Operations | Monitoring | ITSM | DevOps | Cloud

JC, the Director of Software Engineering, Cloud at LogicMonitor, shares how Cost Optimization enabled his team to shift to Cost-Intelligent Observability and tackle an unexpected and growing cloud bill. As engineers, we live and breathe performance. We obsess over latency, reliability, and uptime, the hallmarks of a healthy system. But there’s another metric that’s becoming just as critical: cost.

Load balancers are the primary entry points to distributed applications. By strategically directing the flow of incoming web traffic to specific endpoints, load balancers help optimize throughput and ensure the horizontal scalability of applications. In modern systems, load balancers often do more than their name suggests: Beyond basic load distribution, they analyze requests and route traffic based on a wide range of variables, such as client identity.

Modern organizations often operate from multiple locations. From retail stores to global enterprises, many companies rely on distributed wired and wireless networks to keep business-critical applications online. Aruba Central provides a centralized, cloud-based platform for managing that infrastructure at scale.

Modern IT teams are experimenting with AI agents. But individual agents, working in isolation are not enough. To truly achieve Agentic IT Operations, organisations need a platform — one that coordinates, governs, and contextualises AI-driven actions across the entire IT landscape. That’s where Interlink Software comes in.

Coroot is an open source observability tool that uses eBPF to collect telemetry directly from applications and infrastructure. One of the things it does is capture L7 traffic from TLS connections without any code changes, by hooking into TLS libraries and syscalls. Works great for OpenSSL. Works for Go. Then rustls enters the picture and everything stops being obvious. With OpenSSL, everything is nicely wrapped: From eBPF’s point of view this is perfect: Everything happens inside one call.

In the shift left era where it feels like we’re pushing everything as far to the start of the SDLC as we can, it may seem counterintuitive to shift anything right. That is, however, exactly what I suggest when it comes to generating metrics. How far you go to the right of the SDLC is a much more nuanced question and is dependent on a lot of factors, and on what metrics you’re talking about.

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.