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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

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

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

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...