Operations | Monitoring | ITSM | DevOps | Cloud

Modern business functions are based on the promise of smooth and seamless experience, without the need for downtime or long waits for backend processes to finish. For such digital operations, timely execution of business processes—like financial closings, order fulfilment, report generation—is non-negotiable.

As organizations rely on increasingly complex IT infrastructures, incident management often turns into a constant cycle of alerts, escalations, and fixes. While reactive responses may keep operations running, they rarely address the deeper systemic issues that slowly erode performance. Recurring incidents, silent failures, and hidden patterns are usually symptoms of unresolved root causes that traditional approaches struggle to uncover.

Cloud has become the backbone of digital enterprises, but managing its cost footprint is proving increasingly difficult. With multiple providers, diverse pricing models, and ever-changing workloads, organizations often find themselves facing spend leakage and unanticipated overruns. The stakes are high—not only in terms of IT budgets but also in ensuring cloud resources deliver maximum business value.

Incident management is a high-stakes function. IT operations teams and SRE teams may play different roles, but when a priority incident surfaces, it is often all-hands-on-deck to ensure it is resolved in minimal time. That’s because of the high impact of incidents-if not resolved in time, they can cascade and impact other IT systems, leading to downtime, business disruptions, monetary losses, and impacting brand value, compliance, and regulatory rules.

The IT landscape in enterprises today is complex, hybrid and dynamic and the complexity is also increasing rapidly due to increased containerization, microservice-based apps, and the overall scale of digital operations.

In the previous post, What is OpenTelemetry?, we went over the What, Why, and the How of OpenTelemetry. We also went over the telemetry data lifecycle (data generation à collection à storage à usage) and how telemetry data (MELT) could be put to use to troubleshoot a representative web application scenario.