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Data Center Outages Becoming Less Frequent

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute.

For the fourth consecutive year, Uptime Intelligence Research suggests that overall outage frequency and the general level of reported severity continue to decline. However, cybersecurity incidents are on the rise and often have severe, lasting impacts.

"Outages overall have slowed down," said Andy Lawrence, founding member and executive director, Uptime Intelligence. "Data center operators are facing a growing number of external risks beyond their control, including power grid constraints, extreme weather, network provider failures and third-party software issues. And despite a more volatile risk landscape, improvements are occurring."

Key findings include:

Less Outages

Outages are becoming less frequent and less severe relative to the rapid growth of digital infrastructure. This trend has held for several years, underscoring industry progress in risk management and reliability.

For the third consecutive year, the financial sector saw a decline in outage frequency compared with the long-term average since 2020. This improvement may reflect the impact of stricter regulations and heightened oversight following several major, high-profile outages prior to 2021.

For 2024, outages attributed to digital service providers increased, while those from cloud/internet giants declined, possibly due to hyperscalers' investments in distributed resiliency and regional failover.

Power Remains Leading Outage Cause

Power remains the leading cause of impactful outages. Outages from IT and networking issues increased in 2024, totaling 23% of impactful outages. This trend reflects the long-term move toward colocation providers, cloud, and other third-party services. While outsourcing may reduce the risk for some enterprises, major failures still occur, sometimes with serious consequences. This rise is likely caused by increased IT and network complexity, leading to issues with change management and misconfigurations.

Software-Based and Distributed Resiliency Tools Expanding

Software-based and distributed resiliency tools are expanding. These systems improve uptime but can also introduce new risks and complexities. The use of software-based resiliency strategies alongside physical failover/redundancy is undoubtedly contributing to overall improvements in availability. However, the added complexity brings its own challenges and can blur lines of responsibility for failures, complicating root cause analysis and outage classification.

Pace of Transformation Accelerating

The pace of industry transformation is accelerating. Soaring demand for AI is straining existing infrastructure designs — especially around power and cooling — while electricity grid limitations and global trade tensions introduce new uncertainty in supply chains and expansion plans. Together, these pressures could eventually affect the stability of current reliability trends.

Outages from Human Error Increasing

For 2025, the proportion of human error-related outages caused by failure to follow procedures rose by ten percentage points compared with 2024. The failure of staff to follow procedures has become an even greater cause of outages than in the previous year, suggesting a major opportunity to reduce incidents through training and process review. The overwhelming majority of human error-related outages involve ignored or inadequate procedures.

Nearly 40% of organizations have suffered a major outage caused by human error over the past three years. Of these incidents, 85% stem from staff failing to follow procedures or from flaws in the processes and procedures themselves. The reason for this rise is unclear but may be a consequence of the rapid growth of industry and the resulting staff shortages in many regions.

While improving documentation and processes remains important, greater focus on staff training and real-time operational support may reduce risks more effectively.

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 ...

Data Center Outages Becoming Less Frequent

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute.

For the fourth consecutive year, Uptime Intelligence Research suggests that overall outage frequency and the general level of reported severity continue to decline. However, cybersecurity incidents are on the rise and often have severe, lasting impacts.

"Outages overall have slowed down," said Andy Lawrence, founding member and executive director, Uptime Intelligence. "Data center operators are facing a growing number of external risks beyond their control, including power grid constraints, extreme weather, network provider failures and third-party software issues. And despite a more volatile risk landscape, improvements are occurring."

Key findings include:

Less Outages

Outages are becoming less frequent and less severe relative to the rapid growth of digital infrastructure. This trend has held for several years, underscoring industry progress in risk management and reliability.

For the third consecutive year, the financial sector saw a decline in outage frequency compared with the long-term average since 2020. This improvement may reflect the impact of stricter regulations and heightened oversight following several major, high-profile outages prior to 2021.

For 2024, outages attributed to digital service providers increased, while those from cloud/internet giants declined, possibly due to hyperscalers' investments in distributed resiliency and regional failover.

Power Remains Leading Outage Cause

Power remains the leading cause of impactful outages. Outages from IT and networking issues increased in 2024, totaling 23% of impactful outages. This trend reflects the long-term move toward colocation providers, cloud, and other third-party services. While outsourcing may reduce the risk for some enterprises, major failures still occur, sometimes with serious consequences. This rise is likely caused by increased IT and network complexity, leading to issues with change management and misconfigurations.

Software-Based and Distributed Resiliency Tools Expanding

Software-based and distributed resiliency tools are expanding. These systems improve uptime but can also introduce new risks and complexities. The use of software-based resiliency strategies alongside physical failover/redundancy is undoubtedly contributing to overall improvements in availability. However, the added complexity brings its own challenges and can blur lines of responsibility for failures, complicating root cause analysis and outage classification.

Pace of Transformation Accelerating

The pace of industry transformation is accelerating. Soaring demand for AI is straining existing infrastructure designs — especially around power and cooling — while electricity grid limitations and global trade tensions introduce new uncertainty in supply chains and expansion plans. Together, these pressures could eventually affect the stability of current reliability trends.

Outages from Human Error Increasing

For 2025, the proportion of human error-related outages caused by failure to follow procedures rose by ten percentage points compared with 2024. The failure of staff to follow procedures has become an even greater cause of outages than in the previous year, suggesting a major opportunity to reduce incidents through training and process review. The overwhelming majority of human error-related outages involve ignored or inadequate procedures.

Nearly 40% of organizations have suffered a major outage caused by human error over the past three years. Of these incidents, 85% stem from staff failing to follow procedures or from flaws in the processes and procedures themselves. The reason for this rise is unclear but may be a consequence of the rapid growth of industry and the resulting staff shortages in many regions.

While improving documentation and processes remains important, greater focus on staff training and real-time operational support may reduce risks more effectively.

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 ...