IT organizations are facing enormous operational challenges that must be overcome to satisfy business objectives and meet end-user needs. They not only must meet requirements for availability, capacity, performance, and security but alsomust drive operational efficiency and control costs.Growth in the number of applications and workloads is generating increasing volumes of telemetry data, making it difficult to monitor, track, analyze, and optimize the performance and health of today's complex infrastructures across servers, storage, and networks. The demands of remote work and digital commerce mean that IT must support "always on" operations, with speed and at scale. Ensuring, delivering, and maintaining high-quality service levels in these dynamic and complex environments require intelligence to detect service anomalies, predict and prevent interruptions and outages, speed troubleshooting and repair when needed, and gain insights and recommendations to improve infrastructure performance.
Traditional approaches to optimizing performance and availability for infrastructure and applications are frequently based on tools that read and interpret telemetry data including logs, metrics, and traces; perform some simple analysis; and display graphical information on a series of dashboards for operations personnel to visually interpret and troubleshoot. Often such tools tend to be siloed, aimed at specific operational roles or specific infrastructure technologies. Many of the problem-solving capabilities of these tools come from operator experience and domain knowledge. As infrastructure and applications become more complex and operate at higherscale, with huge volumes of telemetry data, achieving successful outcomes with simple monitoring tools and multiple dashboards becomes increasingly difficult.
