Zenoss announced the availability of its new OpenStack Infrastructure ZenPack.
OpenStack is quickly becoming a key component of the rapidly evolving landscape that includes intrinsic technologies for big data, cloud, containers like Docker, converged infrastructure, virtualization, and more. Zenoss has invested in simplifying the monitoring of these systems for innovative IT organizations around the globe.
“We're seeing some phenomenal growth in the OpenStack market and much demand in our market surveys: our bottoms-up forecast based on vendor and service provider revenue is projecting that the OpenStack market will be $3.3B by 2018, an annual 40% growth rate from 2013,” stated Michael Coté, Research Director, Infrastructure Software. “As OpenStack is used in more deployments, including mainstream, monitoring those installations will become critical but increasingly difficult for end-users. It's great to see innovative vendors like Zenoss adding capabilities so that they can evolve with the growth of the market.”
Innovative companies across the world use OpenStack to achieve unprecedented flexibility and agility and Zenoss ensures reliable IT Service delivery to increase productivity and reduce costs. With Zenoss these organizations can realize the full potential of their investments in modern technology.
“The unprecedented investment by industry leaders is clearly driving the rapid growth and adoption of OpenStack by our customers. We have extended our OpenStack support beyond the current tenant view to now provide operators of OpenStack-based clouds with insight into the performance and availability of the underlying physical and virtual infrastructure,” said Alan Conley, CTO and SVP Engineering at Zenoss. “The combination of OpenStack, application, and infrastructure performance in one unified platform provides unequaled visibility into overall service health.”
Zenoss now has the ability to manage OpenStack from a cloud user perspective as well as a cloud provider perspective through its new OpenStack Infrastructure ZenPack.
Key capabilities in the new OpenStack Infrastructure ZenPack include:
- Automatic discovery and modelling of OpenStack cloud components, including physical hosts, the software components or hypervisors running on the hosts, and relationships between physical hosts and OpenStack components.
- Collection of provider-oriented metrics, such as CPU utilization, disk read/write request and byte rates, and network utilization (incoming/outgoing packet and byte rates) for OpenStack hosts and instances.
- Support for building cloud service impact models, including for the underlying cloud infrastructure such as Cisco UCS converged infrastructure, networking components from Cisco, Brocade, and Juniper, and server hardware from industry-standard hardware vendors such as Dell, HP, and IBM. If a hardware issue occurs on a physical host, this information is propagated into Service Impact so providers can quickly see what infrastructure/services are impacted.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...