Operations | Monitoring | ITSM | DevOps | Cloud

When IT operations run smoothly, it’s more likely everything else in the organization will as well. Unfortunately, tech sprawl can make IT environments more prone to issues that hinder end users or, worse, customers. Recent research shows that up to 50% of organizations juggle multiple tools for observability. Too many disparate tools to monitor too many systems and applications create siloes, slowing incident response and resolution times.

Organizations invest heavily in robust systems, talented personnel, and sophisticated tools to ensure smooth operations. Yet, small anomalies often escape attention—minor glitches in applications, occasional lags in processes, or subtle irregularities in performance metrics. These may appear insignificant, but when left unaddressed, they can cascade into significant disruptions, leading to operational inefficiencies, financial losses, and reputational damage.

Data complexity increases every year. The three Vs of data—volume (the amount of data streaming in and out), velocity (the speed of generation, processing, and streaming), and variety (different forms ranging from structured databases and semi-structured XMLs to completely unstructured data as media files)—are also increasing in complexity.

As work environments for entire industries continue to evolve between on-site, remote, and hybrid models, the performance of IT operations (ITOps) teams is more critical than ever. If you need proof, just remember the global impact of the CloudStrike outage. Operations teams must monitor, triage, communicate, and manage incidents 24×7 across all services. SaaS, legacy on-premises, and homegrown tools and systems are all stretching to meet business demand. Customer expectations are ever-increasing.

In a recent webinar, BigPanda CEO Assaf Resnick noted that for the last 15 years, CIOs staked their reputations on how effectively they could move their enterprises to the cloud. Assaf predicts CIOs will focus on integrating generative AI into their enterprises over the next 10 years to deliver tangible business value. IT operations (ITOps) and IT service management (ITSM) offer significant opportunities to incorporate AI to enhance and accelerate their processes.

Enterprise operations monitor various metrics associated with the stability, performance, availability, and other such aspects of business, application, and IT infrastructure. These could be business KPIs such as footfall, checkout time, and sales of the flagship stores. These could be performance metrics such as the response time of business-critical applications. These could be the queue length or enqueue rate of the backbone message queues.

DX Operational Observability (DX O2), a next-generation AIOps and Observability solution from Broadcom, offers two powerful capabilities that generate valuable insights from complex log data. Since DX O2 supports ingestion of logs from a wide variety of sources, the solution offers an enormous opportunity to improve observability and power AIOps.

Now that AI has revolutionized IT forever, what are its implication on IT observability? Typically, IT operations, SREs, and DevOps professionals use IT observability to gain a holistic view of their IT infrastructure. In that pursuit, they used AIOps in several ways. Now, AI has helped IT observability with better anomaly detection, faster root cause analysis, and proactively identifying opportunities to dynamically scale IT to ensure uptime, performance, and security.

Do you feel you’re always playing catch-up with incidents? If so, you’re not alone. As IT environments become more complex, alerts keep piling up, and finding the root cause feels like searching for a needle in a haystack. And ITOps and incident responders are left scratching their heads and wondering: what went wrong? It can be frustrating when you don’t have end-to-end visibility into your systems. This is where observability comes in.