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Netuitive Joins NetApp Alliance Partner Program

Predictive Analytics Platform Provides Unified View for Optimum Application Performance Management in the Cloud

Netuitive has joined the NetApp Alliance Partner Program as a Cloud Management Partner.

Netuitive is collaborating with NetApp to provide enterprise customers with an industry-leading predictive analytics platform to help improve visibility and insight into their critical applications by automatically detecting anomalies and preventing cascading failures.

Leveraging an integration to NetApp OnCommand with Performance Advisor, Netuitive’s predictive analytics software, powered by its patented Behavior Learning EngineTM, simultaneously analyzes and correlates real-time performance data on NetApp appliances and volumes.

Enterprise Customer Benefits:

• Automate mundane performance management tasks with Behavior Learning technology

• Optimize capacity planning with trended resource utilization

• Automate service performance problem root-cause with additional monitoring data sources

• Leverage automated correlation discovery to isolate performance bottlenecks

• Receive proactive alerts before a cascading failure leads to an outage

• Enable SLAs and address performance problems before end users are impacted

• Predictive (proactive) analytics proven to scale to enterprise-class private clouds

These benefits become more evident as Netuitive’s predictive analytics are applied to additional data sources in physical, virtual, and applications infrastructure, including end-user experience and business metrics for applications – to deliver an end-to-end management capability.

Netuitive has integrations with all of the leading monitoring solutions for each of these domains including VMware, CA, IBM, HP, BMC, Microsoft, Compuware, and others. Netuitive collects data from the third-party monitoring tools and delivers its analytics results into the tools provided by the same vendors for a seamless integration and minimal impact on the systems management architecture and operational processes.

Netuitive reduces manual, rules-based approaches with advanced mathematics and predictive analytics that automatically correlates and self-learns the operational behavior of systems and applications across an entire IT environment. By taking this holistic approach, it provides a unified view across platforms and vendors, and because its learning is adaptive, it excels in dynamic, virtualized environments.

Netuitive’s predictive analytics solution has proven to scale as Netuitive’s customers include eight of the world’s 10 largest banks and several global telecommunications firms. They rely on Netuitive to predict degradations and avoid outages for their most critical applications. One leading global bank uses NetApp and Netuitive in a virtual data center deployment with over 40,000 virtual machines and 2 petabytes of NetApp storage—all while automatically collecting and analyzing millions of performance metrics in real time.

“Storage performance is directly linked to application infrastructure performance representing one of the most important and challenging aspects of enterprise IT,” says Nicola Sanna, CEO of Netuitive. “As an industry leader, NetApp serves as the foundational storage platform for some of the world’s largest enterprises. Netuitive is central to effectively monitoring storage performance while analyzing and correlating all of the components supporting the performance of critical applications and related infrastructure.”

NetApp collaborates with leading automation and analytic software vendors like Netuitive to provide seamless integration with NetApp open-management APIs. This integration provides end-to-end cloud management, including full-stack orchestration, self-service portals, metering, and reporting.

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Netuitive Joins NetApp Alliance Partner Program

Predictive Analytics Platform Provides Unified View for Optimum Application Performance Management in the Cloud

Netuitive has joined the NetApp Alliance Partner Program as a Cloud Management Partner.

Netuitive is collaborating with NetApp to provide enterprise customers with an industry-leading predictive analytics platform to help improve visibility and insight into their critical applications by automatically detecting anomalies and preventing cascading failures.

Leveraging an integration to NetApp OnCommand with Performance Advisor, Netuitive’s predictive analytics software, powered by its patented Behavior Learning EngineTM, simultaneously analyzes and correlates real-time performance data on NetApp appliances and volumes.

Enterprise Customer Benefits:

• Automate mundane performance management tasks with Behavior Learning technology

• Optimize capacity planning with trended resource utilization

• Automate service performance problem root-cause with additional monitoring data sources

• Leverage automated correlation discovery to isolate performance bottlenecks

• Receive proactive alerts before a cascading failure leads to an outage

• Enable SLAs and address performance problems before end users are impacted

• Predictive (proactive) analytics proven to scale to enterprise-class private clouds

These benefits become more evident as Netuitive’s predictive analytics are applied to additional data sources in physical, virtual, and applications infrastructure, including end-user experience and business metrics for applications – to deliver an end-to-end management capability.

Netuitive has integrations with all of the leading monitoring solutions for each of these domains including VMware, CA, IBM, HP, BMC, Microsoft, Compuware, and others. Netuitive collects data from the third-party monitoring tools and delivers its analytics results into the tools provided by the same vendors for a seamless integration and minimal impact on the systems management architecture and operational processes.

Netuitive reduces manual, rules-based approaches with advanced mathematics and predictive analytics that automatically correlates and self-learns the operational behavior of systems and applications across an entire IT environment. By taking this holistic approach, it provides a unified view across platforms and vendors, and because its learning is adaptive, it excels in dynamic, virtualized environments.

Netuitive’s predictive analytics solution has proven to scale as Netuitive’s customers include eight of the world’s 10 largest banks and several global telecommunications firms. They rely on Netuitive to predict degradations and avoid outages for their most critical applications. One leading global bank uses NetApp and Netuitive in a virtual data center deployment with over 40,000 virtual machines and 2 petabytes of NetApp storage—all while automatically collecting and analyzing millions of performance metrics in real time.

“Storage performance is directly linked to application infrastructure performance representing one of the most important and challenging aspects of enterprise IT,” says Nicola Sanna, CEO of Netuitive. “As an industry leader, NetApp serves as the foundational storage platform for some of the world’s largest enterprises. Netuitive is central to effectively monitoring storage performance while analyzing and correlating all of the components supporting the performance of critical applications and related infrastructure.”

NetApp collaborates with leading automation and analytic software vendors like Netuitive to provide seamless integration with NetApp open-management APIs. This integration provides end-to-end cloud management, including full-stack orchestration, self-service portals, metering, and reporting.

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IT organizations have historically measured success by how quickly they can respond when something goes wrong. The entire discipline of Incident Management has been optimized around mean time to resolution, first-response SLAs and ticket closure rates. But new research suggests that even though this is a well-executed playbook, it's no longer enough to retain customers ...

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...