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Flexential Introduces New Professional Services for Hybrid IT Environments

Flexential has launched two professional services designed to help enterprises reduce and optimize public cloud spending and strengthen security across their hybrid IT environments.

The FinOps for Public Cloud service draws on Flexential's extensive DevOps experience and deep understanding of cloud architectures to help organizations reduce cloud spending by analyzing, proposing, and implementing cost reductions and cost management controls. In addition, the Security and Optimization Program, available to customers moving into Flexential colocation and cloud environments, enhances cyber resiliency by uncovering security gaps, mitigating migration risks, and streamlining resource allocation.

"Companies are grappling with rising cloud costs and cybersecurity risks while struggling to maintain the technical expertise needed to address these challenges," said Brian Gero, SVP, Core and Strategic Engineering at Flexential. "Our services deliver immediate value by giving businesses the expertise to slash unnecessary spending and fortify security without stretching their internal resources. By collaborating directly with our Flexential experienced professionals, your technical teams will be in position to implement impactful, lasting solutions to these challenges."

The FinOps for Public Cloud service enables companies to control public cloud spending through a systematic approach to cost management. Organizations work directly with Flexential's cloud engineers to understand public cloud costs, analyze spending patterns, and implement targeted controls. Flexential then creates cross-functional alignment for cost governance to provide clear visibility into cloud expenses and enable accurate forecasting across the hybrid IT infrastructure.

The Security and Optimization Program strengthens an organization's security posture and cyber resiliency. Flexential's proven track record in security and infrastructure, and unique field-tested processes provide low-risk, low-downtime migrations. The service provides customer teams with a detailed analysis of cybersecurity gaps and resource allocations, with specific recommendations for security improvements, ransomware defenses, compute optimization, workload resources, and future modernizations.

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.

Flexential Introduces New Professional Services for Hybrid IT Environments

Flexential has launched two professional services designed to help enterprises reduce and optimize public cloud spending and strengthen security across their hybrid IT environments.

The FinOps for Public Cloud service draws on Flexential's extensive DevOps experience and deep understanding of cloud architectures to help organizations reduce cloud spending by analyzing, proposing, and implementing cost reductions and cost management controls. In addition, the Security and Optimization Program, available to customers moving into Flexential colocation and cloud environments, enhances cyber resiliency by uncovering security gaps, mitigating migration risks, and streamlining resource allocation.

"Companies are grappling with rising cloud costs and cybersecurity risks while struggling to maintain the technical expertise needed to address these challenges," said Brian Gero, SVP, Core and Strategic Engineering at Flexential. "Our services deliver immediate value by giving businesses the expertise to slash unnecessary spending and fortify security without stretching their internal resources. By collaborating directly with our Flexential experienced professionals, your technical teams will be in position to implement impactful, lasting solutions to these challenges."

The FinOps for Public Cloud service enables companies to control public cloud spending through a systematic approach to cost management. Organizations work directly with Flexential's cloud engineers to understand public cloud costs, analyze spending patterns, and implement targeted controls. Flexential then creates cross-functional alignment for cost governance to provide clear visibility into cloud expenses and enable accurate forecasting across the hybrid IT infrastructure.

The Security and Optimization Program strengthens an organization's security posture and cyber resiliency. Flexential's proven track record in security and infrastructure, and unique field-tested processes provide low-risk, low-downtime migrations. The service provides customer teams with a detailed analysis of cybersecurity gaps and resource allocations, with specific recommendations for security improvements, ransomware defenses, compute optimization, workload resources, and future modernizations.

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.