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5 Questions to Ask Yourself About Composable Infrastructure

Perry Szarka

Is composable infrastructure the right choice for your IT environment? The following are 5 key questions that can help you begin to explore the capabilities of composable infrastructure and its applicability within your own IT environment.

Start with The Business Case for Composable Infrastructure

1. Is IT holding your business back?

To compete successfully in today's fast-paced business environment requires agile compute solutions designed with speed and accuracy in mind. If you find that your legacy IT solutions are holding you back from becoming a digitally enabled competitor, yet you still need those legacy apps from time to time, a composable infrastructure may provide the best of both worlds.

2. Are you fighting a battle with stranded assets?

One of the most common problems CIOs face is over- or under-buying of infrastructure to support the business' fluctuating demands. Most err on the side of caution and over-buy, which leaves them with too many stranded assets on the balance sheet – and an uncomfortable meeting with the CFO when explanations are required. Because a composable infrastructure creates a pool of resources that are automatically configured as the business' compute needs change, there is no need for over-provisioning, something which puts CIOs and CFOs on the same side of the table.

3. Do you develop your own applications in house?

To avoid over- or under-provisioning during the DevOps process, organizations that are developing their own business-building apps in house are often asked to use hand-me-down legacy infrastructures for development and quality assurance, then switch to another more agile environment for production where resources can be carefully allocated and monitored by IT staff; the use of two environments, however, often slows the entire process. Optimally, to make the most of advanced DevOps tools, internal developers need the ability to control and rapidly model their own application environment without having to hit the "pause" button and rely on IT to allocate resources for them. Because a composable infrastructure's resources are pooled, they can be both shared as services and allocated without IT intervention, which makes a composable infrastructure uniquely positioned to meet the DevOps needs of internal application development teams.

4. Are you making the best use of your IT talent?

Nearly everyone in IT today has at least talked about the 80/20 principle – the fact that nearly 80 percent of IT pros' time is spent on mundane "lights on" activities and only 20 percent on more valuable business-building projects. While the goal has long been to flip those percentages upside down, this has proven to be easier said than done. The kind of automation and orchestration built into composable infrastructure solutions, however, may finally make this possible, allowing your most talented IT professionals to refocus their efforts on more strategic and creative activities.

5. Is your current infrastructure future ready?

As copper wire nears its maximum capacity, a light is being shined on the science of photonics, technology slated to be the replacement for copper wire in the not-too-distant future. Instead of transporting gigabits of information, with photonics, computing systems will need to be ready to handle terabits of data, something a composable infrastructure is already equipped to do. So, while there's no such thing as a future-proof environment, there is such thing as one that can be future ready, and a composable infrastructure may be the first step in that direction.

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 ...

5 Questions to Ask Yourself About Composable Infrastructure

Perry Szarka

Is composable infrastructure the right choice for your IT environment? The following are 5 key questions that can help you begin to explore the capabilities of composable infrastructure and its applicability within your own IT environment.

Start with The Business Case for Composable Infrastructure

1. Is IT holding your business back?

To compete successfully in today's fast-paced business environment requires agile compute solutions designed with speed and accuracy in mind. If you find that your legacy IT solutions are holding you back from becoming a digitally enabled competitor, yet you still need those legacy apps from time to time, a composable infrastructure may provide the best of both worlds.

2. Are you fighting a battle with stranded assets?

One of the most common problems CIOs face is over- or under-buying of infrastructure to support the business' fluctuating demands. Most err on the side of caution and over-buy, which leaves them with too many stranded assets on the balance sheet – and an uncomfortable meeting with the CFO when explanations are required. Because a composable infrastructure creates a pool of resources that are automatically configured as the business' compute needs change, there is no need for over-provisioning, something which puts CIOs and CFOs on the same side of the table.

3. Do you develop your own applications in house?

To avoid over- or under-provisioning during the DevOps process, organizations that are developing their own business-building apps in house are often asked to use hand-me-down legacy infrastructures for development and quality assurance, then switch to another more agile environment for production where resources can be carefully allocated and monitored by IT staff; the use of two environments, however, often slows the entire process. Optimally, to make the most of advanced DevOps tools, internal developers need the ability to control and rapidly model their own application environment without having to hit the "pause" button and rely on IT to allocate resources for them. Because a composable infrastructure's resources are pooled, they can be both shared as services and allocated without IT intervention, which makes a composable infrastructure uniquely positioned to meet the DevOps needs of internal application development teams.

4. Are you making the best use of your IT talent?

Nearly everyone in IT today has at least talked about the 80/20 principle – the fact that nearly 80 percent of IT pros' time is spent on mundane "lights on" activities and only 20 percent on more valuable business-building projects. While the goal has long been to flip those percentages upside down, this has proven to be easier said than done. The kind of automation and orchestration built into composable infrastructure solutions, however, may finally make this possible, allowing your most talented IT professionals to refocus their efforts on more strategic and creative activities.

5. Is your current infrastructure future ready?

As copper wire nears its maximum capacity, a light is being shined on the science of photonics, technology slated to be the replacement for copper wire in the not-too-distant future. Instead of transporting gigabits of information, with photonics, computing systems will need to be ready to handle terabits of data, something a composable infrastructure is already equipped to do. So, while there's no such thing as a future-proof environment, there is such thing as one that can be future ready, and a composable infrastructure may be the first step in that direction.

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 ...