Netuitive announced details about its upcoming major release, Netuitive 6.0, which features the industry’s first open API to a predictive analytics platform.
The innovations in this release improve usability and eliminate vendor lock-in by enabling extensible data integration and correlation capabilities required to achieve end-to-end application performance management (APM).
One of the biggest challenges for APM is how to quickly correlate and extract value from the vast and unmanageable amounts of data (e.g., business activity, customer experience, applications, and infrastructure) collected from a plethora of specialized monitoring tools.
“The APM market is confronted with a big data problem. As our customers have progressed in the deployment of more agents to monitor their real-time performance at the business, application and infrastructure levels, they have been confronted with a deluge of data that is humanly impossible to correlate and interpret with traditional monitoring tools,” said Nicola Sanna, CEO of Netuitive. “Netuitive 6.0 provides a leap in extensibility by providing the tools and analytics necessary to turn data from new data sources into actionable insight.”
Netuitive 6.0 delivers rapid extension capabilities to integrate with and correlate any third party data source, allowing power users and partners to meet their unique data analysis needs at their own pace.
Netuitive 6.0 provides meaningful visibility into the health of applications, automatically isolates problems across silos and domains, and delivers proactive notifications of impending performance issues.
Orbitz is a Netuitive customer who has tested Integration Studio. “Our company is rapidly growing our big data collections. With new types of data arriving weekly, the new Studio feature in the 6.0 release will let us adapt quicker, easier and better,” said Brian Devlin, Operations Engineer for Orbitz.
Netuitive 6.0 innovates in three key areas:
- Integration Studio for Unlimited Extensibility
- Most Complete View into Java Application Ecosystem
- Improved User Interface and New Algorithms for Optimized APM Diagnostics
Integration Studio
Netuitive has developed an SDK empowering users to:
- Integrate and correlate data streams from any monitoring source
- Edit the settings via UI-based configuration wizards
- Create best practices templates for integrations with new and custom data sources
On this new analytics platform, data is collected and normalized in Netuitive’s Performance Management Database (PMDB), analyzed by Netuitive’s Behavior Learning technology, with actionable outputs delivered based on the analysis.
Central to this capability are APIs enabling integration with configuration management databases, incident management, and programmatic administration of users security and policies.
Integration Studio complements Netuitive’s Open approach and broad portfolio of standard integrations with leading monitoring tools from more than 30 companies including leaders such as CA, BMC, HP, IBM, VMware, Microsoft, Compuware, EMC, NetApp, Oracle, and many others. These standard integrations embed best practices for a rapid implementation and immediate time to value.
Most Complete View Into Java Application Ecosystem
Netuitive has developed new models for complex, distributed Java applications. By introducing new managed elements types such as JVM and Web Application clusters, and then applying Behavior Learning technology to application performance, Netuitive 6.0 provides much greater visibility into Java applications running in large distributed environments while preserving relationships that power diagnostics.
The software also correlates application and infrastructure performance data together, facilitating performance troubleshooting across enterprise silos. This new modeling capability is available in the standard product with built-in best practices to deliver a rapid time to value.
Improved User Interface and New Algorithms Optimized for APM Diagnostics
Netuitive’s innovative APM graphical user interface provides real time, multi-tier visibility into application performance management across silos and domains. It takes a problem-oriented event-management approach, leveraging critical knowledge bases, to automate and categorize problems.
It then provides prescriptive advice making Netuitive’s composite alerting and health index more actionable and intuitive to understand. New algorithms have been developed to make Netuitive’s unique Trusted Alarms and health index more intuitive and easy to interpret at a glance.
Ultimately, the new features simplify troubleshooting workflow and the detection of anomalies that can lead to service degradation and outages. The combination is a game-changing leap forward in the way that analytics delivers value to IT operations.
“A major challenge of large-scale multi-vendor APM implementations is the analytics - whether integrated or provided by independent vendors. Feeding the analytics tools with relevant business and IT data sources is required to automatically build relationships, key performance indicators and service models,” said Jonah Kowall, Research Director for Gartner.
“Solutions that leverage behavior learning engines can help automate the correlation of these disparate data sources. When tooling is provided customers may extend the product to almost any data source, which helps the analytics solution to become engrained across an entire organization.”
Eight of the world’s 10 largest banks and several global service providers have deployed Netuitive’s self-learning predictive analytics software that sits on top of their traditional monitoring tools, providing a holistic view of performance across business, application, and infrastructure silos.
Hot Topic
The Latest
For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...
Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...
Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...
Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...
I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...
The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...
For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...
The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...
44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...
Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...