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Despite the parade of global challenges, an abundance of silver lining can be found by looking at the technological advancements that have emerged in recent years. Particularly those that have transformed how we work by breaking down complex requirements into actionable milestones.

From the growing need for digital workspace transformation and cloud adoption, to more mainstream applications of artificial intelligence and a desire to mitigate future supply chain disruptions — our collective embrace of next-generation technology has ushered in a visible shift in power. One in which IT operations holds a more strategic role as businesses continue to invest in digital transformation technologies.

One of the buzzwords to arise from this shift is "AIOps," or artificial intelligence for IT operations. By combining functionalities from data science and machine learning, like full-stack observability and AI-enabled automation and control, AIOps helps IT operations synthesize the influx of data generated by the technology that's become so central modern success.

For a refresher on AIOps and its value, we recommend starting here:

With that backdrop in mind, here's what's shaping the AIOps landscape. 

A growing demand for AIOps solutions and expertise

In the natural progression of software development solutions, the timing couldn't be better for the widespread adoption of AIOps. Why? One reason is a growing demand for the business outcomes AIOps can deliver, such as:

  • Increased visibility up and down the IT stack
  • Less time spent troubleshooting
  • Issue forecasting, identification and escalation capabilities
  • The ability to reduce, eliminate and triage outages
  • More efficient and cost-effective IT Operations teams
  • Enhanced customer experiences

Another reason, as it has evolved from a technical philosophy into an actual solution, is that AIOps has become more central to an enterprise's ability to scale. Two components are driving this shift:

  • The increasing complexity of data center environments: Over the last four to five years, application complexity has exploded. Once-niche concepts like containerization, hybrid cloud deployments, and abstracted security layers have all become industry norms. That means it's more challenging than ever to see and manage applications across the enterprise.
  • A laser focus on customer experience: In the grand scheme of things, none of the recent advances in observability or automation means much unless they help enhance the end-user experience. AIOps helps enterprises put customers first by making it easier to integrate data, habits, desires, loyalty and daily interactions — all while helping optimize marketing strategies and build personalized journeys.

Despite the growing importance of AIOps, businesses are finding there's a limit to what off-the-shelf AIOps solutions can deliver on their own. When used as a mere tool, most organizations will struggle to extract the full value of AIOps — a technology best viewed as a means to an end rather than an end-state itself.

The missing component in this equation is expertise. To get the most out of AIOps, companies will find they need to invest in AIOps as a discipline rather than as a tool. This means a team of experts who understands how to strategically orchestrate AIOps into a sustainable system that optimizes the technical platform.

As such, WWT foresees a growing demand for experts who understand the underlying architecture required to generate AIOps' promised business outcomes.

Full-stack observability becomes a key catalyst to AIOps scalability

Another term often heard in conjunction with AIOps is "FSO," or full-stack observability. FSO has cemented its rightful place as one of the leading catalysts driving organizations to modernize their approach to application development.

As the moniker suggests, FSO promises the real-time ability to see and manage everything in your modern data center stack, including applications, compute, storage, networking, security, cloud and more.

Introducing FSO capabilities to the traditional software development lifecycle — capabilities like comprehensive metrics, events and correlated real-time data — can help enterprises accelerate AIOps adoption. It can also help unlock new levels of interoperability and unification, from initial coding all the way through the underlying infrastructure modernization needed to take full advantage of today's digital technologies.

FSO's comprehensive observability, action and insight platform can also help organizations looking to scale better understand how various actions impact their business goals.

Ultimately, FSO can help organizations enable full, enterprise-scale AIOps and stay a step ahead of the competition in delivering solutions to market.

An escalating shift to cloud-native application architectures

Since the COVID-19 pandemic, the unprecedented spike in cloud adoption has been well documented. As such, there's been an increased interest in SaaS cloud service models as well as hybrid cloud deployment models.

With increased adoption levels expected to persist, it's no surprise that cloud will play a role of growing importance in the next generation of AIOps solutions.

Despite some historical pushback to the notion, more platforms and providers are adopting cloud-native application architectures. This shift should make it easier for organizations to adopt AIOps-friendly approaches to application development. For example, incorporating microservices and containerization can speed and streamline how dev teams build, test, run and update applications for the business and customers.

It should be noted that to be successful, this shift to cloud-native architectures will likely require a corresponding shift in both business and cultural structures.

AIOps plays a more visible role in enhancing security capabilities

Finally, AIOps is playing a greater role in improving cybersecurity posture, particularly from an end-user perspective.

The main reason for this stems from a host of useful AIOps features, including threat intelligence analysis, open metrics, security event management, endpoint behavior modeling and more. Augmented by AIOps' AI/ML-based automation capabilities, these features offer an extra layer of contextualization that can help experts identify and isolate potential security breaches. When network administrators have the visibility needed to know what a "normal baseline" looks like across an entire network , it's that much easier to identify and fix red flags.

From an end-user point of view, this is a big deal. Why? Because AIOps enables security breaches to be dealt with before they have a chance to cause harm. This signals a potentially huge improvement to the customer experience.

As companies increasingly embrace AIOps to bolster their cybersecurity capabilities, they'll want to ensure their IT teams have the AIOps and security skillsets needed to achieve this alignment. They'll also want to make sure the silos between IT Ops and business and cybersecurity leaders don't slow the organization from taking advantage of the security benefits of modern AIOps solutions.

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