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ITOps and DevOps Spending 10 Extra Hours Per Week Resolving Incidents During Pandemic

More than 80% of organizations have experienced a significant increase in pressure on digital services since the start of the COVID-19 pandemic, according to a survey by PagerDuty.

These same companies cited a 47% increase in the number of daily incidents, resulting in 62% of IT and DevOps practitioners spending more than 10 extra hours per week resolving incidents, compared to six months ago.

The global survey, which involved more than 700 DevOps and IT practitioners across North America, EMEA and APJ, also shows that 40% of organizations expect this digital pressure to get worse in the next six to 12 months.

"The pandemic has irreversibly changed the way we live, work, communicate, learn and shop. We now exist in a digital default world and the stakes are high. Downtime can mean millions in lost revenue and keeping digital services running perfectly is a complex job," said Rachel Obstler, VP of Product at PagerDuty. "This research underscores the fact that every company is facing the challenge of accelerating their digital transformation to keep pace with customer expectations and needs, while grappling with increased digital complexity and strain. It also candidly points to the human cost of this dramatic change — an immense strain on the practitioners charged with keeping digital services running which can lead to massive burnout."

Since the pandemic began, 55% of respondents divulged that they are asked to resolve incidents during their personal time five or more times a week, and 39% say they are firefighting or focused on unplanned work 100% of the time, which leaves no room for proactive, innovative work.

As a result, organizations have had to cancel or delay an average of 7.6 projects in the last three to six months.

Other survey highlights include:

■ The top reason respondents stay at their jobs is because of the teams and the camaraderie in DevOps/IT (71%).

■ 58% said they are grateful for the opportunity to play an integral role in the digital economy.

■ 53% said the pressure to keep digital services running perfectly has reached unprecedented levels in the last 3-6 months.

■ 46% feel overwhelmed when thinking about the next 12 months and feel the volume of work in the future will be significant.

■ 79% believe digital acceleration has to be their company's number one priority in 2021.

■ 51% cite intelligent data and insights that help prioritize where to spend time are critical.

■ 64% believe automation that removes manual processes will be critical to do more with less and meet increased demand on digital services.

■ 69% believe smart integrations are critical to doing their job better.

"As organizations strive to capitalize on the new norm of digital first, they must modernize and automate how they manage their digital operations, because the old approach doesn't work anymore. You need AI and machine learning, and automation, in order to remove complexity and be proactive and predictive," Obstler continued. "Any company that fails to mature their approach, compromises customer experience, employee health, critical projects and risks significantly impacting cost structure."

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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 ...

ITOps and DevOps Spending 10 Extra Hours Per Week Resolving Incidents During Pandemic

More than 80% of organizations have experienced a significant increase in pressure on digital services since the start of the COVID-19 pandemic, according to a survey by PagerDuty.

These same companies cited a 47% increase in the number of daily incidents, resulting in 62% of IT and DevOps practitioners spending more than 10 extra hours per week resolving incidents, compared to six months ago.

The global survey, which involved more than 700 DevOps and IT practitioners across North America, EMEA and APJ, also shows that 40% of organizations expect this digital pressure to get worse in the next six to 12 months.

"The pandemic has irreversibly changed the way we live, work, communicate, learn and shop. We now exist in a digital default world and the stakes are high. Downtime can mean millions in lost revenue and keeping digital services running perfectly is a complex job," said Rachel Obstler, VP of Product at PagerDuty. "This research underscores the fact that every company is facing the challenge of accelerating their digital transformation to keep pace with customer expectations and needs, while grappling with increased digital complexity and strain. It also candidly points to the human cost of this dramatic change — an immense strain on the practitioners charged with keeping digital services running which can lead to massive burnout."

Since the pandemic began, 55% of respondents divulged that they are asked to resolve incidents during their personal time five or more times a week, and 39% say they are firefighting or focused on unplanned work 100% of the time, which leaves no room for proactive, innovative work.

As a result, organizations have had to cancel or delay an average of 7.6 projects in the last three to six months.

Other survey highlights include:

■ The top reason respondents stay at their jobs is because of the teams and the camaraderie in DevOps/IT (71%).

■ 58% said they are grateful for the opportunity to play an integral role in the digital economy.

■ 53% said the pressure to keep digital services running perfectly has reached unprecedented levels in the last 3-6 months.

■ 46% feel overwhelmed when thinking about the next 12 months and feel the volume of work in the future will be significant.

■ 79% believe digital acceleration has to be their company's number one priority in 2021.

■ 51% cite intelligent data and insights that help prioritize where to spend time are critical.

■ 64% believe automation that removes manual processes will be critical to do more with less and meet increased demand on digital services.

■ 69% believe smart integrations are critical to doing their job better.

"As organizations strive to capitalize on the new norm of digital first, they must modernize and automate how they manage their digital operations, because the old approach doesn't work anymore. You need AI and machine learning, and automation, in order to remove complexity and be proactive and predictive," Obstler continued. "Any company that fails to mature their approach, compromises customer experience, employee health, critical projects and risks significantly impacting cost structure."

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 ...