N-able Technologies, a provider of remote monitoring and management (RMM) automation software for managed service providers (MSPs) and IT departments, announced the general availability of N-central 8.1, its next-generation managed services technology platform.
Now available worldwide, the new N-central 8.1 RMM automation platform offers VMware remote monitoring and delivers new Scheduled Task improvements along with automated warranty expiration monitoring. Technicians "on the go" will also appreciate the new N-central mobile app now supporting the Android mobile platform.
These features are all designed to ensure a clear line of sight into the network and drive further business success and improved productivity for MSPs, IT administrators and their customers.
Highlights of N-central's new capabilities for VMware include monitoring of the key hardware components of ESX and ESXi servers, such as power supplies, fans and RAID-related hardware, as well as in-depth profiling of the performance of an ESX/ESXi server's disk sub-system. Together, these features give N-central administrators the opportunity to quickly identify and address both hardware and performance issues before they affect those users hosted on a company's virtual infrastructure.
The new N-central 8.1 platform also introduces Android device support, which is accessible by downloading the N-central mobile app from the Android Market. The N-central mobile application, first introduced for Apple mobile devices in May, makes viewing active issues and job status pages from an Android-based mobile device fast and convenient. It also gives MSPs and IT administrators the ability to acknowledge alerts and view devices, and review the details of a particular service.
Additional scheduling options now available in N-central 8.1 deliver greater flexibility and new ways for MSPs and IT administrators to improve network performance and customer satisfaction. Scheduled Tasks can now be configured to run multiple times in one day, on the last day of each month, on an interval basis or only during specific months, with many other new and useful scheduling configurations also available.
The Latest
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...