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Harness surveyed 500 security practitioners and decision makers responsible for securing AI-native applications from the United States, UK, Germany, and France to share findings on global security practices. The State of AI-Native Application Security 2025 dives deep into AI visibility and the changing landscape of security vulnerabilities. If 2024 was the year AI started quietly showing up in our workflows, 2025 was the year it kicked the door down.

Welcome to CloudZero’s inaugural Cloud Economics Pulse! This is our monthly snapshot of how cloud spend is evolving across providers, services, and emerging AI workloads. Each month, we’ll surface key trends, highlight where the money’s moving in cloud spend, and offer practical insight to help FinOps and cloud cost teams stay on top of things. October — and preceding months — shows a turbulent stretch for cloud economics.

If you’ve ever opened your Google Cloud bill and felt confused, you’re not alone. Costs in GCP can spike up fast. One project here, a few APIs there, until the total looks nothing like what you expected. That’s because Google Cloud pricing is built for flexibility. You pay for what you use, across dozens of services, each with its own rules, discounts, and data charges. It’s robust, but also easy to lose sight of what’s driving your spend. The good news?

Go’s os.Root feature, introduced in Go 1.24, is designed to improve filesystem security by restricting operations to a specific directory, making it much harder for attackers to exploit path traversal vulnerabilities.

Some parts of a system don’t lend themselves to quick instrumentation changes. You might have a production binary that hasn’t been rebuilt in years, or a stack made of several languages where each team manages telemetry differently. In those situations, getting consistent signals often means touching code you’d rather leave alone or coordinating updates across many services. OpenTelemetry eBPF Instrumentation (OBI) approaches this from the kernel side.

There’s a viral saying folks use about flaky crushes, spouses, and forgetful friends: "if he wanted to, he would." The idea is straightforward: when someone cares, they make the effort. As it turns out, the same principle applies surprisingly well to AI. Systems, like people, have things they "want" to do. Each model has patterns of reasoning and synthesis it performs naturally.

Some of the team at Sentry spent this past quarter fixing bugs, more than 800 to be exact. Among them was a complex issue causing transaction spikes in our own Sentry project. Using Sentry Logs, we were able to investigate, trace the root cause, and resolve the problem.

Active Telemetry is the evolution in how organizations collect, process, and use observability data. In traditional observability, telemetry is passive: systems emit logs, metrics, and traces that are stored and visualized after the fact. This model worked when systems were simpler and changes were predictable. But in today’s world with distributed microservices, Kubernetes, and AI workloads, passive telemetry can’t keep up. Active Telemetry changes that.

The digital landscape has transformed dramatically, and with it, the demands on our systems have grown exponentially. Traditional monitoring tools struggle to provide sufficient insight into complex, distributed, cloud-native environments. Observability is the answer, moving beyond merely knowing "what" is happening to understanding "why" it's happening, and its impact on user experience and business outcomes.

We’re thrilled to share that Redgate Software has been recognized as a ‘Strong Performer’ in the 2025 Gartner Peer Insights Voice of the Customer for Infrastructure Monitoring Tools category with our Redgate Monitor solution. We believe this recognition is a reflection of the trust and feedback from the people who matter most: our customers.