Operations | Monitoring | ITSM | DevOps | Cloud

Introducing MicroCloud Cluster Manager

Today, we’re excited to introduce the beta release of MicroCloud Cluster Manager, a new way to discover, organize, and operate your MicroCloud environments from a single, unified interface. MicroCloud is an open source cloud platform that makes it simple to create lightweight, resilient clusters anywhere. As teams scale from one cluster to many, visibility and coordination quickly become essential. Cluster Manager is built to solve exactly that.

Best On-Call Management Software for Teams that Need Faster Response Time

Teams running modern infrastructure can’t afford slow incident response. On-call management software ensures the right person is alerted instantly, incidents are escalated intelligently, and downtime is minimized. This guide breaks down the best on-call management software for 2026, helping teams choose the right platform based on their specific use case, response requirements, and operational complexity.

How to monitor LLMs in production with Grafana Cloud,OpenLIT, and OpenTelemetry

Moving a large language model (LLM) application from a demo to a production‑scale service raises very different questions than the ones you ask when playing with an API key in a notebook. In production, you have to answer: How much is each model costing us? Are we keeping latency within our service‑level objectives? Are we accidentally returning hallucinations or toxic content? Is the system vulnerable to prompt‑injection attacks?

Observe your AI agents: Endtoend tracing with OpenLIT and Grafana Cloud

In another post in this series, we discussed how to instrument large language model (LLM) calls. This can be a good starting point, but generative AI workloads increasingly rely on agents, which are systems that plan, call tools, reason, and act autonomously. And their non‑deterministic behavior makes incidents harder to diagnose, in part, because the same prompt can trigger different tool sequences and costs.

Monitor Model Context Protocol (MCP) servers with OpenLIT and Grafana Cloud

Large language models don’t work in a vacuum. They often rely on Model Context Protocol (MCP) servers to fetch additional context from external tools or data sources. MCP provides a standard way for AI agents to talk to tool servers, but this extra layer introduces complexity. Without visibility, an MCP server becomes a black box: you send a request and hope a tool answers. When something breaks, it’s hard to tell if the agent, the server or the downstream API failed.

Instrument zerocode observability for LLMs and agents on Kubernetes

Building AI services with large language models and agentic frameworks often means running complex microservices on Kubernetes. Observability is vital, but instrumenting every pod in a distributed system can quickly become a maintenance nightmare. OpenLIT Operator solves this problem by automatically injecting OpenTelemetry instrumentation into your AI workloads—no code changes or image rebuilds required.

How to migrate your paging tool without breaking your team

Most engineering teams don’t migrate their on-call and paging systems unless absolutely necessary. No matter how painful their current solution, it's one of those changes that people put off for as long as possible because the cost is real. The disruption, the retraining, the risk of missing a critical page during the transition. It's not something you do on a whim.

Margaret Hamilton Coined "Software Engineering" Because Code Deserves the Same Rigor as Bridges

During International Women’s Month, we celebrate women whose technical work changed entire industries. But the lessons from engineers like Margaret Hamilton aren’t seasonal, they’re fundamental to how we should approach software development every single day. Margaret coined the term “software engineering” and built the code that landed humans on the moon. Her approach to rigor is as relevant to your next Git commit as it was to Apollo 11’s descent engine.

Back to fundamentals: 7 insights from Kelsey Hightower at HAProxyConf

Early in his career, Kelsey Hightower made a bet. The load balancer his team was running was consuming too much memory, and he was convinced he knew the fix. He told his manager: “If it doesn’t work, fire me. But I think I can make it work.” The fix was HAProxy. It was a story he shared publicly for the first time at HAProxyConf 2025, where he delivered a keynote address, “The Fundamentals.”