2023 Application Performance Management Predictions - Part 6

Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, OpenTelemetry and related technologies will evolve and impact business in 2023. Part 6 covers more on AIOps.

Start with: 2023 Application Performance Management Predictions - Part 1

Start with: 2023 Application Performance Management Predictions - Part 2

Start with: 2023 Application Performance Management Predictions - Part 3

Start with: 2023 Application Performance Management Predictions - Part 4

Start with: 2023 Application Performance Management Predictions - Part 5

NEW BUSINESS-ALIGNED APPROACH TO AIOPS

IT organizations will continue to shift from a technology-focused approach for IT operations management and AIOps to more of a solution and process-focused approach in the coming year. Historically, many IT teams focused on extensive and time-consuming point product side-by-side comparison matrixes try to guess which algorithm is the biggest and fastest and then worried about how to implement that tool with their processes later. The new business-aligned approach will think about current and future process implementation at the same time to improve automated problem detection and remediation.
Matt Gowarty
Senior Manager, Product Marketing, IT Operations Management, ServiceNow

GROWTH OF SAAS AIOPS

Enterprises have realized there is no one master observability tool they can depend on. They are sitting on heaps of observability data which can be used to predict outages and help operations teams triage the right issues while reducing false alerts. Despite there being multiple tools to use for correlations, the introduction of full-stack observability APM tools with AI/ML techniques to predict and triage issues will help in reducing downtime and aid in better planning for technology updates. As adoption continues, we anticipate further growth of SaaS AIOps solutions, making them more widely accessible and available to small- to medium-size businesses.
George Thangadurai
CEO, HEAL Software

AIOPS ENABLES PLATFORMOPS

IT organizations will start implementing PlatformOps for everything from observability, DevOps, SecOps, ServiceOps, and analytics — to glue together all the different use cases demanded by various stakeholder teams in business, technology, compliance, security, etc. AIOps platforms will be a key enabler for implementing the enterprise PlatformOps technology stack.
Srini Miriyala
Marketing & Business Development, APAC, CloudFabrix

EVENT CORRELATION AND AIOPS

Event Correlation and AIOps adoption will increase in 2023. With applications becoming wholly cloud-native, organizations are adopting a microservices-based architecture for their business efficiency. This system relies heavily on a complex underlying infrastructure, which increases the influx of events — telemetry data. It will be next to impossible to manually ascertain operational and security pitfalls, thus expanding the scope for mainstream adoption of event correlation and AIOps.
Srinivasa Raghavan
Director of Product Management at Site24x7 and ManageEngine

PRODUCTION AIOPS ENVIRONMENTS MIGRATE TO KUBERNETES

After hearing the buzzword AIOps circling for so long, it's exciting to finally see some of the first (small) successes, after years of promise. This is in large part thanks to the standardization we are seeing in the industry around widely adopted technologies like Kubernetes (that have become an industry standard for many disciplines, including AI). I believe production environments for AIOps are going to migrate to Kubernetes, which will be a real game changer for real-time analytics and ops.
Itiel Shwartz
CTO and Co-Founder, Komodor

ENTERPRISES COMBAT IT SKILLS CRUNCH WITH AIOPS

Amidst an ever-growing IT skills gap, enterprises are crunched for talent, while juggling budget cuts, heightened productivity KPIs and a lack of qualified talent. In 2023, enterprises will rely on AIOps driven-automation to bridge the gap and enable them to deliver autonomous workspaces, simplifying IT administration and reducing dependency on skilled IT labor. Enterprises will increasingly lean on Unified Endpoint Management (UEM) to automate workflows to eliminate manual intervention across device management, security and user-experience. In addition, UEM solutions will leverage AIOps for data-driven automation with proactive detection and remediation of device performance and other manual processes.
Mathivanan Venkatachalam
Vice President, ManageEngine

AIOPS DISAPPOINTS

AIOps will continue to disappoint as a broad solution that can automagically detect and resolve IT issues. AIOps, when utilized correctly and in the correct places, can be immensely helpful by allowing for the analysis of significant quantities of data and identification of patterns that a human is likely to miss. However, the idea that AIOps will be able to detect all (or even almost all) issues, identify the root cause, develop a remediation plan, and then implement that plan is unrealistic. Networks (and associated environments) are simply too complicated and unique for any tool to be able to work across broad swaths of organizations. Instead AIOps tools will continue to excel in narrowly focused areas where they are doing things such as analyzing the huge quantities of data organizations currently collect and identifying specific anomalies that can then be addressed in specific ways through either automation or human intervention.
Josh Chessman
VP, Strategy & Innovation, Netreo

Go to: 2023 Application Performance Management Predictions - Part 7, covering the user experience.

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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 End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

5 Security Principles Every Entrepreneur Should Apply to Leadership

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

2023 Application Performance Management Predictions - Part 6

Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, OpenTelemetry and related technologies will evolve and impact business in 2023. Part 6 covers more on AIOps.

Start with: 2023 Application Performance Management Predictions - Part 1

Start with: 2023 Application Performance Management Predictions - Part 2

Start with: 2023 Application Performance Management Predictions - Part 3

Start with: 2023 Application Performance Management Predictions - Part 4

Start with: 2023 Application Performance Management Predictions - Part 5

NEW BUSINESS-ALIGNED APPROACH TO AIOPS

IT organizations will continue to shift from a technology-focused approach for IT operations management and AIOps to more of a solution and process-focused approach in the coming year. Historically, many IT teams focused on extensive and time-consuming point product side-by-side comparison matrixes try to guess which algorithm is the biggest and fastest and then worried about how to implement that tool with their processes later. The new business-aligned approach will think about current and future process implementation at the same time to improve automated problem detection and remediation.
Matt Gowarty
Senior Manager, Product Marketing, IT Operations Management, ServiceNow

GROWTH OF SAAS AIOPS

Enterprises have realized there is no one master observability tool they can depend on. They are sitting on heaps of observability data which can be used to predict outages and help operations teams triage the right issues while reducing false alerts. Despite there being multiple tools to use for correlations, the introduction of full-stack observability APM tools with AI/ML techniques to predict and triage issues will help in reducing downtime and aid in better planning for technology updates. As adoption continues, we anticipate further growth of SaaS AIOps solutions, making them more widely accessible and available to small- to medium-size businesses.
George Thangadurai
CEO, HEAL Software

AIOPS ENABLES PLATFORMOPS

IT organizations will start implementing PlatformOps for everything from observability, DevOps, SecOps, ServiceOps, and analytics — to glue together all the different use cases demanded by various stakeholder teams in business, technology, compliance, security, etc. AIOps platforms will be a key enabler for implementing the enterprise PlatformOps technology stack.
Srini Miriyala
Marketing & Business Development, APAC, CloudFabrix

EVENT CORRELATION AND AIOPS

Event Correlation and AIOps adoption will increase in 2023. With applications becoming wholly cloud-native, organizations are adopting a microservices-based architecture for their business efficiency. This system relies heavily on a complex underlying infrastructure, which increases the influx of events — telemetry data. It will be next to impossible to manually ascertain operational and security pitfalls, thus expanding the scope for mainstream adoption of event correlation and AIOps.
Srinivasa Raghavan
Director of Product Management at Site24x7 and ManageEngine

PRODUCTION AIOPS ENVIRONMENTS MIGRATE TO KUBERNETES

After hearing the buzzword AIOps circling for so long, it's exciting to finally see some of the first (small) successes, after years of promise. This is in large part thanks to the standardization we are seeing in the industry around widely adopted technologies like Kubernetes (that have become an industry standard for many disciplines, including AI). I believe production environments for AIOps are going to migrate to Kubernetes, which will be a real game changer for real-time analytics and ops.
Itiel Shwartz
CTO and Co-Founder, Komodor

ENTERPRISES COMBAT IT SKILLS CRUNCH WITH AIOPS

Amidst an ever-growing IT skills gap, enterprises are crunched for talent, while juggling budget cuts, heightened productivity KPIs and a lack of qualified talent. In 2023, enterprises will rely on AIOps driven-automation to bridge the gap and enable them to deliver autonomous workspaces, simplifying IT administration and reducing dependency on skilled IT labor. Enterprises will increasingly lean on Unified Endpoint Management (UEM) to automate workflows to eliminate manual intervention across device management, security and user-experience. In addition, UEM solutions will leverage AIOps for data-driven automation with proactive detection and remediation of device performance and other manual processes.
Mathivanan Venkatachalam
Vice President, ManageEngine

AIOPS DISAPPOINTS

AIOps will continue to disappoint as a broad solution that can automagically detect and resolve IT issues. AIOps, when utilized correctly and in the correct places, can be immensely helpful by allowing for the analysis of significant quantities of data and identification of patterns that a human is likely to miss. However, the idea that AIOps will be able to detect all (or even almost all) issues, identify the root cause, develop a remediation plan, and then implement that plan is unrealistic. Networks (and associated environments) are simply too complicated and unique for any tool to be able to work across broad swaths of organizations. Instead AIOps tools will continue to excel in narrowly focused areas where they are doing things such as analyzing the huge quantities of data organizations currently collect and identifying specific anomalies that can then be addressed in specific ways through either automation or human intervention.
Josh Chessman
VP, Strategy & Innovation, Netreo

Go to: 2023 Application Performance Management Predictions - Part 7, covering the user experience.

Related Links

Hot Topics

The Latest

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 End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

5 Security Principles Every Entrepreneur Should Apply to Leadership

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...