Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on API Development, Management, Monitoring, and related technologies.

From API to live dashboard - building a SquaredUp plugin with AI

No matter how fast we build, we'll never integrate with every tool. There are too many, new ones appear constantly, and some are too niche to ever reach the top of our roadmap. So if the tool you care about isn't supported yet, your options have been to wait for us to get to it, or build it yourself with our Web API plugin — a powerful, flexible option, though one that asks you to map out the endpoints, authentication and paging yourself.

Validate Spring Boot Upgrades with Traffic Replay

Spring Boot version upgrades—whether moving from 2.x to 3.x, 3.x to 4.x, or even minor bumps like 3.2.5 to 3.3.1—regularly introduce subtle, breaking changes that unit and integration tests miss. JSON serialization shifts, autoconfiguration reordering, and transitive dependency conflicts can silently alter your API contract.

API update: Full board management now available

We’re excited to announce expanded functionality for the StatusGator Boards API. You can now create new boards, update existing boards, and delete boards directly through the API. Previously, the Boards API only supported listing boards and retrieving board details. With these new capabilities, you can automate the complete board lifecycle – from provisioning new boards to managing ownership and cleaning up boards that are no longer needed.

The AI Code Explosion: Why Your Mocking Strategy is Breaking Down

The rise of AI-assisted coding has transformed how software is built. With tools generating entire features in seconds, the bottleneck is no longer writing code—it’s verifying it. Because AI can generate boilerplate and handle API integrations instantly, more service changes are being pushed into authentication logic, API calls, and configurations. Teams desperately need a way to verify these changes before merging, especially when the code touches external dependencies.

Testing AI Code is a Security Nightmare? #Speedscale #DevOps #Kubernetes #AICoding #SoftwareTesting

AI can write a feature in seconds, but where are you testing it? Sending production traffic, API payloads, and auth headers to a third-party SaaS is a massive security risk. In this video, we break down why the Bring Your Own Cloud (BYOC) model is the ultimate fix for DevSecOps. Learn how to safely test AI-generated code against real production traffic entirely within your own VPC or Kubernetes cluster. No data leaks, no massive DLP pipelines, and no endless masking rules.

How to debug REST Collector APIs with Cribl REST Collector Diagnostics

This video introduces the new REST Collector Diagnostics feature in Cribl, which helps you troubleshoot API collection issues faster. It’s designed for observability and data engineers who use REST Collector to pull data from external APIs and need deeper visibility into HTTP requests, responses, and errors.

The Bug Hiding in Your Production Traffic

Your logs showed 500 errors. The traces showed the dependency graph. Neither showed the actual bug, a DEL control character getting appended to the query string. This is how I found it. In this video I walk through Speedscale BYOC (bring your own cloud): capture real production traffic, store it in your own Elasticsearch cluster inside your VPC, pull it down locally with a single script, and reproduce the exact bug using proxymock. The data never leaves your environment.

Logs told me something broke. Traffic showed me what.

Here’s a problem I run into constantly: something breaks in production, I can see the 500 errors in my logs, but I can’t reproduce it locally. The trace shows me the dependency graph but not the actual request that failed. This is especially painful in microservices. I was looking at a CNCF example the other day (a simple demo app, like 4 pods) and it already had so many cross-service dependencies that understanding what broke required looking at the whole system at once.

Your AI agent is fixing the wrong service

Everyone wants an AI agent factory in 2026. Autonomous agents fixing bugs and shipping features while you sleep. I’ve been building toward that myself. But the error rates don’t support the fantasy. The best AI coding agents in the world fix about 50% of real bugs on SWE-bench verified. Half the time they fail. And AI-generated code produces 1.7x more issues than human-written code.