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3 Tool Trends in IT Ops

IT budgets have held up quite well despite the pandemic, and the majority of respondents (63%) were actually accelerating or maintaining their digital transformation initiatives, according to an OpsRamp study of 230 IT operations executives in the US and UK in October 2020.

The same IT ops pros said they were focused on buying tools that enabled compelling customer and employee experiences.

The current OpsRamp study, which was conducted in March 2021 and includes input from 132 IT operations directors or above in the UK, tells a similar story. Respondents to this year's survey are still moving forward with digital transformation, but many are re-evaluating the number and type of tools they're using.

There are three main takeaways from the 2021 survey:

Trend 1: Too Many Tools

Only 27% of respondents are highly satisfied with their current monitoring approaches. 52% are moderately satisfied and 21% are somewhat dissatisfied or not at all satisfied.

Areas of improvement for existing tools include the ability to monitor hybrid, multi-cloud and cloud-native infrastructure, integrate data and automate incident response for efficient and timely operations, and support business goals with accurate and relevant insights.

Meanwhile, nearly all IT ops pros (95%) surveyed this year said they're using at least five tools every day and half are using more than 10.

Apparently, though, that's about to change, with 37% saying they expect to cut the number of tools they use this year by half.

Trend 2: AIOps is Here to Stay

AIOps has become a focal point for this "tool rationalization," as the technology appears to have sufficiently demonstrated its ability to act as a sort of connective tissue for centralized operations by delivering proactive insights across different IT monitoring, service management and process automation tools.

The results of the 2021 study back this up, with 48% of respondents saying they have prioritized AIOps across their enterprise IT environments.

The 2021 study also found that 42% of IT ops pros have already deployed AIOps in their organization, and 55% plan to roll out AIOps this year.

Trend 3: Requirements for a Modern IT Ops Solution

Given the strong recent media attention on hacks and data vulnerabilities, it's not surprising that the 2021 study found that platform security, which is the ability to withstand sophisticated attacks, is the most critical attribute of a modern IT ops solution (61%).

The next two capabilities ranked important by IT ops pros were hybrid infrastructure management (53%) for controlling the chaos of distributed architectures, and SaaS and multi-tenant architecture (46%) that allow IT to manage hybrid infrastructure from the cloud, without introducing additional system overhead.

IT ops leaders also see huge value in deploying a digital operations management platform that offers capabilities for hybrid, multi-cloud and cloud-native monitoring, intelligent incident management and automated remediation.

56% of respondents expect to roll out a digital operations management platform this year.

"This study exposes new priorities for IT ops pros and validates many of our hypotheses on the future of IT operations," said George Bonser, VP of EMEA Sales for OpsRamp. "The pandemic accelerated many of the mid-flight digital transformation initiatives. Tools are a valuable part of the IT operations portfolio, but the future belongs to digital operations management platforms that can consolidate data across hybrid environments, apply machine learning to drive faster incident analysis, and use process automation to handle repetitive work."

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 ...

3 Tool Trends in IT Ops

IT budgets have held up quite well despite the pandemic, and the majority of respondents (63%) were actually accelerating or maintaining their digital transformation initiatives, according to an OpsRamp study of 230 IT operations executives in the US and UK in October 2020.

The same IT ops pros said they were focused on buying tools that enabled compelling customer and employee experiences.

The current OpsRamp study, which was conducted in March 2021 and includes input from 132 IT operations directors or above in the UK, tells a similar story. Respondents to this year's survey are still moving forward with digital transformation, but many are re-evaluating the number and type of tools they're using.

There are three main takeaways from the 2021 survey:

Trend 1: Too Many Tools

Only 27% of respondents are highly satisfied with their current monitoring approaches. 52% are moderately satisfied and 21% are somewhat dissatisfied or not at all satisfied.

Areas of improvement for existing tools include the ability to monitor hybrid, multi-cloud and cloud-native infrastructure, integrate data and automate incident response for efficient and timely operations, and support business goals with accurate and relevant insights.

Meanwhile, nearly all IT ops pros (95%) surveyed this year said they're using at least five tools every day and half are using more than 10.

Apparently, though, that's about to change, with 37% saying they expect to cut the number of tools they use this year by half.

Trend 2: AIOps is Here to Stay

AIOps has become a focal point for this "tool rationalization," as the technology appears to have sufficiently demonstrated its ability to act as a sort of connective tissue for centralized operations by delivering proactive insights across different IT monitoring, service management and process automation tools.

The results of the 2021 study back this up, with 48% of respondents saying they have prioritized AIOps across their enterprise IT environments.

The 2021 study also found that 42% of IT ops pros have already deployed AIOps in their organization, and 55% plan to roll out AIOps this year.

Trend 3: Requirements for a Modern IT Ops Solution

Given the strong recent media attention on hacks and data vulnerabilities, it's not surprising that the 2021 study found that platform security, which is the ability to withstand sophisticated attacks, is the most critical attribute of a modern IT ops solution (61%).

The next two capabilities ranked important by IT ops pros were hybrid infrastructure management (53%) for controlling the chaos of distributed architectures, and SaaS and multi-tenant architecture (46%) that allow IT to manage hybrid infrastructure from the cloud, without introducing additional system overhead.

IT ops leaders also see huge value in deploying a digital operations management platform that offers capabilities for hybrid, multi-cloud and cloud-native monitoring, intelligent incident management and automated remediation.

56% of respondents expect to roll out a digital operations management platform this year.

"This study exposes new priorities for IT ops pros and validates many of our hypotheses on the future of IT operations," said George Bonser, VP of EMEA Sales for OpsRamp. "The pandemic accelerated many of the mid-flight digital transformation initiatives. Tools are a valuable part of the IT operations portfolio, but the future belongs to digital operations management platforms that can consolidate data across hybrid environments, apply machine learning to drive faster incident analysis, and use process automation to handle repetitive work."

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 ...