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Why Enterprises Must Consider AIOps

Gareth Smith
Eggplant

The demand for AIOps has accelerated as organizations struggle with the increased complexities of IT systems, a disparate workforce, and the explosive growth of operational data. Gartner even recently stated that "there is no future of IT operations that does not include AIOps." For the modern enterprise, relying solely on traditional analysis or humans results in missed opportunities and potentially increases risk.

So, what is AIOps?

It's about leveraging intelligent technologies, including AI and ML, to automate an organization's operations to provide a real-time understanding of issues in order to improve the reliability and quality of services. In addition, once adopted, it minimizes the time spent firefighting.

Another key benefit of AIOps is that it removes the barriers and wasted cost of siloed IT operations and provides enterprises with a platform to increase agility incrementally.

By using insights from uncorrelated data across systems, organizations can predict and fix operational problems before they occur. As a result, enterprises can reduce the time spent resolving these problems along with minimizing the impact. In addition, the intelligent technologies provide data-driven insights that help inform better decision making and improve the quality of services. By utilizing the power of AI and ML, this ultimately becomes fully automated and should prevent major outages from occurring.

Starting Your DevOps Journey

When it comes to starting your AIOps journey, it's best to focus on visibility. First, organizations should use the insights to hone in on critical operational indicators such as reliability, quality, mean time to resolution, and identify the major stumbling blocks.
Then IT teams should plan changes around those vital areas with additional, more proactive, AIOps capabilities while continually using the data generated to demonstrate progress and validate the shift to AIOps.

One of the advantages of AIOps adoption is that you can do it incrementally. With this approach, the insights initially uncovered can highlight otherwise unknown problems without disruption. Then augment the visibility aspects with more automation and more powerful analytics across a more comprehensive set of data sources. This allows the enterprise to become familiar with AIOps while proving its value before rolling it out further.

At the same time, there are some common pitfalls that enterprises need to be cognizant of. For example, the common problem of inertia with IT teams also applies to AIOps. Existing IT teams are overstretched and lack the time to investigate new technologies and initiatives, especially ones with more advanced AI and ML capabilities. However, given the automation and efficiency benefits of AIOps, this incremental migration should be seen as a good investment for a much-improved result.

As Abraham Lincoln put it, "give me six hours to chop down a tree and I will spend the first four sharpening the axe."

Gareth Smith is General Manager at Eggplant

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Why Enterprises Must Consider AIOps

Gareth Smith
Eggplant

The demand for AIOps has accelerated as organizations struggle with the increased complexities of IT systems, a disparate workforce, and the explosive growth of operational data. Gartner even recently stated that "there is no future of IT operations that does not include AIOps." For the modern enterprise, relying solely on traditional analysis or humans results in missed opportunities and potentially increases risk.

So, what is AIOps?

It's about leveraging intelligent technologies, including AI and ML, to automate an organization's operations to provide a real-time understanding of issues in order to improve the reliability and quality of services. In addition, once adopted, it minimizes the time spent firefighting.

Another key benefit of AIOps is that it removes the barriers and wasted cost of siloed IT operations and provides enterprises with a platform to increase agility incrementally.

By using insights from uncorrelated data across systems, organizations can predict and fix operational problems before they occur. As a result, enterprises can reduce the time spent resolving these problems along with minimizing the impact. In addition, the intelligent technologies provide data-driven insights that help inform better decision making and improve the quality of services. By utilizing the power of AI and ML, this ultimately becomes fully automated and should prevent major outages from occurring.

Starting Your DevOps Journey

When it comes to starting your AIOps journey, it's best to focus on visibility. First, organizations should use the insights to hone in on critical operational indicators such as reliability, quality, mean time to resolution, and identify the major stumbling blocks.
Then IT teams should plan changes around those vital areas with additional, more proactive, AIOps capabilities while continually using the data generated to demonstrate progress and validate the shift to AIOps.

One of the advantages of AIOps adoption is that you can do it incrementally. With this approach, the insights initially uncovered can highlight otherwise unknown problems without disruption. Then augment the visibility aspects with more automation and more powerful analytics across a more comprehensive set of data sources. This allows the enterprise to become familiar with AIOps while proving its value before rolling it out further.

At the same time, there are some common pitfalls that enterprises need to be cognizant of. For example, the common problem of inertia with IT teams also applies to AIOps. Existing IT teams are overstretched and lack the time to investigate new technologies and initiatives, especially ones with more advanced AI and ML capabilities. However, given the automation and efficiency benefits of AIOps, this incremental migration should be seen as a good investment for a much-improved result.

As Abraham Lincoln put it, "give me six hours to chop down a tree and I will spend the first four sharpening the axe."

Gareth Smith is General Manager at Eggplant

Hot Topics

The Latest

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

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In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...