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Zenoss Launches Advanced Anomaly Detection

Zenoss announced a major update to existing anomaly detection capabilities for preventing outages in modern IT environments.

The enhancements have enabled Zenoss Cloud to yield an 18% improvement in precision making predictions about anomalous events that are precursors to IT service disruptions.

The anomaly detection enhancements have adapted a modern neural network algorithm from Google Cloud and operationalized it for IT environments. The platform also leverages Vertex AI, a managed machine learning (ML) platform from Google Cloud that accelerates the deployment and maintenance of AI models. Vertex AI requires nearly 80% fewer lines of code to train a model versus competitive platforms, enabling data scientists and ML engineers to efficiently build and manage ML projects throughout the entire development life cycle.

The Zenoss Cloud AIOps platform helps to eliminate the need for customer organizations to employ teams of data scientists, who currently grapple with the challenge of manually piecing together homegrown ML point solutions — creating a lag time in model development and experimentation, resulting in very few models making it into production.

The advanced anomaly detection capabilities deliver:

- Predictive precision improvement of 18%

- An actions framework that notifies downstream systems of anomalous events

- Intelligent, real-time dashboard views that surface top entities exhibiting anomalous behavior based on related metrics that are monitored by machine learning algorithms

- Out-of-box and configurable policies

- At-a-glance view of anomalous entities, root-cause analysis and dependencies

“This is another big step in achieving the goal of a lights-out data center, where the infrastructure is self-healing and doesn’t require humans to manage it,” said Ani Gujrathi, CTO at Zenoss. “This launch continues to advance our AI/ML capabilities and leadership in AIOps with leading-edge technologies to reduce the risks involved with organizations modernizing their environments and moving at the speed of business.”

Zenoss Cloud is an AI-driven full-stack monitoring platform that collects all machine data, uniquely enabling the emergence of context for preventing service disruptions in complex, modern IT environments. Zenoss Cloud leverages some of the most powerful machine learning capabilities and real-time analytics of streaming data to deliver AIOps, giving companies the ability to scale and adapt to the changing needs of their businesses.

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Zenoss Launches Advanced Anomaly Detection

Zenoss announced a major update to existing anomaly detection capabilities for preventing outages in modern IT environments.

The enhancements have enabled Zenoss Cloud to yield an 18% improvement in precision making predictions about anomalous events that are precursors to IT service disruptions.

The anomaly detection enhancements have adapted a modern neural network algorithm from Google Cloud and operationalized it for IT environments. The platform also leverages Vertex AI, a managed machine learning (ML) platform from Google Cloud that accelerates the deployment and maintenance of AI models. Vertex AI requires nearly 80% fewer lines of code to train a model versus competitive platforms, enabling data scientists and ML engineers to efficiently build and manage ML projects throughout the entire development life cycle.

The Zenoss Cloud AIOps platform helps to eliminate the need for customer organizations to employ teams of data scientists, who currently grapple with the challenge of manually piecing together homegrown ML point solutions — creating a lag time in model development and experimentation, resulting in very few models making it into production.

The advanced anomaly detection capabilities deliver:

- Predictive precision improvement of 18%

- An actions framework that notifies downstream systems of anomalous events

- Intelligent, real-time dashboard views that surface top entities exhibiting anomalous behavior based on related metrics that are monitored by machine learning algorithms

- Out-of-box and configurable policies

- At-a-glance view of anomalous entities, root-cause analysis and dependencies

“This is another big step in achieving the goal of a lights-out data center, where the infrastructure is self-healing and doesn’t require humans to manage it,” said Ani Gujrathi, CTO at Zenoss. “This launch continues to advance our AI/ML capabilities and leadership in AIOps with leading-edge technologies to reduce the risks involved with organizations modernizing their environments and moving at the speed of business.”

Zenoss Cloud is an AI-driven full-stack monitoring platform that collects all machine data, uniquely enabling the emergence of context for preventing service disruptions in complex, modern IT environments. Zenoss Cloud leverages some of the most powerful machine learning capabilities and real-time analytics of streaming data to deliver AIOps, giving companies the ability to scale and adapt to the changing needs of their businesses.

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My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026 ...

Industry experts offer predictions on how Cloud will evolve and impact business in 2026. Part 3 covers Multi, Hybrid and Private Cloud ...

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