Anyone who’s worked in a customer-facing role knows the pressure to find the correct answers quickly. Emotions are high when something is broken, or there’s an outage. The customer is angry. You’re stressed. And your boss is watching and wondering why the problem hasn’t been fixed. You need to troubleshoot quickly and provide the right information ASAP. As a support professional, you want to give customers and stakeholders the best possible experience.

By breaking down the silos between observability, IT operations, and service management, teams can improve service delivery and enhance IT incident management. However, this is more easily said than done. The average BigPanda customer uses more than 20 observability and monitoring data sources. Combining mountains of alert data with legacy event management systems can make it almost impossible to sift through the noise to find the most important alerts.

Advances in generative AI are rapidly transforming the IT operations landscape. According to Enterprise Strategy Group, 85% of organizations use or plan to deploy AI across many functional areas, including ITOps. AIOps platforms can apply advanced GenAI to quickly identify an incident’s root cause, impact, and recommend steps to resolution. When fed the correct information, AIOps gives IT teams immediate access to context-rich insights.

Many organizations face increased costs from excess noise, manual workflows, and long outage times. These inefficiencies negatively impact budget, service uptime, and, ultimately, customer satisfaction. With effective use of AI, you can give operators the most relevant, full-context incident data, providing a greater understanding of an incident within seconds.

Most IT leaders realize that automating repetitive, low-level incident response actions is vital to multiple benefits. To name just a few, these include: In IT, incident response refers to addressing any event that disrupts normal service, application, security operation, or performance. Using AI and machine learning, automation addresses incident analysis, detection, investigation, triage, and response. The question is often identifying where to start or the best approach.

Network topology describes how a network‘s nodes, connections, and devices physically arrange and interconnect, as well as how they communicate. The arrangement or configuration of a network’s components plays a crucial role in ensuring smooth ITOps with minimum downtime. Any issues in the network can disrupt operations, leading to potentially dire consequences. To prevent this, you need to understand your network functionality and structure.

Lack of communication between IT operations and ITSM teams results in data silos. And data silos make it challenging, if not impossible, to solve problems efficiently. One-third of ITOps professionals say that gathering business context is the biggest challenge to effective incident response and management, according to EMA Research.

The lines between IT service management (ITSM) and AIOps are blurring. The Gartner Hype Cycle for ITSM, 20241 discusses this exciting convergence. Traditionally, ITSM has focused on structured processes and best practices. AIOps brings valuable new capabilities to service management, including automation, correlation, machine learning, and real-time insights. This convergence augments established ITSM frameworks and processes rather than replace them.