Skip to main content

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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...