Operations | Monitoring | ITSM | DevOps | Cloud

We’re pleased to announce new enhancements to the StatusGator API platform that make it easier to automate how you monitor third-party services. The new Service Search, Create Service Monitor, and Update Service Monitor endpoints give developers more control over how monitors are created, labeled, and maintained across projects and environments. These APIs are designed for teams that integrate StatusGator into their deployment processes, internal tooling, or infrastructure automation.

Cover letters are supposed to help you shine, but most of them blur together into the same polite, forgettable paragraphs. The intention is good (“I want them to notice me!”), but the execution… not so much. So, here’s a simple, honest guide to writing a cover letter that actually works, especially if you’re applying to Checkly. Spoiler: shorter is better. And authenticity in this AI era is better than perfect polished perfection.

Continuing my adventure to have Monitive being run by AI Agents, I had some brainstorming sessions with... well... AI. I was impressed about the maturity of the discussions one can have with ChatGPT 5.1 Pro and Claude Code Opus 4.5.

One year ago, at AWS re:Invent, we launched CloudZero Advisor, a free, standalone AI assistant that enables anyone to ask questions about cloud spend in plain language. It was the first experiment of its kind in FinOps, a chance to see what people really wanted to know when cost data finally became conversational. Over the past year, Advisor has become a learning engine.

Over the last few years, AI has quietly shifted from a fascinating experiment to a core operational system. Enterprises aren’t just building prototypes anymore — they’re deploying LLMs into production environments where uptime directly affects customer interactions, revenue flows, and business continuity. AI has essentially become a new layer of critical infrastructure. Because of that shift, the definition of “reliability” is changing.

AI coding assistants are quickly becoming a core part of software engineering workflows, helping developers write, refactor, and review code faster. But without effective monitoring, it can be difficult to know whether these tools are performing reliably and proving useful to engineers. As organizations scale their use of tools like Claude Code, key questions emerge.