Systems | Development | Analytics | API | Testing

API testing gets harder as it grows: fragmented tools, brittle scripts, thousands of endpoints, and external dependencies that block progress. SmartBear ReadyAPI lets teams ship production-ready APIs faster by validating functionality, performance, and security in one test, with virtualization built in – no separate tools to juggle. In this Demo Den, Thomas Hurley, senior manager of product management at SmartBear, shows how one test does the work of three, so teams cut maintenance time and stop waiting on external dependencies.

Learn how to trace complex multi-hop transactions across microservices when OpenTelemetry isn't available or trace parents get lost. This quick tutorial demonstrates how to use full-text search in proxymock (a free CLI and UI tool) to isolate user journeys (like looking up a specific username) and instantly generate waterfall tracing views. Whether you are working locally or in a Kubernetes cluster, you can record API traffic, visualize multi-hop requests, and easily transition those captures into load or regression tests.

This video explains how to trace a user through older or inaccessible services using identifiable information like emails or usernames when OpenTelemetry traces are unavailable.

AI tip: For pull requests, let your AI agent take the first pass before your team ever sees it. That's the workflow Ilia Mogilevsky, Software Engineering Manager at SmartBear, built. By packaging prompts into a skill loaded with Git history, Jira context, and CI checks, he turned a basic AI assistant into a reviewer he trusts. The skill then generates a structured report with approval-ready fixes. Accept the changes, adjust what's off, and push – review cycles shrink and deploys move faster.

A new Google white paper suggests that as AI writes the majority of our code, the role of a software engineer is shifting from writing applications to performing rigorous validation and QA.