” and “supported” are two very different states. A Node.js release is more than a JavaScript executable.
What is Sauce Labs AURA? The AI-Unified Release Assurance Platform
AURA: AI-Unified Release Assurance is the world's only closed-loop agentic platform that authors, runs, and analyzes tests with human oversight, informed by 8.7B+ test executions. It takes you from business intent to production confidence at AI speed. From the founders of Selenium and Appium.
Duplicate API Tests Are Slowing You Down. Here's How Keploy Deduplicates them
Ever wondered why your test suite keeps growing even though you're testing the same few flows over and over? 👀 In this video, we break down how Keploy automatically detects and removes duplicate tests - so your suite stays fast, lean, and actually trustworthy to review.
Announcing Confluent Platform 8.3: Powerful Apache Flink SQL operations, Easier KRaft Migrations, Expanded Monitoring and more.
Platform teams want to maximize the value of data in motion, but separate workstreams for stream processing, monitoring, KRaft migrations, and data governance create friction as environments grow. As a result, teams spend more time managing operational overhead and less time building. Today, we’re excited to announce Confluent Platform (CP) 8.3.0, built on Apache Kafka 4.3.0, reinforcing our core capabilities as a data streaming platform.
Orchestrating Runtime Resilience: The Definitive Guide to Self-Healing Test Frameworks
Enterprise teams depend on automated testing to sustain rapid release cycles, yet scaling quickly reveals a major bottleneck: the maintenance footprint. Consider a financial enterprise running a nightly regression suite of 3,000 scripts. A developer updates the checkout UI, renaming a submit button’s class from-submit to-primary. The core payment logic stays completely untouched, yet 400 test cases fail overnight.
AI Debugging: How to Use AI to Find and Fix Bugs Faster
At its simplest, AI debugging automates repetitive coding tasks like searching logs, reading stack traces and comparing sessions. But good AI debugging is a much more challenging concept that relies on focused context, runtime evidence and structured investigation paths. In this post we’ll show you how to debug with AI, not just productively but also responsibly. Let’s get into it.