Netuitive announced Cloud Collector to provide IT Operations Analytics (ITOA) capable of rapid deployment to cloud infrastructure.
This new product capability enables:
- Secure data transmission from on-premise application and monitoring infrastructure to cloud-hosted instances of Netuitive analytics.
- Rapid deployment of Netuitive in Pilot or Production instances, taking advantage of ease of deployment, cost effectiveness, and elasticity gained from cloud infrastructure.
The Cloud Collector feature will be available in Remote Collector 3.1, Netuitive’s module for managing data collection across disparate monitoring data sources.
Netuitive’s patented software, powered by Behavior Learning technology, replaces human guess work with real-time, predictive analytics to help enterprises visualize, isolate and proactively address application performance issues before they impact the business.
“Netuitive is focused on expanding our capabilities for enterprise adoption of IT operations analytics,” said Nicola Sanna, CEO of Netuitive. “Some enterprises prefer the flexibility and ease of deploying Netuitive to cloud infrastructure that is separate from their application infrastructure. Cloud Collector offers them a way to do that securely. And for our customers, this speeds up implementation and makes it easier for us to support customers during Pilot projects.”
Netuitive’s IT analytics fall squarely into Gartner’s categorization of IT Operations Analytics (ITOA): “IT operations analytics tools enable CIOs and senior IT operations managers to monitor their business operational data and metrics. The tools are similar to a business intelligence platform that business unit managers use to drive business performance. IT operations analytics tools enable users to assess efficiency, optimize IT investments, correlate trends, and understand and maximize IT opportunities that support the business.” (IT Market Clock for IT Operations Management, 2012 published on August 15, 2012)
Related Links:
The Latest
For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...
FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...
Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...
While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...
A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...
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 ...