The why and what we learned from surveying 1,900 engineering teams around their best practices to build, scale, and maintain high availability.

With distributed IT Operations becoming the norm, most enterprise teams struggle with communication and collaboration within and across the organization. Without the proper tools, staying on top of incidents can be challenging, quickly resulting in outages taking longer to resolve. The overall effect: increase in downtime-related costs and decrease in performance and availability of services making mean time to resolve (MTTR) worse.

Nowadays, most organizations are highly dependent on APM technology, but many are shifting to automated monitoring, which is generally referred to as AIOps technology. AIOps is considered the future of operations management for organizations. As we already know, AI is considered the next revolution in the history of mankind. AIOps uses advanced AI for supporting day-to-day operational tasks so the employees don’t need to hassle for no reason.

Artificial Intelligence for IT Operations (or AIOps for short) continues to be a hot topic among developers, SREs, and DevOps professionals. The case for AIOps is especially crucial given the expansive nature of today’s observability efforts across hybrid and multi-cloud environments. As with most observability platforms, it all starts with your telemetry data: metrics, logs, traces, and events.