Skip to main content

2 Out of 3 IT Pros Put Systems at Risk of Downtime

Pete Goldin
APMdigest

Almost three-fourths (70%) of companies forget about documenting changes, up from 57% last year, according to Netwrix Corporation's 2015 State of IT Changes Survey, covering 700 IT professionals across over 40 industries.

In addition, the number of large enterprises that make undocumented changes has increased by 20% to 66%.

Undocumented changes pose a hidden threat to business continuity and the integrity of sensitive data. The survey shows that 67% of companies suffer from service downtime due to unauthorized or incorrect changes to system configurations, while the worst offenders are again enterprises in 73% of cases.

The report states: "Incorrect or unauthorized changes to system configurations can impact sustainability of business processes and cause IT services to stop. The majority of IT pros admit that they still are not able to control sustainable performance of their IT systems and continue to make changes that were a root cause of system downtime; the share has even increased throughout the year."

Despite the fact that companies still have shortcomings in their change management policies, the overall results of 2015 show a positive trend. More organizations have changed their approach to changes and have made some effort to establish auditing processes to achieve visibility into their IT infrastructures.

Key survey findings:

■ 80% of organizations surveyed continue to claim they document changes; however, the number of companies that make undocumented changes has grown throughout the year and reached 70%. The frequency of those changes has also increased.

■ 58% of small companies surveyed have started to track changes despite the lack of change management controls, against 30% last year.

■ Change auditing technology continues to capture the market, as 52% of organizations surveyed have established change auditing controls, compared to 38% last year. Today, 75% of enterprises surveyed (52% in 2014) have established change auditing processes to monitor their IT infrastructures.

■ Organizations opt for several methods of change auditing at once. 60% of SMBs surveyed traditionally choose manual monitoring of native logs, whereas 65% of enterprises deploy automated auditing solutions.


Pete Goldin is Editor and Publisher of APMdigest

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 ...

2 Out of 3 IT Pros Put Systems at Risk of Downtime

Pete Goldin
APMdigest

Almost three-fourths (70%) of companies forget about documenting changes, up from 57% last year, according to Netwrix Corporation's 2015 State of IT Changes Survey, covering 700 IT professionals across over 40 industries.

In addition, the number of large enterprises that make undocumented changes has increased by 20% to 66%.

Undocumented changes pose a hidden threat to business continuity and the integrity of sensitive data. The survey shows that 67% of companies suffer from service downtime due to unauthorized or incorrect changes to system configurations, while the worst offenders are again enterprises in 73% of cases.

The report states: "Incorrect or unauthorized changes to system configurations can impact sustainability of business processes and cause IT services to stop. The majority of IT pros admit that they still are not able to control sustainable performance of their IT systems and continue to make changes that were a root cause of system downtime; the share has even increased throughout the year."

Despite the fact that companies still have shortcomings in their change management policies, the overall results of 2015 show a positive trend. More organizations have changed their approach to changes and have made some effort to establish auditing processes to achieve visibility into their IT infrastructures.

Key survey findings:

■ 80% of organizations surveyed continue to claim they document changes; however, the number of companies that make undocumented changes has grown throughout the year and reached 70%. The frequency of those changes has also increased.

■ 58% of small companies surveyed have started to track changes despite the lack of change management controls, against 30% last year.

■ Change auditing technology continues to capture the market, as 52% of organizations surveyed have established change auditing controls, compared to 38% last year. Today, 75% of enterprises surveyed (52% in 2014) have established change auditing processes to monitor their IT infrastructures.

■ Organizations opt for several methods of change auditing at once. 60% of SMBs surveyed traditionally choose manual monitoring of native logs, whereas 65% of enterprises deploy automated auditing solutions.


Pete Goldin is Editor and Publisher of APMdigest

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 ...