Skip to main content

Cherwell Announces New SaaS Offerings

Cherwell Software announced the availability of new SaaS hosting technology offerings in the US this month, delivering significant performance improvements that include hourly data backup, as well as monitoring by four different systems every 60 seconds, and 24x7 staffing.

With several datacenters on three continents and planned expansions in 2014, Cherwell Software continues to advance its SaaS strategy worldwide.

“We believe that Cherwell Software’s SaaS business is currently experiencing hyper-growth, and with our new advanced SaaS technologies, scheduled downtime for planned upgrades is now practically non-existent,” said Vance Brown, CEO of Cherwell Software. “Cherwell delivers the best cloud solution with the fastest recovery time in the business technology industry—no other service management company offers this level of SaaS performance.”

Cherwell Software has invested significantly in SaaS hosting technologies to deliver high-availability data centers to its customers, this month in the U.S. and coming soon in EMEA. Near real-time failover is now available with a recovery point objective (RPO) of one hour. Failover between data centers is reducing the current recovery time objective (RTO) to less than two hours. In Cherwell Software's European data centers, disaster recovery is available for customers with a site in Manchester, U.K., where RTO will be reduced to four hours and a RPO of one hour.

Scheduled downtime for Cherwell Service Management SaaS production systems will be reduced to just minutes, while failover is taking place between data centers. Systems are monitored every 60 seconds by four different monitoring systems, and employees are staffed to respond on a 24x7 basis. Cherwell Software currently has extra hardware available to its customers in the event of server failure, and there is no extra charge to customers for this capability.

Cherwell provides customers with flexibility in every step of the decision-making process: licensing and hosting, subscription or purchase. Customers can choose hosting by Cherwell, on-premise, or hosting by a third party.

“Customers can switch from SaaS to on-premise in a couple hours, because Cherwell uses the same code base for both SaaS and on-premise. Our licensing and hosting model Cherwell Choice™ offers maximum portability,” said Brown. “We are willing to invest in extraordinary customer satisfaction—we have added all this SaaS capability in direct response to customer requests and market demand.”

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 ...

Cherwell Announces New SaaS Offerings

Cherwell Software announced the availability of new SaaS hosting technology offerings in the US this month, delivering significant performance improvements that include hourly data backup, as well as monitoring by four different systems every 60 seconds, and 24x7 staffing.

With several datacenters on three continents and planned expansions in 2014, Cherwell Software continues to advance its SaaS strategy worldwide.

“We believe that Cherwell Software’s SaaS business is currently experiencing hyper-growth, and with our new advanced SaaS technologies, scheduled downtime for planned upgrades is now practically non-existent,” said Vance Brown, CEO of Cherwell Software. “Cherwell delivers the best cloud solution with the fastest recovery time in the business technology industry—no other service management company offers this level of SaaS performance.”

Cherwell Software has invested significantly in SaaS hosting technologies to deliver high-availability data centers to its customers, this month in the U.S. and coming soon in EMEA. Near real-time failover is now available with a recovery point objective (RPO) of one hour. Failover between data centers is reducing the current recovery time objective (RTO) to less than two hours. In Cherwell Software's European data centers, disaster recovery is available for customers with a site in Manchester, U.K., where RTO will be reduced to four hours and a RPO of one hour.

Scheduled downtime for Cherwell Service Management SaaS production systems will be reduced to just minutes, while failover is taking place between data centers. Systems are monitored every 60 seconds by four different monitoring systems, and employees are staffed to respond on a 24x7 basis. Cherwell Software currently has extra hardware available to its customers in the event of server failure, and there is no extra charge to customers for this capability.

Cherwell provides customers with flexibility in every step of the decision-making process: licensing and hosting, subscription or purchase. Customers can choose hosting by Cherwell, on-premise, or hosting by a third party.

“Customers can switch from SaaS to on-premise in a couple hours, because Cherwell uses the same code base for both SaaS and on-premise. Our licensing and hosting model Cherwell Choice™ offers maximum portability,” said Brown. “We are willing to invest in extraordinary customer satisfaction—we have added all this SaaS capability in direct response to customer requests and market demand.”

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 ...