
Paessler and Rittal are combining their Paessler PRTG and Rittal CMC III monitoring solutions in the context of the Paessler Uptime Alliance programme.
This means that users will be able to see what is going on with their IT and OT simultaneously with one powerful tool, and in the way they need it for their work: on a central dashboard for IT and data center OT, in individually configurable dashboards or, for example, as a service-based management overview.
“Paessler and Rittal, two companies that have established widely used standards are combining their solutions,” says Uwe Scharf, Managing Director Business Units and Marketing at Rittal: “Many IT administrators value PRTG as their standard daily IT tool, while their data center OT is built with Rittal OT solutions and monitoring. This has rapidly led to a large user base.”
Moreover, Helmut Binder, CEO of Paessler AG adds: “Rittal is a good fit for Paessler and not just because of its OT’s reliability. By combining Paessler PRTG with Rittal consulting and components, customers gain a detailed overview of their data center energy consumption, allowing them to improve the entire system in terms of energy usage.”
With RiMatrix, Rittal has developed a flexible modular system for the fast and secure build-up of IT infrastructure. It includes all supporting pillars such as rack, power, cooling, security and OT monitoring. The CMC III solution monitors all relevant physical environmental parameters, from humidity to vandalism. With RiZone, Rittal simplifies the integration of OT devices into a data center infrastructure management system. Thus, the solution serves to optimize the utilization and availability of a data center as well.
PRTG from Paessler offers ease of use, a practical range of functions, numerous interfaces and an ecosystem of partner solutions, all of which interact with PRTG to provide overarching and comprehensive solutions for a precise overview of the IT.
Paessler and Rittal have optimised the open interfaces. With just a few clicks, PRTG users can activate the function. CMC III infrastructure can be included in the central monitoring with the help of the predefined SNMP Rittal CMC III hardware status sensor in PRTG and the automatic network detection. Using the generic sensors in PRTG, the measurements from the sensors – and thus the entire data center environment – can be integrated into PRTG via several different protocols. Besides SNMP, ModbusTCP or OPC UA can also be used for this purpose.
The building floor plans or server enclosures can be mapped graphically and the devices and the associated measured values can be clearly displayed. In addition, QR codes generated in PRTG simplify the assignment of the measured values on site: The technician simply scans the QR code on the device and then sees the associated values, including their history, on their laptop or smartphone.
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.