The Challenge of Managing Converged Infrastructure

Kent Erickson
Learn more about Zenoss

While the use of converged infrastructure (CI) is becoming mainstream, the accompanying management tools are still a challenge, according to the third annual global State of Converged Infrastructure survey from Zenoss.

CI systems integrate servers, storage, network and virtualization components into one system that can be managed as a single unit rather than separate systems. With 84% of all respondents using or planning to deploy CI, the technology has reached mainstream status. Companies large and small are building data centers around these integrated systems because they reduce investment risk and offer a faster way to scale out IT infrastructure capacity.

"While converged infrastructure architectures are delivering real value as the foundational element behind the transformation already underway in enterprise data centers, these packaged offerings are lacking unified monitoring and analytics software," said Megan Lueders, VP of Marketing at Zenoss. "With more effective management tools available, there is a huge opportunity for IT organizations shops to dramatically increase their agility and IT effectiveness."

The 2015 CI survey provides many additional insights into data center modernization, including:

■ In companies with more than 5,000 employees, only 8% are not using or considering CI.

■ Despite being pervasively adopted, the survey results indicate management software is lagging behind, with 63% of respondents indicating they manage their CI deployments by repurposing existing management tools designed for traditional infrastructure.

■ Astonishingly, 25% of companies who have deployed CI are dealing with seven or more tools to manage it.

■ Key drivers for CI deployments include projects for big data, infrastructure as a service, unified communications, and custom application development.

Zenoss polled 410 IT professionals from across the world to determine how technology leaders are leveraging CI to respond to business needs, including 151 who have already adopted CI within their IT environments and another 194 who were currently considering or planning for it. 32% of these respondents come from organizations with more than 5,000 employees.

Kent Erickson is Alliance Strategist at Zenoss.

Related Links

Hot Topics

Related Vendors

The Latest

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

How Intelligent Orchestration Enables Enterprises to Move from AI POC to AI Production

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Reliability Is the New Bottleneck of Innovation

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

5 Takeaways from the Observability Forecast for Retail and eCommerce

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Maximizing Impact Amid Constraints: The Role of Automation and Orchestration in Federal IT Modernization

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

The SRE Report 2026: Reliability Is Being Redefined

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

The Hidden Data Engineering Work Required to Make Enterprise AI Viable

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

The Challenge of Managing Converged Infrastructure

Kent Erickson
Learn more about Zenoss

While the use of converged infrastructure (CI) is becoming mainstream, the accompanying management tools are still a challenge, according to the third annual global State of Converged Infrastructure survey from Zenoss.

CI systems integrate servers, storage, network and virtualization components into one system that can be managed as a single unit rather than separate systems. With 84% of all respondents using or planning to deploy CI, the technology has reached mainstream status. Companies large and small are building data centers around these integrated systems because they reduce investment risk and offer a faster way to scale out IT infrastructure capacity.

"While converged infrastructure architectures are delivering real value as the foundational element behind the transformation already underway in enterprise data centers, these packaged offerings are lacking unified monitoring and analytics software," said Megan Lueders, VP of Marketing at Zenoss. "With more effective management tools available, there is a huge opportunity for IT organizations shops to dramatically increase their agility and IT effectiveness."

The 2015 CI survey provides many additional insights into data center modernization, including:

■ In companies with more than 5,000 employees, only 8% are not using or considering CI.

■ Despite being pervasively adopted, the survey results indicate management software is lagging behind, with 63% of respondents indicating they manage their CI deployments by repurposing existing management tools designed for traditional infrastructure.

■ Astonishingly, 25% of companies who have deployed CI are dealing with seven or more tools to manage it.

■ Key drivers for CI deployments include projects for big data, infrastructure as a service, unified communications, and custom application development.

Zenoss polled 410 IT professionals from across the world to determine how technology leaders are leveraging CI to respond to business needs, including 151 who have already adopted CI within their IT environments and another 194 who were currently considering or planning for it. 32% of these respondents come from organizations with more than 5,000 employees.

Kent Erickson is Alliance Strategist at Zenoss.

Related Links

Hot Topics

Related Vendors

The Latest

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

How Intelligent Orchestration Enables Enterprises to Move from AI POC to AI Production

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Reliability Is the New Bottleneck of Innovation

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

5 Takeaways from the Observability Forecast for Retail and eCommerce

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Maximizing Impact Amid Constraints: The Role of Automation and Orchestration in Federal IT Modernization

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

The SRE Report 2026: Reliability Is Being Redefined

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

The Hidden Data Engineering Work Required to Make Enterprise AI Viable

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...