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AI May Benefit from Data Centers, but Data Centers Need Observability

Ranjan Goel
VP of Product
LogicMonitor

AI continues to shape the digital landscape and its explosion isn't slowing down anytime soon. Businesses innovate and unveil new technologies daily. In fact, we found 81% of enterprises plan to increase AI investments this year, focusing on predictive analytics, automation and anomaly detection.

This surge in AI adoption amplifies the need for robust data center infrastructure to handle the terabytes of data being generated daily. Fortunately, progress is already underway. The US government recently announced a $500 billion joint initiative in collaboration with industry leaders such as OpenAI, SoftBank, and Oracle to expand and modernize data center capabilities across the nation, ensuring the infrastructure can keep pace with AI's rapid growth.

Still, as much as AI will benefit from data centers, data centers need observability solutions to ensure resiliency and sustainability so businesses can operate to their full potential and provide seamless experiences to customers.

Why Observability Matters

Businesses have insurmountable amounts of data across IT infrastructures, and although digital transformation started over 20 years ago, many organizations are still in the process of transferring that data from on-premise solutions to the cloud, which — without the right tools in place — is a recipe for disaster of its own.

By implementing an observability solution, IT teams are given a single pane of glass view into their systems to ensure they remain up and running to reduce downtime — like the real-life scenario we saw play out with the Crowdstrike incident. With observability tools, anomalies within IT infrastructure can be detected faster, so time, resources, and money aren't lost. Coupled with next-generation AIOps tools that deliver actionable insights in order to remediate problems, observability solutions are a one-stop-shop for resilience. Multiple teams from L1 to L2 operations staff can now quickly collaborate during an incident with the same context and data all nicely summarized and root-cause identified through Agentic AI.

As IT practitioners, we know that it takes one small glitch in the system to completely flip business operations on a head, which is why these solutions are so important. Without observability, we might as well be flying blind in day-to-day operations, spending countless hours trying to rectify minor problems that cause gigantic risks. But with observability, the mean-time to resolution (MTTR) is significantly lowered allowing us to focus on mission critical work that's meaningful to our organizations at large.

Observability's Transformative Impact on Data Centers

With 68% of organizations leveraging AI tools for anomaly detection, root cause analysis, and real-time threat detection, a lot of data is being processed, and that data needs a home. Enter: data centers.

Observability comes into play to ensure those data centers remain up and running in the event of an error or software failure. If a data center were to experience an IT disruption, any system or AI that is connected to it may also fail in the process. The downtime could result in lost access to electronic records, decreased employee productivity, revenue loss, damaged customer trust and reputation, and potential compliance violations due to the service disruption.

However, the good news is that 59% of organizations that have implemented observability solutions report exceeding ROI expectations, with faster response times, improved uptime, and enhanced decision-making driving measurable business value.

Observability is a data center's best friend and it's imperative that as data centers increase in size and complexity, the investment stretches into sustainable and resilient observability solutions as well.

What's Next

The role of AI within IT operations is evolving rapidly with the advances in technology and acceptance of AI tools by operations staff. In the next 6 months, Agentic AI-driven observability and AIOps tools will become a must-have for any data center, thus improving their availability and bringing efficiency to the operations.

Ranjan Goel is VP of Product at LogicMonitor

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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 ...

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AI May Benefit from Data Centers, but Data Centers Need Observability

Ranjan Goel
VP of Product
LogicMonitor

AI continues to shape the digital landscape and its explosion isn't slowing down anytime soon. Businesses innovate and unveil new technologies daily. In fact, we found 81% of enterprises plan to increase AI investments this year, focusing on predictive analytics, automation and anomaly detection.

This surge in AI adoption amplifies the need for robust data center infrastructure to handle the terabytes of data being generated daily. Fortunately, progress is already underway. The US government recently announced a $500 billion joint initiative in collaboration with industry leaders such as OpenAI, SoftBank, and Oracle to expand and modernize data center capabilities across the nation, ensuring the infrastructure can keep pace with AI's rapid growth.

Still, as much as AI will benefit from data centers, data centers need observability solutions to ensure resiliency and sustainability so businesses can operate to their full potential and provide seamless experiences to customers.

Why Observability Matters

Businesses have insurmountable amounts of data across IT infrastructures, and although digital transformation started over 20 years ago, many organizations are still in the process of transferring that data from on-premise solutions to the cloud, which — without the right tools in place — is a recipe for disaster of its own.

By implementing an observability solution, IT teams are given a single pane of glass view into their systems to ensure they remain up and running to reduce downtime — like the real-life scenario we saw play out with the Crowdstrike incident. With observability tools, anomalies within IT infrastructure can be detected faster, so time, resources, and money aren't lost. Coupled with next-generation AIOps tools that deliver actionable insights in order to remediate problems, observability solutions are a one-stop-shop for resilience. Multiple teams from L1 to L2 operations staff can now quickly collaborate during an incident with the same context and data all nicely summarized and root-cause identified through Agentic AI.

As IT practitioners, we know that it takes one small glitch in the system to completely flip business operations on a head, which is why these solutions are so important. Without observability, we might as well be flying blind in day-to-day operations, spending countless hours trying to rectify minor problems that cause gigantic risks. But with observability, the mean-time to resolution (MTTR) is significantly lowered allowing us to focus on mission critical work that's meaningful to our organizations at large.

Observability's Transformative Impact on Data Centers

With 68% of organizations leveraging AI tools for anomaly detection, root cause analysis, and real-time threat detection, a lot of data is being processed, and that data needs a home. Enter: data centers.

Observability comes into play to ensure those data centers remain up and running in the event of an error or software failure. If a data center were to experience an IT disruption, any system or AI that is connected to it may also fail in the process. The downtime could result in lost access to electronic records, decreased employee productivity, revenue loss, damaged customer trust and reputation, and potential compliance violations due to the service disruption.

However, the good news is that 59% of organizations that have implemented observability solutions report exceeding ROI expectations, with faster response times, improved uptime, and enhanced decision-making driving measurable business value.

Observability is a data center's best friend and it's imperative that as data centers increase in size and complexity, the investment stretches into sustainable and resilient observability solutions as well.

What's Next

The role of AI within IT operations is evolving rapidly with the advances in technology and acceptance of AI tools by operations staff. In the next 6 months, Agentic AI-driven observability and AIOps tools will become a must-have for any data center, thus improving their availability and bringing efficiency to the operations.

Ranjan Goel is VP of Product at LogicMonitor

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 ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

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

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

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 ...

Image
Broadcom

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 ...