Systems | Development | Analytics | API | Testing

Load Test PostgreSQL Instantly using Production Recordings

The first PostgreSQL post ran on a laptop: a demo app, a Docker container, and the proxymock CLI. That is the fastest way to see the idea. It is also not where your database problems live. Your real query mix lives in the cluster, where a Java service with a connection pool, an ORM and a schema migration tool sends the statements nobody wrote by hand. This post deploys an open source banking app to Kubernetes and records the queries one of its services sends to PostgreSQL.

How to Automatically Fail Over Between LLM Providers | Kong AI Gateway

Learn how to automatically switch between LLM providers when your primary provider becomes unavailable. In this AI Gateway Discovery video, we configure automatic failover using Kong AI Gateway’s Priority load balancing algorithm. You’ll learn how to assign models to priority groups and fall back to a backup group when all targets in the preferred group are unavailable. Follow along to set up automatic LLM failover and make your AI applications more resilient to provider outages.

Insurance API Integration: 7 Platforms for Connecting Carriers, TPAs, and Insurtechs

Insurance companies face a unique data integration challenge that most generic platforms cannot solve. Your benefits administration platform may connect via REST API to modern HR systems, while another partner still sends eligibility files over SFTP. Enrollment and eligibility workflows commonly use EDI 834 transactions, while claims workflows may involve X12 837 claims and 835 remittance data.

The Missing Piece in Your AI Coding Agent #aiagents #aitools #devops #debugging #softwareengineer

Stop making your AI coding agent guess how your app works with massive prompts. We feed live API traffic and runtime evidence directly into your agent so it can automatically detect bugs, run replays, and fix code fast! Learn more: speedscale.com.

BrowserStack vs. TestComplete: Which automation tool fits your stack?

Every QA team carries a list of things it hasn’t gotten to yet, and that list tends to grow at about the same rate as the application portfolio. There are more tests to automate than there is time to write them, coverage that stops short of the applications nobody wants to touch, and workflows that have stayed manual long enough to become part of how the team works. Automation chips away at that list without ever quite emptying it, because the constraint is rarely how fast the existing tests run.

Catch bugs and UI issues automatically with QA agents | SmartBear BearQ

In this video, you’ll see how SmartBear BearQ's QA agents catch bugs, UI and UX issues, and accessibility gaps automatically as they explore or test your applications, zero test script writing necessary. Whenever the Explorer Agent investigates your app or the Tester Agent runs a test, the QA Lead Agent is watching in the background for anything that looks wrong. Each suspected issue arrives with a clear title, a description, expected versus actual behavior, steps to reproduce, and a link to the evidence that shows exactly when it was found.

Confidence in AI-generated code is rising in lockstep with its failure rate

If you only read the headlines this year, you’d think AI makes shipping good software easier than ever. Yet, this was the year of very public AI-coding incidents. PocketOS’ production database deletion and a Vercel AI agent shipping unverified code are just two examples of AI-authored code shipped with confidence that turned out to be wrong. And, of course, these AI-coding incidents are distinct from Agentic AI orchestration incidents like the HuggingFace hack by OpenAI.