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It's Time to Change the "Channel" to AIOps

Antonio Piraino

The life of a channel partner is challenging. As today's enterprise customers undergo large-scale digital transformation initiatives, the challenges for the channel are many, including the need to stay current with the newest technologies.

Since digital transformation is happening at such a rapid pace based on new, highly complex technologies like multi-cloud, containers and microservice architectures, customers are experiencing more challenges than ever in managing this complexity. However, with every challenge comes an opportunity. So, how can channel partners leverage these market disruptions to open the door to opportunity?

The answer is simple. As enterprise IT challenges expand in both breadth and depth, IT operations teams are being pushed to transition from ITOps to AIOps.

AIOps (Artificial Intelligence for IT Operations) is an innovative framework that combines AI and ML to address operational complexity in IT. By helping customers embrace AIOps, the channel is meeting the growing demand for modern technology solutions that address today's IT complexities. The channel should seize the opportunity around the AIOps market, forecasted to reach over $11 billion by 2023.

So, what's behind AIOps, and why is it such an attractive option for channel partners seeking to capitalize on digital transformation?

IT as a Business Enabler

The draw for channel partners is the immense market value. However, behind these numbers lies a powerful story. As more enterprises rely increasingly on digital infrastructure, IT outages can cost an organization hundreds of thousands of dollars per minute. Therefore, the path to AIOps will not only create IT efficiencies but can also make a sizable impact on the customer experience and bottom line.

Ultimately, AIOps can enable IT teams to predict and prevent outages and remediate issues through automation resulting in reduced downtime, which equates to happier customers.

Additionally, equipping channel partner sales teams with innovative technologies that enable high value business outcomes can lead to more strategic discussions, position partners as a trusted advisor, and yield wider margins.

Complexity of Modern Ops

The scope of data and degree of IT complexity are outpacing the human capacity to collect, organize, and manage information, and therefore to predict, prevent, and remediate IT challenges.

With the advent of VMs, multi-cloud, hybrid IT, containers and microservices, IT operations require advanced capabilities that can operate seamlessly across variegated architectures, work at machine speed, and automate. This presents a strong market opportunity for AI/ML-driven technologies, since legacy tools, designed for the mainframe era, are ill-equipped to work in today's cloud and ephemeral IT environments.

To make matters worse, most legacy monitoring tools also require multiple add-on modules or are nearing end-of-life (i.e., some vendors have announced they will no longer support legacy monitoring suites). Enterprises need more viable alternatives that will keep pace with the dynamics of today's IT landscape. As demand rises and legacy technologies fail to deliver, the channel stands to benefit from the AIOps wave.

The recognition that AIOps is the future of automation and the confluence of market variables represents a massive opportunity, not only for end-users seeking to have their pain points addressed, but also for providers and channel partners seeking to provide robust solutions to further enable enterprise customers now, and well into the future. The time for providers and their partners to embrace AIOps is now.

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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 ...

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It's Time to Change the "Channel" to AIOps

Antonio Piraino

The life of a channel partner is challenging. As today's enterprise customers undergo large-scale digital transformation initiatives, the challenges for the channel are many, including the need to stay current with the newest technologies.

Since digital transformation is happening at such a rapid pace based on new, highly complex technologies like multi-cloud, containers and microservice architectures, customers are experiencing more challenges than ever in managing this complexity. However, with every challenge comes an opportunity. So, how can channel partners leverage these market disruptions to open the door to opportunity?

The answer is simple. As enterprise IT challenges expand in both breadth and depth, IT operations teams are being pushed to transition from ITOps to AIOps.

AIOps (Artificial Intelligence for IT Operations) is an innovative framework that combines AI and ML to address operational complexity in IT. By helping customers embrace AIOps, the channel is meeting the growing demand for modern technology solutions that address today's IT complexities. The channel should seize the opportunity around the AIOps market, forecasted to reach over $11 billion by 2023.

So, what's behind AIOps, and why is it such an attractive option for channel partners seeking to capitalize on digital transformation?

IT as a Business Enabler

The draw for channel partners is the immense market value. However, behind these numbers lies a powerful story. As more enterprises rely increasingly on digital infrastructure, IT outages can cost an organization hundreds of thousands of dollars per minute. Therefore, the path to AIOps will not only create IT efficiencies but can also make a sizable impact on the customer experience and bottom line.

Ultimately, AIOps can enable IT teams to predict and prevent outages and remediate issues through automation resulting in reduced downtime, which equates to happier customers.

Additionally, equipping channel partner sales teams with innovative technologies that enable high value business outcomes can lead to more strategic discussions, position partners as a trusted advisor, and yield wider margins.

Complexity of Modern Ops

The scope of data and degree of IT complexity are outpacing the human capacity to collect, organize, and manage information, and therefore to predict, prevent, and remediate IT challenges.

With the advent of VMs, multi-cloud, hybrid IT, containers and microservices, IT operations require advanced capabilities that can operate seamlessly across variegated architectures, work at machine speed, and automate. This presents a strong market opportunity for AI/ML-driven technologies, since legacy tools, designed for the mainframe era, are ill-equipped to work in today's cloud and ephemeral IT environments.

To make matters worse, most legacy monitoring tools also require multiple add-on modules or are nearing end-of-life (i.e., some vendors have announced they will no longer support legacy monitoring suites). Enterprises need more viable alternatives that will keep pace with the dynamics of today's IT landscape. As demand rises and legacy technologies fail to deliver, the channel stands to benefit from the AIOps wave.

The recognition that AIOps is the future of automation and the confluence of market variables represents a massive opportunity, not only for end-users seeking to have their pain points addressed, but also for providers and channel partners seeking to provide robust solutions to further enable enterprise customers now, and well into the future. The time for providers and their partners to embrace AIOps is now.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...