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Zenoss Achieves Cisco Compatibility Certification

The Zenoss Service Assurance Version 5.0 has successfully achieved Cisco compatibility certification with Cisco Application Policy Infrastructure Controller (Cisco APIC) Version 1.0.

The Cisco APIC is the unifying point of automation and management for the Application Centric Infrastructure (ACI) fabric, providing centralized access to all fabric information, optimizing the application lifecycle for scale and performance, and supporting flexible application provisioning across physical and virtual resources. As a member of the Cisco Solution Partner Program, Zenoss is able to quickly create and deploy solutions to enhance the capabilities, performance and management of the network to capture value for customers deploying ACI.

Zenoss for Cisco ACI software delivers application-centric IT operations monitoring for the software-defined data center. Cisco ACI defines tenant and application needs, and Zenoss software delivers service impact and root-cause analysis unified across the network, computing, virtualization, and storage resources in the infrastructure.

Zenoss for Cisco ACI uses the business definitions of tenants, applications, endpoint groups, and contracts to build an end-to-end live model of your data center. The Zenoss live model identifies the specific infrastructure components used by each application and correlates the network health, key performance indicators (KPIs), faults, and events for each ACI tenant and application to identify the root cause of performance and availability problems.

Zenoss for Cisco ACI offers these primary benefits:

- Operations Agility. The Cisco Application Policy Infrastructure Controller (APIC) simplifies automation with an application-based policy model, while Zenoss software keeps IT operations synchronized with centralized visibility.

- Reduced Time-to-Repair. Automated network provisioning from Cisco reduces overhead and errors, and quantitative root-cause analytics from Zenoss reduces the mean time to repair problems.

- Increased Effifiency. Zenoss policy-based monitoring and analysis is simpler to define and maintain when promoted by consistent application policies based on Cisco ACI.

- Application Visibility. Zenoss extends the application policy model of ACI to include computing, storage, and virtualization to provide an end-to-end view of application infrastructure.

The Cisco Solution Partner Program, part of the Cisco Partner Ecosystem, unites Cisco with third-party independent hardware and software vendors to deliver integrated solutions to joint customers. As a Solution Partner, Zenoss, Inc. offers a complementary product offering and has started to collaborate with Cisco to meet the needs of joint customers.

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

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In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Zenoss Achieves Cisco Compatibility Certification

The Zenoss Service Assurance Version 5.0 has successfully achieved Cisco compatibility certification with Cisco Application Policy Infrastructure Controller (Cisco APIC) Version 1.0.

The Cisco APIC is the unifying point of automation and management for the Application Centric Infrastructure (ACI) fabric, providing centralized access to all fabric information, optimizing the application lifecycle for scale and performance, and supporting flexible application provisioning across physical and virtual resources. As a member of the Cisco Solution Partner Program, Zenoss is able to quickly create and deploy solutions to enhance the capabilities, performance and management of the network to capture value for customers deploying ACI.

Zenoss for Cisco ACI software delivers application-centric IT operations monitoring for the software-defined data center. Cisco ACI defines tenant and application needs, and Zenoss software delivers service impact and root-cause analysis unified across the network, computing, virtualization, and storage resources in the infrastructure.

Zenoss for Cisco ACI uses the business definitions of tenants, applications, endpoint groups, and contracts to build an end-to-end live model of your data center. The Zenoss live model identifies the specific infrastructure components used by each application and correlates the network health, key performance indicators (KPIs), faults, and events for each ACI tenant and application to identify the root cause of performance and availability problems.

Zenoss for Cisco ACI offers these primary benefits:

- Operations Agility. The Cisco Application Policy Infrastructure Controller (APIC) simplifies automation with an application-based policy model, while Zenoss software keeps IT operations synchronized with centralized visibility.

- Reduced Time-to-Repair. Automated network provisioning from Cisco reduces overhead and errors, and quantitative root-cause analytics from Zenoss reduces the mean time to repair problems.

- Increased Effifiency. Zenoss policy-based monitoring and analysis is simpler to define and maintain when promoted by consistent application policies based on Cisco ACI.

- Application Visibility. Zenoss extends the application policy model of ACI to include computing, storage, and virtualization to provide an end-to-end view of application infrastructure.

The Cisco Solution Partner Program, part of the Cisco Partner Ecosystem, unites Cisco with third-party independent hardware and software vendors to deliver integrated solutions to joint customers. As a Solution Partner, Zenoss, Inc. offers a complementary product offering and has started to collaborate with Cisco to meet the needs of joint customers.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.