Checkmk expanded its SaaS platform, Checkmk Cloud.
IT teams can see applications and infrastructure in context, pinpoint root causes faster, and resolve issues efficiently—without adding operational overhead. New capabilities include comprehensive SNMP coverage, application observability based on OpenTelemetry, and AI-powered alert analysis.
With Checkmk Relay, physical network devices such as NAS systems or printers can now be integrated directly into SaaS monitoring. The lightweight container collects monitoring data locally and transmits it mTLS-encrypted—without inbound traffic. Even highly segmented networks can be monitored securely, giving IT teams a complete and transparent view of their entire hybrid IT environment within a fully managed SaaS model.
Checkmk Cloud also expands visibility into the application layer. The platform captures application metrics via OpenTelemetry and Prometheus scraping, and brings it together with infrastructure metrics for cross-analysis in a single pane of glass. IT teams can immediately determine whether performance issues originate in the application or the underlying infrastructure, taking precise action to significantly reduce MTTR and minimize service impact. Custom or legacy applications, including Java or .NET workloads, can also be integrated via auto-instrumentation, without any code changes. Checkmk Cloud comes with pre-configured dashboards for RED signals—visualizing request rate, errors, and latency—so IT teams can quickly identify user-impacting problems and prioritize resolution.
Checkmk Cloud analyzes incoming alerts and translates them into clear, understandable explanations of potential root causes. IT teams receive actionable insights, reducing analysis time and enabling faster response in critical situations.
With “Explain with AI,” Checkmk Cloud analyzes incoming alerts and translates them into clear, understandable explanations of potential root causes. IT teams receive actionable insights, reducing analysis time and enabling faster response in critical situations. The function also generates readable incident summaries, improving documentation and cross-team communication.
Checkmk Cloud is ready to use within minutes, letting IT teams monitor applications, on-premises systems, containers, and multi-cloud environments without installation or maintenance. Automated discovery of new systems and pre-configured integrations reduce setup effort and simplify operations. The fully managed SaaS platform delivers 99.5 % availability and meets strict security and compliance standards, with data residency in the EU or the United States. Designed for organizations seeking enterprise-grade monitoring without the complexity of self-managed solutions, Checkmk Cloud focuses on rapid deployment, automated operations, and minimal administrative overhead.
The Latest
I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...