Operations | Monitoring | ITSM | DevOps | Cloud

The OTLPMetricsWriter is a new Icinga 2 feature available since v2.16 that exports check plugin performance data as OpenTelemetry-compliant metrics via the OTLP HTTP protocol. With a single configuration object, it connects Icinga 2 to any OTLP-compatible backend like Prometheus, Grafana Mimir, Datadog, Elasticsearch, VictoriaMetrics, and more.

By Doreen Jacobi, CEO of Derdack Corp Modern IT environments generate a high volume of alerts intended to improve detection and response. However, increasing alert volume does not necessarily improve operational outcomes. Alert fatigue is not simply a function of quantity. It is a predictable consequence of how humans process repeated stimuli, manage limited cognitive resources, and make decisions under sustained load.

When we talk about patient experience in hospitals, the conversation usually centers on clinical outcomes, bedside manner, or discharge satisfaction scores. But a growing body of research suggests that something far more basic, how quickly and clearly a care team communicates, may matter just as much. This isn’t just true inside the hospital walls.

The way you write code is changing, which means the way you observe your systems and respond to issues needs to change, too. Engineers today spend much of their day working via command line, as agentic tools like Cursor and Claude Code have become highly effective at handling many day-to-day engineering tasks. This greatly accelerates code generation, but it doesn't solve for the context switching that comes when you have to jump into another tool that's not part of this new, faster workflow.

To simulate real user behavior, performance tests often rely on API keys, tokens, or credentials to interact with real systems. But as your testing suite grows, this sensitive data can start to sprawl across scripts, configs, and environments, increasing the risk of exposure and making tests harder to manage and maintain. To address this challenge, we’re rolling out secrets management for Grafana Cloud k6, the fully managed performance testing platform powered by k6 OSS.

Many teams remain bogged down by operational chaos and manual drudgery, even with access to a variety of automation solutions. These tools often operate in silos, creating disconnected islands of automation that require significant human effort to bridge. Agentic AI offers a path forward, creating a cohesive system that can intelligently and autonomously handle complex operational workflows.

The incident is over. The service is back up. The monitoring dashboard is green, the on-call engineer has stood down, and the post-incident review is on the calendar for Thursday. But there is a question that separates good operations teams from great ones: do you actually know what that incident cost you in terms of reliability commitments? Whether you breached an SLO. Whether a customer-facing SLA is now at risk.

Notes from a finance leader whose job this is. A few weeks ago, I traveled to Philadelphia for a conversation with a prospective CloudZero customer. We’d been working with the prospect’s engineering team for some weeks, demoing our platform in view of the RFP they’d drawn up. This stage had gone well, and so the next step was talking it over with the prospect’s CFO. We expected a conversation centered around the key criteria in the RFP.

CloudZero's new AWS Kiro integration puts cost intelligence directly in your agentic IDE. Ask plain-language questions about spend, attribution, and cost-per-serve without leaving your development workflow. We see a similar pattern playing out across engineering teams running agentic development tools: code gets shipped fast, something moves in the cost data, and understanding why still requires leaving your environment entirely.

Guest blog by Florent Goutailler, Associate Professor, Télécom Saint-Etienne, France Teaching real-time embedded systems has always involved a fundamental challenge: the most critical behaviors – task scheduling, timing, and concurrency – are largely invisible at runtime. When students begin working with a real-time operating system such as FreeRTOS, they are introduced to concepts like scheduling, task prioritization, semaphores, and inter-task communication.