Operations | Monitoring | ITSM | DevOps | Cloud

Technology leaders spent the past decade investing heavily in visibility. They expanded monitoring footprints, adopted cloud-native observability tools, integrated analytics dashboards, and layered on automation intended to streamline detection. Every addition promised deeper insight. Every initiative aimed to bring clarity to increasingly complex environments. Yet operations feel more chaotic, not less. Outages move faster. Incidents cross more boundaries. Signals appear without context.

Have you noticed AI recently? Yeah, us too. Generative AI is wreaking havoc on the software status quo, and that includes licensing, and that generates … opinions. Sentry has a long history of having opinions about software licensing. We started life as an unlicensed side project in 2008, then went through BSD, to BSL, to writing our own license, FSL.

Not long ago, cloud cost was an engineering problem. FinOps teams owned it, finance leaned in occasionally, and everyone else stayed out of it. Now, that’s changed. AI changed who has skin in the game. CFOs get asked about it in board meetings. CEOs field questions on earnings calls. The audience for cloud cost management has exploded — and that means the conversation CloudZero is built to enable isn’t only a technical one, it’s a business one.

We hear a lot of war stories from the teams we work with. Horror stories about cloud bills, surprise overages, and the infrastructure decisions that seemed perfectly reasonable at the time. This one comes from Erik Dasque, CTO at Allure Security. It involves a junior developer, a Kubernetes CronJob, and a recurring bill that, if not caught, would have happened on a yearly basis.

AI is changing both what you build and how you build it - at the same time. Today, Harness is announcing two new products to secure both: AI Security, a new product to discover, test, and protect AI running in your applications, and Secure AI Coding, a new capability of Harness SAST that secures the code your AI tools are writing.

--- ‍Key Takeaways --- AI can generate code in seconds. It still can’t ship software safely. That gap isn’t about model quality or prompt engineering. It’s about context, and most software organizations don’t have a system that accurately reflects how pipelines, services, environments, policies, and teams actually relate to each other. Without that context, AI doesn’t automate delivery. It amplifies risk.