Skip to main content

Condusiv Releases DymaxIO

V-locity, Diskeeper, and SSDkeeper are now DymaxIO

Condusiv Technologies announced the release of new DymaxIO, a cost-effective, easy, and indispensable solution for fast data, increased throughput, and accelerated I/O performance so systems and applications run at peak performance for as long as possible.

“I developed Diskeeper 34 years ago because SysAdmins were spending their weekends doing ‘backup-and-restore’ to fix performance problems due to fragmentation,” said Craig Jensen, Condusiv CEO. “We have come a long way since then. We have the best engineers on the planet who have consistently evolved and improved our software from automatic defrag on spinning disks to fragmentation prevention, to multiple, patented technologies to optimize performance in virtual environments, on all-flash, and in the cloud. New DymaxIO automatically detects the type of hardware on which it is installed and deploys the appropriate performance enhancement technologies for that exact individual system so organizations can boost performance without overspending on hardware.”

There are 2 severe I/O inefficiencies that cause performance and reliability problems. First is that the Windows file system tends to break up writes into separate storage I/Os which causes I/O characteristics that are much smaller, more fractured, and more random than they need to be. Second is storage IO contention, also known as the I/O Blender Effect, which happens when you have multiple systems all sharing the same storage resource. Performance is penalized twice by these storage I/O inefficiencies, causing systems to process workloads about 50% slower than they should.

DymaxIO dynamically accelerates data for maximum I/O performance. By solving I/O inefficiencies at the source, DymaxIO improves application performance, increases throughput 30-40%, reduces latency, increases VDI capacity, reduces timeouts and crashes, shortens backups, improves data transfer rates and extends hardware lifecycles.

“By making sure that DymaxIO will adapt to your specific workload and having studied what kinds of I/Os amplify the I/O Blender Effect, we were able to add intelligence to specifically go after those I/Os,” said Rick Cadruvi, Condusiv Chief Architect. “We take a global view. We aren’t limited to a specific application or workload. While we do have technologies that shine under certain workloads, such as transactional SQL applications, our goal is to optimize the entire network of systems. That’s the only way to overcome the I/O Blender Effect.”

Key DymaxIO Features

- New AI Intelligent Detection and Adaption: Diskeeper, SSDkeeper, and V-locity have been combined into a single product that intelligently detects and adapts to its operating environment using artificial intelligence.

- New Condusiv Management Console: the new management console will manage all Condusiv software.

- IntelliWrite® patented write optimization technology: automatically prevents excessively small, fractured, random writes and reads that harms performance due to the severe inefficiency in the native hand-off of data between the Windows OS and underlying storage.

- IntelliMemory® patented read I/O optimization technology: intelligently caches hot read requests from server memory that is otherwise idle and unused.

- InvisiTasking® patented intelligent scheduling technology: allows all the DymaxIO “background” operations within the server to run with zero resource impact on current production by only leveraging idle CPU cycles and memory.

- Benefits Dashboard: The “time saved” dashboard demonstrates the value by showing the amount of I/O traffic offloaded from storage, the percentage of read and write I/O traffic offloaded, and the resulting time saved to any one system or group of systems.

New DymaxIO is available as an annual subscription SaaS model.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...

Condusiv Releases DymaxIO

V-locity, Diskeeper, and SSDkeeper are now DymaxIO

Condusiv Technologies announced the release of new DymaxIO, a cost-effective, easy, and indispensable solution for fast data, increased throughput, and accelerated I/O performance so systems and applications run at peak performance for as long as possible.

“I developed Diskeeper 34 years ago because SysAdmins were spending their weekends doing ‘backup-and-restore’ to fix performance problems due to fragmentation,” said Craig Jensen, Condusiv CEO. “We have come a long way since then. We have the best engineers on the planet who have consistently evolved and improved our software from automatic defrag on spinning disks to fragmentation prevention, to multiple, patented technologies to optimize performance in virtual environments, on all-flash, and in the cloud. New DymaxIO automatically detects the type of hardware on which it is installed and deploys the appropriate performance enhancement technologies for that exact individual system so organizations can boost performance without overspending on hardware.”

There are 2 severe I/O inefficiencies that cause performance and reliability problems. First is that the Windows file system tends to break up writes into separate storage I/Os which causes I/O characteristics that are much smaller, more fractured, and more random than they need to be. Second is storage IO contention, also known as the I/O Blender Effect, which happens when you have multiple systems all sharing the same storage resource. Performance is penalized twice by these storage I/O inefficiencies, causing systems to process workloads about 50% slower than they should.

DymaxIO dynamically accelerates data for maximum I/O performance. By solving I/O inefficiencies at the source, DymaxIO improves application performance, increases throughput 30-40%, reduces latency, increases VDI capacity, reduces timeouts and crashes, shortens backups, improves data transfer rates and extends hardware lifecycles.

“By making sure that DymaxIO will adapt to your specific workload and having studied what kinds of I/Os amplify the I/O Blender Effect, we were able to add intelligence to specifically go after those I/Os,” said Rick Cadruvi, Condusiv Chief Architect. “We take a global view. We aren’t limited to a specific application or workload. While we do have technologies that shine under certain workloads, such as transactional SQL applications, our goal is to optimize the entire network of systems. That’s the only way to overcome the I/O Blender Effect.”

Key DymaxIO Features

- New AI Intelligent Detection and Adaption: Diskeeper, SSDkeeper, and V-locity have been combined into a single product that intelligently detects and adapts to its operating environment using artificial intelligence.

- New Condusiv Management Console: the new management console will manage all Condusiv software.

- IntelliWrite® patented write optimization technology: automatically prevents excessively small, fractured, random writes and reads that harms performance due to the severe inefficiency in the native hand-off of data between the Windows OS and underlying storage.

- IntelliMemory® patented read I/O optimization technology: intelligently caches hot read requests from server memory that is otherwise idle and unused.

- InvisiTasking® patented intelligent scheduling technology: allows all the DymaxIO “background” operations within the server to run with zero resource impact on current production by only leveraging idle CPU cycles and memory.

- Benefits Dashboard: The “time saved” dashboard demonstrates the value by showing the amount of I/O traffic offloaded from storage, the percentage of read and write I/O traffic offloaded, and the resulting time saved to any one system or group of systems.

New DymaxIO is available as an annual subscription SaaS model.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...