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It's Not Downtime We Should be Worried About - It's Uptime

Ivar Sagemo

Here's an eight-letter word, twice as bad as any four-letter word, that no business leader wants to hear: downtime. Today's businesses are far more dependent on IT services than ever, and that's true whether you're talking about internal IT services (like ERP) used to drive strategic operations, or external IT services used to satisfy client and customer demand.

Among the more daunting long-term potential consequences of downtime to the organization are these:

• Lost revenues because business couldn't be transacted. A recent Ponemon study tells us the average cost of downtime for US-based organizations is a stunning $5600/minute.

• Diminished brand strength, because the company is seen as unreliable. The same study suggests the average length of downtime was 90 minutes, leading to roughly $500K of costs per incident.

• Evaporating market share, because unhappy customers go to competitors.

Quite a mess in short. And it's a mess that's rapidly getting bigger. Aberdeen Group found that between 2010 and 2012, the cost per hour of downtime climbed an average of 65%!

Now, all of this is obvious in my own area of application performance monitoring (APM), and while downtime is a problem, there is a bigger issue, more subtle lurking just beneath the surface. When we believe everything is running smoothly but don't know something is wrong, that’s when the most damage happens.

For instance, suppose a BizTalk-based service is up and running in a holistic sense, but operating in a subtly inconsistent manner — difficult to detect — that leads to lost transactions from time to time. By this I mean occasionally lost e-mails, lost database entries, lost purchase orders, etc. Time spent by customers resending email and clients waiting or employees spending time looking for an invoice that has not come through – all of these cause more loss in productivity and reputation over a longer period of time.

According to Pricewaterhouse Coopers, the average organization, spends $120 searching for a lost document and wastes 25 hours recreating each lost document.* But what we don't know is how much productivity is lost through not knowing when a problem exists, searching for a file that is not lost at all. Waiting on document resends, searching for "missing" invoices or customer relationships that need to be repaired due to an apparent miscommunication because information is not flowing smoothly in a system all impact company efficiency and costs.

Application performance, and service uptime, can be affected by myriad factors — some as subtle as a gradual shortage of key computational resources. That's why it's important to find a way to granularly monitor your system. To have control and visibility over the problems that are happening so you can decide which ones to tackle is key.

Over time, I think we're going to see that kind of granular insight play a larger and larger role in APM as a field. But in the meantime, it's important to have a clear view of the information that flows throughout your organization so you can see any problem lurking out of sight.

Ivar Sagemo is CEO of AIMS Innovation.

Related Links:

www.aimsinnovation.com

* DocuSense Blog: How Much are Lost Documents Costing You?

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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 ...

It's Not Downtime We Should be Worried About - It's Uptime

Ivar Sagemo

Here's an eight-letter word, twice as bad as any four-letter word, that no business leader wants to hear: downtime. Today's businesses are far more dependent on IT services than ever, and that's true whether you're talking about internal IT services (like ERP) used to drive strategic operations, or external IT services used to satisfy client and customer demand.

Among the more daunting long-term potential consequences of downtime to the organization are these:

• Lost revenues because business couldn't be transacted. A recent Ponemon study tells us the average cost of downtime for US-based organizations is a stunning $5600/minute.

• Diminished brand strength, because the company is seen as unreliable. The same study suggests the average length of downtime was 90 minutes, leading to roughly $500K of costs per incident.

• Evaporating market share, because unhappy customers go to competitors.

Quite a mess in short. And it's a mess that's rapidly getting bigger. Aberdeen Group found that between 2010 and 2012, the cost per hour of downtime climbed an average of 65%!

Now, all of this is obvious in my own area of application performance monitoring (APM), and while downtime is a problem, there is a bigger issue, more subtle lurking just beneath the surface. When we believe everything is running smoothly but don't know something is wrong, that’s when the most damage happens.

For instance, suppose a BizTalk-based service is up and running in a holistic sense, but operating in a subtly inconsistent manner — difficult to detect — that leads to lost transactions from time to time. By this I mean occasionally lost e-mails, lost database entries, lost purchase orders, etc. Time spent by customers resending email and clients waiting or employees spending time looking for an invoice that has not come through – all of these cause more loss in productivity and reputation over a longer period of time.

According to Pricewaterhouse Coopers, the average organization, spends $120 searching for a lost document and wastes 25 hours recreating each lost document.* But what we don't know is how much productivity is lost through not knowing when a problem exists, searching for a file that is not lost at all. Waiting on document resends, searching for "missing" invoices or customer relationships that need to be repaired due to an apparent miscommunication because information is not flowing smoothly in a system all impact company efficiency and costs.

Application performance, and service uptime, can be affected by myriad factors — some as subtle as a gradual shortage of key computational resources. That's why it's important to find a way to granularly monitor your system. To have control and visibility over the problems that are happening so you can decide which ones to tackle is key.

Over time, I think we're going to see that kind of granular insight play a larger and larger role in APM as a field. But in the meantime, it's important to have a clear view of the information that flows throughout your organization so you can see any problem lurking out of sight.

Ivar Sagemo is CEO of AIMS Innovation.

Related Links:

www.aimsinnovation.com

* DocuSense Blog: How Much are Lost Documents Costing You?

Hot Topics

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 ...