The Future of Monitoring and AIOps

Learn more about BigPanda

In response to noisier and more complex IT environments, operations teams are growing in size and using more monitoring tools. But timely outage detection, investigation and resolution are still a major challenge.

"IT operations is at a crossroads, as constant changes to infrastructure and code due to the acceleration in cloud migration makes incident management and outage prevention an increasingly difficult task," said Assaf Resnick, CEO and co-founder, BigPanda. "This survey shows that most IT organizations predict growing future workloads because of these changes, even as budgets shrink or remain constant. We hope this survey helps illuminate what IT Ops, NOC and DevOps teams think about the current and future state of their operations, what tools might be able to help and where AIOps fits into their plans."

BigPanda conducted a survey of 1,300 IT professionals, spanning IT operations (IT Ops), NOC, DevOps and other functions at companies in a wide range of industries. The report, The Future of Monitoring and AIOps, highlights how challenging it is for teams to contend with complex IT environments:

■ Nearly half (47%) of respondents experience hourly to weekly code changes, and 48% expect public cloud migration to accelerate in the next two years.

■ A majority (53%) believe their IT Ops/NOC workloads will increase in the next two years.

■ 42% of respondents use more than 10 different monitoring tools to contend with these changes.

■ Very few teams are satisfied with their ability to handle different aspects of incident management, such as incident investigation (23% are satisfied today), incident resolution (28% are satisfied), and incident detection (a mere 18% are satisfied with their current state).

■ Furthermore, three-quarters of IT teams don’t feel their IT Ops tools enable automation.

AIOps, Intelligent Automation and Black-Box Concerns

Most (56%) respondents feel more automation and nearly half (46%) feel the implementation of AI and Machine Learning (ML) in their organizations will offer them more control over their workloads, as nearly one-third are actively evaluating and researching AIOps tools.  AIOps presents a solution that melds AI with IT Ops and fosters automation. However:

■ The vast majority of respondents (89%) want ease of adoption from their AIOps tools, and 84% need their AIOps tools to work well with existing tools.

■ 81% of respondents don’t want to rely on data scientists in order to operationalize their AIOps tools.

Importantly, the majority of respondents are uncomfortable with opaque black-box AIOps tools, which suggests that AIOps tools should be more transparent about their underlying ML logic.

79% of respondents want to see the ML logic behind the AIOps tool, 81% want to be able to edit the logic, and 85% want to preview results before deploying the ML logic to production.

These results highlight the importance of effective and automated IT incident management for IT Ops, NOC and DevOps teams that must grapple with increasingly noisy, complex and fast-moving IT environments.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The Future of Monitoring and AIOps

Learn more about BigPanda

In response to noisier and more complex IT environments, operations teams are growing in size and using more monitoring tools. But timely outage detection, investigation and resolution are still a major challenge.

"IT operations is at a crossroads, as constant changes to infrastructure and code due to the acceleration in cloud migration makes incident management and outage prevention an increasingly difficult task," said Assaf Resnick, CEO and co-founder, BigPanda. "This survey shows that most IT organizations predict growing future workloads because of these changes, even as budgets shrink or remain constant. We hope this survey helps illuminate what IT Ops, NOC and DevOps teams think about the current and future state of their operations, what tools might be able to help and where AIOps fits into their plans."

BigPanda conducted a survey of 1,300 IT professionals, spanning IT operations (IT Ops), NOC, DevOps and other functions at companies in a wide range of industries. The report, The Future of Monitoring and AIOps, highlights how challenging it is for teams to contend with complex IT environments:

■ Nearly half (47%) of respondents experience hourly to weekly code changes, and 48% expect public cloud migration to accelerate in the next two years.

■ A majority (53%) believe their IT Ops/NOC workloads will increase in the next two years.

■ 42% of respondents use more than 10 different monitoring tools to contend with these changes.

■ Very few teams are satisfied with their ability to handle different aspects of incident management, such as incident investigation (23% are satisfied today), incident resolution (28% are satisfied), and incident detection (a mere 18% are satisfied with their current state).

■ Furthermore, three-quarters of IT teams don’t feel their IT Ops tools enable automation.

AIOps, Intelligent Automation and Black-Box Concerns

Most (56%) respondents feel more automation and nearly half (46%) feel the implementation of AI and Machine Learning (ML) in their organizations will offer them more control over their workloads, as nearly one-third are actively evaluating and researching AIOps tools.  AIOps presents a solution that melds AI with IT Ops and fosters automation. However:

■ The vast majority of respondents (89%) want ease of adoption from their AIOps tools, and 84% need their AIOps tools to work well with existing tools.

■ 81% of respondents don’t want to rely on data scientists in order to operationalize their AIOps tools.

Importantly, the majority of respondents are uncomfortable with opaque black-box AIOps tools, which suggests that AIOps tools should be more transparent about their underlying ML logic.

79% of respondents want to see the ML logic behind the AIOps tool, 81% want to be able to edit the logic, and 85% want to preview results before deploying the ML logic to production.

These results highlight the importance of effective and automated IT incident management for IT Ops, NOC and DevOps teams that must grapple with increasingly noisy, complex and fast-moving IT environments.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...