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Zenoss Releases Zenoss Service Dynamics

Impact Management for Hybrid Cloud Operations

Zenoss has announced the availability of Zenoss Service Dynamics. The new offering includes a service impact management solution that both unifies and automates impact and root cause analysis for IT services that span private and public IT infrastructures.

With Zenoss Service Dynamics, service providers and enterprises can now maintain visibility into the health of their hybrid IT services from a single console that is easy-to- configure and automatically updated in real-time as workloads migrate and relationships change. Zenoss’ offering natively understands virtualization and cloud services, and automatically adapts to changes in the underlying infrastructure that impact service delivery.

“In the wake of recent cloud outages and with enterprises hesitating to virtualize mission-critical applications, service assurance has become a key concern for cloud operations,” says Bill Karpovich, CEO of Zenoss. “Applying our model-driven approach to service impact and root cause analysis, we are giving IT operators what they need to move forward with confidence in the cloud – an automated solution for quickly pinpointing and responding to service health issues in real-time across the hybrid cloud datacenter.”

With the addition of service impact management, Zenoss continues to deliver on its vision for end-to-end service assurance for next generation data centers. With this release, service impact management, resource management and analytics will be offered as a single product under the brand name Zenoss Service Dynamics, the company’s commercial IT service assurance solution.

Key Features of Zenoss Service Dynamics include:

* Dynamic Impact Analysis – Maintain operational awareness of service health with next generation service impact analysis that leverages patent-pending “policy-gate” technology along with a real-time service model.

* Automated Root Cause Analysis – Quickly and automatically identify root cause of performance and availability issues with next generation root cause analysis that reduces event storms to a prioritized list of most likely incidents leveraging patent-pending confidence ranking algorithm.

* Highly Scalable Event Management – Aggregate and manage events for your entire IT stack across your virtual, physical, and cloud deployments with an event management system that provides event normalization and enrichment, and is easily extended and scaled through an embedded enterprise message bus.

* Historical & Predictive Analytics (formerly Zenoss Datacenter Insight) – Gain access to a turnkey operations data warehouse, out-of-the-box reports and advanced ad-hoc analysis capabilities that provide tenant-based reporting, historical trending, correlation and capacity forecasting.

* Unified Resource Monitoring (formerly Zenoss Enterprise) - Unify performance, availability, fault and event monitoring of networks, servers, storage and applications across your entire IT environment with a single, horizontally- scalable collection platform that is also agentless, template-driven, easy to customize and driven by auto-discovery.

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Zenoss Releases Zenoss Service Dynamics

Impact Management for Hybrid Cloud Operations

Zenoss has announced the availability of Zenoss Service Dynamics. The new offering includes a service impact management solution that both unifies and automates impact and root cause analysis for IT services that span private and public IT infrastructures.

With Zenoss Service Dynamics, service providers and enterprises can now maintain visibility into the health of their hybrid IT services from a single console that is easy-to- configure and automatically updated in real-time as workloads migrate and relationships change. Zenoss’ offering natively understands virtualization and cloud services, and automatically adapts to changes in the underlying infrastructure that impact service delivery.

“In the wake of recent cloud outages and with enterprises hesitating to virtualize mission-critical applications, service assurance has become a key concern for cloud operations,” says Bill Karpovich, CEO of Zenoss. “Applying our model-driven approach to service impact and root cause analysis, we are giving IT operators what they need to move forward with confidence in the cloud – an automated solution for quickly pinpointing and responding to service health issues in real-time across the hybrid cloud datacenter.”

With the addition of service impact management, Zenoss continues to deliver on its vision for end-to-end service assurance for next generation data centers. With this release, service impact management, resource management and analytics will be offered as a single product under the brand name Zenoss Service Dynamics, the company’s commercial IT service assurance solution.

Key Features of Zenoss Service Dynamics include:

* Dynamic Impact Analysis – Maintain operational awareness of service health with next generation service impact analysis that leverages patent-pending “policy-gate” technology along with a real-time service model.

* Automated Root Cause Analysis – Quickly and automatically identify root cause of performance and availability issues with next generation root cause analysis that reduces event storms to a prioritized list of most likely incidents leveraging patent-pending confidence ranking algorithm.

* Highly Scalable Event Management – Aggregate and manage events for your entire IT stack across your virtual, physical, and cloud deployments with an event management system that provides event normalization and enrichment, and is easily extended and scaled through an embedded enterprise message bus.

* Historical & Predictive Analytics (formerly Zenoss Datacenter Insight) – Gain access to a turnkey operations data warehouse, out-of-the-box reports and advanced ad-hoc analysis capabilities that provide tenant-based reporting, historical trending, correlation and capacity forecasting.

* Unified Resource Monitoring (formerly Zenoss Enterprise) - Unify performance, availability, fault and event monitoring of networks, servers, storage and applications across your entire IT environment with a single, horizontally- scalable collection platform that is also agentless, template-driven, easy to customize and driven by auto-discovery.

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 ...