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CIQ Introduces New Release of Fuzzball

CIQ announced the availability of federation capabilities in Fuzzball, their performance-intensive computing platform. 

This release allows engineering teams and business analysts to easily connect, manage and share compute resources for all performance-intensive workloads (HPC and AI) that need to be deployed globally, across different sites, and even across hybrid/on-premises and public cloud infrastructures.  Further, the team has also made the CIQ Fuzzball platform available on AWS, providing easier consumption and facilitating the use of elastic cloud computing resources.

Introduced last year, CIQ Fuzzball already helps individuals define, deploy and manage complex analytical jobs across these disparate compute resources, freeing them to focus on solving problems rather than spending valuable time managing infrastructure. Often, however, the virtual resources and physical infrastructure they require can also span clusters, availability zones, regions, geographies and even clouds, and this has been a challenge.

The new federation capabilities in Fuzzball address the complexities of hybrid infrastructure head-on. Now, organizations can define resource pools across zones, regions and clouds, and Fuzzball intelligently deploys jobs to an appropriate cluster based on workload requirements. Fuzzball evaluates the compute, data and storage requirements of the workflow against the resources available and then dispatches the workflow to a suitable cluster for execution. In an environment where AI is driving nearly every company to face performance-intensive computing challenges, this approach not only simplifies delivery of these jobs but also allows analysts and engineers to address the challenges of and take advantage of hybrid cloud, on-premises infrastructure.

"From the very beginning, Fuzzball was architected as a hybrid computing platform and this new capability unlocks workload execution across on-premises and cloud resources, a key milestone in the evolution of Fuzzball," said Gregory Kurtzer, founder and CEO of CIQ. "Federation allows Fuzzball to now automate the deployment of jobs based on a sophisticated analysis of architecture, resources, cost and data-centric policies so that you no longer need to manually evaluate and choose the optimal environment for each workload. This is the first of many features designed to provide unparalleled hybrid flexibility in Fuzzball."

Federation allows users to develop in the cloud and then deploy on expensive GPU or CPU resources on-premises or in the cloud in order to save costs. Conversely, some may choose to develop locally and then deploy to the cloud for scale. Either way, Fuzzball allows users to do this without modification to code or management of the underlying environment. It allows for Fuzzball to deliver optimal performance, whether prioritizing speed, cost-effectiveness or time-to-completion.

CIQ has also announced availability of Fuzzball on AWS allowing users to easily experiment with and deploy analytical and performance-intensive workloads. This allows organizations to optimize or avoid the complexities and the capital expense of traditional, high-end on-premises environments and use their AWS environment as an option. This capability lets users deploy hybrid federation capabilities in Fuzzball to enable integration of existing on-premises resources with AWS for a cost-optimized, hybrid environment. Recognizing that some workloads may be more cost-effective to run on-premises, Fuzzball on AWS provides an option for on-demand and burst processing, giving organizations flexibility and cost optimization for these workloads.

CIQ Fuzzball is available on AWS today via the CIQ website.

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CIQ Introduces New Release of Fuzzball

CIQ announced the availability of federation capabilities in Fuzzball, their performance-intensive computing platform. 

This release allows engineering teams and business analysts to easily connect, manage and share compute resources for all performance-intensive workloads (HPC and AI) that need to be deployed globally, across different sites, and even across hybrid/on-premises and public cloud infrastructures.  Further, the team has also made the CIQ Fuzzball platform available on AWS, providing easier consumption and facilitating the use of elastic cloud computing resources.

Introduced last year, CIQ Fuzzball already helps individuals define, deploy and manage complex analytical jobs across these disparate compute resources, freeing them to focus on solving problems rather than spending valuable time managing infrastructure. Often, however, the virtual resources and physical infrastructure they require can also span clusters, availability zones, regions, geographies and even clouds, and this has been a challenge.

The new federation capabilities in Fuzzball address the complexities of hybrid infrastructure head-on. Now, organizations can define resource pools across zones, regions and clouds, and Fuzzball intelligently deploys jobs to an appropriate cluster based on workload requirements. Fuzzball evaluates the compute, data and storage requirements of the workflow against the resources available and then dispatches the workflow to a suitable cluster for execution. In an environment where AI is driving nearly every company to face performance-intensive computing challenges, this approach not only simplifies delivery of these jobs but also allows analysts and engineers to address the challenges of and take advantage of hybrid cloud, on-premises infrastructure.

"From the very beginning, Fuzzball was architected as a hybrid computing platform and this new capability unlocks workload execution across on-premises and cloud resources, a key milestone in the evolution of Fuzzball," said Gregory Kurtzer, founder and CEO of CIQ. "Federation allows Fuzzball to now automate the deployment of jobs based on a sophisticated analysis of architecture, resources, cost and data-centric policies so that you no longer need to manually evaluate and choose the optimal environment for each workload. This is the first of many features designed to provide unparalleled hybrid flexibility in Fuzzball."

Federation allows users to develop in the cloud and then deploy on expensive GPU or CPU resources on-premises or in the cloud in order to save costs. Conversely, some may choose to develop locally and then deploy to the cloud for scale. Either way, Fuzzball allows users to do this without modification to code or management of the underlying environment. It allows for Fuzzball to deliver optimal performance, whether prioritizing speed, cost-effectiveness or time-to-completion.

CIQ has also announced availability of Fuzzball on AWS allowing users to easily experiment with and deploy analytical and performance-intensive workloads. This allows organizations to optimize or avoid the complexities and the capital expense of traditional, high-end on-premises environments and use their AWS environment as an option. This capability lets users deploy hybrid federation capabilities in Fuzzball to enable integration of existing on-premises resources with AWS for a cost-optimized, hybrid environment. Recognizing that some workloads may be more cost-effective to run on-premises, Fuzzball on AWS provides an option for on-demand and burst processing, giving organizations flexibility and cost optimization for these workloads.

CIQ Fuzzball is available on AWS today via the CIQ website.

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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.