Stop Overpaying the Software Test Tax
AI solves the velocity problem, but confidence is still holding testing teams back.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
The latest News and Information on Software Testing and related technologies.
HealthTech QA Services
A clinical decision support tool suggests the wrong medication dose. A telehealth platform exposes 50,000 patient records. An AI diagnostics chatbot confidently gives incorrect test results. These are not just rare cases; they are real risks when healthcare software is released without proper HealthTech QA Services and healthcare software testing. Healthcare software cannot afford mistakes. In other industries, bugs can cause financial loss or inconvenience.
Stop Chasing Ghosts, Use Observability to Find Real Performance Gremlins
Performance testing without observability is like diagnosing a sick patient using only a thermometer. You get one number. You miss everything that matters. Observability-driven performance testing combines load testing with metrics, logs and distributed tracing to identify not just when performance degrades, but exactly why.
SAP testing is broken. Agentic AI is how we fix it.
Software testing has a bad rap for bottlenecks — and nowhere is that truer than in the SAP world. An overwhelming majority of SAP orgs continue to rely on manual testing practices that can consume up to 30% of implementation budgets, making QA out to be a persistent roadblock to transformation. To be fair to SAP QA teams, the issue is not as much about inefficiency as complexity.
AI Coding Agents Break What Works
Your AI coding agent just made every test pass. Ship it, right? Not so fast. A growing class of AI-generated bugs doesn’t come from writing bad code. It comes from the AI changing working code to accommodate its own mistakes. This isn’t a theoretical risk. It’s happening now, in production codebases, and it’s harder to catch than any bug the AI might introduce from scratch.
Beyond the Dashboard: Using Telemetry to Solve the Unknown Unknowns of Performance
Your dashboards are lying to you, not through bad data, but through incomplete data. They show you what you told them to watch. They cannot show you what you did not know to ask. Telemetry-driven performance engineering uses metrics, logs, traces and profiling to detect and diagnose issues that traditional dashboards cannot capture. The failures that hurt most are not the ones you predicted; they are the ones your monitoring was never designed to catch.
Real Device Access API - Product Demo
Building Internal Developer Tools with a Device Lab API: Sessions, Streaming, Logs, and Automation For years, platform teams have had to choose between costly internal device labs for control or public clouds with limited access. That tradeoff ends with the Real Device Access API, the first solution to treat mobile devices as Infrastructure-as-Code—delivering direct, low-latency access to real devices without framework constraints. See how teams can retire internal racks while running any workflow on fully managed infrastructure they control programmatically.
BearQ Q&A recap: Top questions from SmartBear's live event
Asked a question in our BearQ livestream? We’ve got your answers. We received 100+ questions during the event and couldn’t get to all of them live, so we pulled together the most common ones and answered them here. In this video, we break down what BearQ can test, how it handles authentication and complex workflows, how the AI works behind the scenes, how it fits into your existing tools, and even how to get early access.
Create tests in Reflect directly from your coding agent!
If you’ve used Claude Code, GitHub Copilot, Cursor, or any coding agent, you already know the feeling. You describe what you want in plain language, the agent figures out the steps, and you watch it work. When something goes wrong, it backs up and tries a different approach. Reflect now brings that same agentic workflow to test automation. Through the SmartBear MCP server, any coding agent that supports MCP can connect to Reflect and build tests from high-level objectives.
The 4 Golden Signals of Monitoring Explained
As a team, we have spent many years troubleshooting performance problems in production systems. Applications have become so complex that you need a standard methodology to understand performance. Our approach to this problem is called the Golden Signals. By measuring these signals and paying very close attention to these four key metrics, providers can simplify even the most complex systems into an understandable corpus of services and systems.