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Discovering AIOps - Part 8: The Future of AIOps

Pete Goldin
Editor and Publisher
APMdigest

The future of AIOps holds significant promise and potential, Ali Siddiqui, Chief Product Officer at BMC predicts. As technology continues to advance, AIOps is likely to play a crucial role in reshaping the landscape of IT operations and business processes. In the era of data-driven decision-making and automation, there will be a significant surge in the demand for AIOps and generative AI. The organizations that can effectively leverage the potential of these will be the ones defining the future landscape of enterprise software.

Overall, AIOps is poised to revolutionize how businesses manage their IT operations, making them more efficient, resilient, and customer-centric, Siddiqui continues. As the technology matures and becomes more widely adopted, it will undoubtedly bring about transformative changes across industries, contributing to improved business outcomes and customer satisfaction.

Start with: Discovering AIOps - Part 1

Start with: Discovering AIOps - Part 2: Must-Have Capabilities

Start with: Discovering AIOps - Part 3: The Users

Start with: Discovering AIOps - Part 4: Advantages

Start with: Discovering AIOps - Part 5: More Advantages

Start with: Discovering AIOps - Part 6: Challenges

Start with: Discovering AIOps - Part 7: The Current State of AIOps

Part 7 of this blog series covered the current state of AIOps. Now, in Part 8, the experts provide their visions for the future of AIOps:

Becoming the Norm

"I think AIOps becomes the norm and not hyped as the latest thing. I'm hopeful that more people quickly see the value and purpose faster so as to enable the adoption of more advanced automation," Carlos Casanova, Principal Analyst at Forrester Research

Helping but Not Replacing ITOPS

"AIOps has definitely changed the way we think about solving problems. In the least, it has allowed us to dream about what may be possible for this still nascent set of capabilities. Because that's what AIOps truly is — a set of capabilities. In the same way monitoring has evolved into a conversation about observability, automation and data (of all types) have evolved into a conversation about AIOps. And since capabilities are the true gateway to positive business outcomes, it is great to see that — according to the most recent SRE survey — reliability practitioners believe AIOPs will make their work easier (52%), while not replacing them (4%)," says Leo Vasiliou, Director of Product Marketing at Catchpoint.

Image removed.

"I believe that most of this technology will be in the form of a very intelligent assistant, rather than replace humans in the loop. I do think it will help eliminate a lot of the groundwork and help teams be more effective and faster in remediating problems," adds Spiros Xanthos, SVP and General Manager of Observability at Splunk.

Complementing Observability

"Observability plays a vital role, working hand-in-hand with AIOps to form a powerful combination, which complements and reinforces each other. An organization equipped with both can leverage AIOps for more intelligent and dynamic monitoring, featuring anomaly detection and advanced root cause analysis," says Siddiqui from BMC.

AIOps for Each Vertical

"People tend to only think about it in the context of alerting or applying CI/CD techniques to IT, but you can also see AIOps techniques applied across various industries and use cases. Health organizations used AIOps to report on COVID data that they collected from a variety of databases in different formats, for example. There are many more opportunities to apply AIOps to core business functions, and eventually engineering functions, too," says Camden Swita, Senior Product Manager at New Relic.

"There will be AIOps technology tailored for every vertical — retail, manufacturing, financial services, utilities, etc. These systems will train on machine data unique to each sector, so they'll offer more specific intelligence and insights," Monika Bhave, Product Manager at Digitate, predicts.

Generative AI Improves AIOps

"Generative AI will make AIOps better as complex orchestrations, automations, etc. will leverage natural language processing or other methods to better interact with what can be complex tooling," says Heath Newburn, Distinguished Field Engineer at PagerDuty.

Natural Language Interfaces

Carlos Casanova from Forrester says, "I see AIOps solutions having much more sophisticated Natural Language Interfaces (NLI) such that lower skilled/trained individuals can perform higher level work. This will hopefully offset some of the displacement that the automation is bringing."

"The next generation of AIOps platforms will offer some form of natural language processing interactions as a way to quickly ramp up a knowledge base that is easily understood by users," Thomas LaRock, Principal Developer Evangelist at Selector, agrees. "This is in contrast to legacy systems which rely on manual help files compiled by subject matter experts and need constant revisions. As AIOps continues to mature and become easier to implement as well as utilize, it will spread to every corner of the office in much the same way the Internet did 30 years ago — gradually, then suddenly."

Variety of Personas

"I see a scenario where the vendor's technologies are able to engage a variety of personas from service delivery, to engineering, to security to business owner," Carlos Casanova from Forrester envisions. "If the data is all the same from across the enterprise, there's no reason why there should be a multitude of tools segmented by persona. I speak to the current state of this from just the technology side in my Three Stages of Preparation For AIOps report. Picking your perspective is the first step."

Read the Forrester blog: Perspective Is Key To Understanding AIOps

Delivering on the Promise

"I think the future of AIOps is people actually doing AIOps. The AIOps space is at the peak of inflated expectations on the hype curve. I don't think people have realized value from AIOps in a meaningful way yet, so the future is about actually applying it. The future of AIOps is about delivering on its own productivity promise," says Bill Lobig, VP Product Management of Automation at IBM.

"AIOps gives the enterprise greater command over its monitored environment so the enterprise can adapt faster and with greater confidence. As enterprises adopt new technologies, rely increasingly on complex digital services to deliver value to customers and seek to connect IT organizations with business outcomes, AIOPs will be an important catalyst for change," Andreas Reiss, Head of Product Management, AIOps and Observability, at Broadcom, concludes. "Where that will lead is tremendously exciting."

Auto-Remediation

Probably the most important ultimate vision, and hope, for AIOps is auto-remediation.

“The movement toward higher levels of automation including automated remediation is accelerating. Typically this can be done on two levels — automated remediation requiring initial IT approval, and automated remediation that occurs on its own, but which should also document its actions in some way. There is definitely a move toward the latter, as both business and technology dynamics are becoming more accelerated,” says Dennis Drogseth, VP at Enterprise Management Associates (EMA).

Go to: Discovering AIOps - Part 9: Auto-Remediation

Pete Goldin is Editor and Publisher of APMdigest

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Discovering AIOps - Part 8: The Future of AIOps

Pete Goldin
Editor and Publisher
APMdigest

The future of AIOps holds significant promise and potential, Ali Siddiqui, Chief Product Officer at BMC predicts. As technology continues to advance, AIOps is likely to play a crucial role in reshaping the landscape of IT operations and business processes. In the era of data-driven decision-making and automation, there will be a significant surge in the demand for AIOps and generative AI. The organizations that can effectively leverage the potential of these will be the ones defining the future landscape of enterprise software.

Overall, AIOps is poised to revolutionize how businesses manage their IT operations, making them more efficient, resilient, and customer-centric, Siddiqui continues. As the technology matures and becomes more widely adopted, it will undoubtedly bring about transformative changes across industries, contributing to improved business outcomes and customer satisfaction.

Start with: Discovering AIOps - Part 1

Start with: Discovering AIOps - Part 2: Must-Have Capabilities

Start with: Discovering AIOps - Part 3: The Users

Start with: Discovering AIOps - Part 4: Advantages

Start with: Discovering AIOps - Part 5: More Advantages

Start with: Discovering AIOps - Part 6: Challenges

Start with: Discovering AIOps - Part 7: The Current State of AIOps

Part 7 of this blog series covered the current state of AIOps. Now, in Part 8, the experts provide their visions for the future of AIOps:

Becoming the Norm

"I think AIOps becomes the norm and not hyped as the latest thing. I'm hopeful that more people quickly see the value and purpose faster so as to enable the adoption of more advanced automation," Carlos Casanova, Principal Analyst at Forrester Research

Helping but Not Replacing ITOPS

"AIOps has definitely changed the way we think about solving problems. In the least, it has allowed us to dream about what may be possible for this still nascent set of capabilities. Because that's what AIOps truly is — a set of capabilities. In the same way monitoring has evolved into a conversation about observability, automation and data (of all types) have evolved into a conversation about AIOps. And since capabilities are the true gateway to positive business outcomes, it is great to see that — according to the most recent SRE survey — reliability practitioners believe AIOPs will make their work easier (52%), while not replacing them (4%)," says Leo Vasiliou, Director of Product Marketing at Catchpoint.

Image removed.

"I believe that most of this technology will be in the form of a very intelligent assistant, rather than replace humans in the loop. I do think it will help eliminate a lot of the groundwork and help teams be more effective and faster in remediating problems," adds Spiros Xanthos, SVP and General Manager of Observability at Splunk.

Complementing Observability

"Observability plays a vital role, working hand-in-hand with AIOps to form a powerful combination, which complements and reinforces each other. An organization equipped with both can leverage AIOps for more intelligent and dynamic monitoring, featuring anomaly detection and advanced root cause analysis," says Siddiqui from BMC.

AIOps for Each Vertical

"People tend to only think about it in the context of alerting or applying CI/CD techniques to IT, but you can also see AIOps techniques applied across various industries and use cases. Health organizations used AIOps to report on COVID data that they collected from a variety of databases in different formats, for example. There are many more opportunities to apply AIOps to core business functions, and eventually engineering functions, too," says Camden Swita, Senior Product Manager at New Relic.

"There will be AIOps technology tailored for every vertical — retail, manufacturing, financial services, utilities, etc. These systems will train on machine data unique to each sector, so they'll offer more specific intelligence and insights," Monika Bhave, Product Manager at Digitate, predicts.

Generative AI Improves AIOps

"Generative AI will make AIOps better as complex orchestrations, automations, etc. will leverage natural language processing or other methods to better interact with what can be complex tooling," says Heath Newburn, Distinguished Field Engineer at PagerDuty.

Natural Language Interfaces

Carlos Casanova from Forrester says, "I see AIOps solutions having much more sophisticated Natural Language Interfaces (NLI) such that lower skilled/trained individuals can perform higher level work. This will hopefully offset some of the displacement that the automation is bringing."

"The next generation of AIOps platforms will offer some form of natural language processing interactions as a way to quickly ramp up a knowledge base that is easily understood by users," Thomas LaRock, Principal Developer Evangelist at Selector, agrees. "This is in contrast to legacy systems which rely on manual help files compiled by subject matter experts and need constant revisions. As AIOps continues to mature and become easier to implement as well as utilize, it will spread to every corner of the office in much the same way the Internet did 30 years ago — gradually, then suddenly."

Variety of Personas

"I see a scenario where the vendor's technologies are able to engage a variety of personas from service delivery, to engineering, to security to business owner," Carlos Casanova from Forrester envisions. "If the data is all the same from across the enterprise, there's no reason why there should be a multitude of tools segmented by persona. I speak to the current state of this from just the technology side in my Three Stages of Preparation For AIOps report. Picking your perspective is the first step."

Read the Forrester blog: Perspective Is Key To Understanding AIOps

Delivering on the Promise

"I think the future of AIOps is people actually doing AIOps. The AIOps space is at the peak of inflated expectations on the hype curve. I don't think people have realized value from AIOps in a meaningful way yet, so the future is about actually applying it. The future of AIOps is about delivering on its own productivity promise," says Bill Lobig, VP Product Management of Automation at IBM.

"AIOps gives the enterprise greater command over its monitored environment so the enterprise can adapt faster and with greater confidence. As enterprises adopt new technologies, rely increasingly on complex digital services to deliver value to customers and seek to connect IT organizations with business outcomes, AIOPs will be an important catalyst for change," Andreas Reiss, Head of Product Management, AIOps and Observability, at Broadcom, concludes. "Where that will lead is tremendously exciting."

Auto-Remediation

Probably the most important ultimate vision, and hope, for AIOps is auto-remediation.

“The movement toward higher levels of automation including automated remediation is accelerating. Typically this can be done on two levels — automated remediation requiring initial IT approval, and automated remediation that occurs on its own, but which should also document its actions in some way. There is definitely a move toward the latter, as both business and technology dynamics are becoming more accelerated,” says Dennis Drogseth, VP at Enterprise Management Associates (EMA).

Go to: Discovering AIOps - Part 9: Auto-Remediation

Pete Goldin is Editor and Publisher of APMdigest

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...