Modern Observability and Automation: A Strategy for Enterprise Transformation
Organizations with the right level of observability can gain insight into user experiences and the inner workings of their complex environments.
While IT organizations have traditionally monitored systems and applications through metrics, traces and logs, these approaches have not often been linked. A modern operations environment evolves from availability and applications performance monitoring to include observability. An effective observability approach built on a set of principles that leverage people, process, and technology to gather data will allow organizations to gain insight into the behavior and performance of complex systems by bringing together data from disparate systems, services, and applications, discovering and linking dependencies. This is increasingly important in the context of modern distributed and cloud-based architectures, where applications are composed of numerous interconnected components running across different environments.
Ultimately, this part of a modern operation enables positive business outcomes–and leads to proactive conversations.
But this all depends on one critical element. Automation. An organization’s ability to leverage its data to improve performance, availability, and other key business metrics is crucial. To get the best results, observability should be integrated into development and automated deployment pipelines, rather than added after.
Organizations looking to build or transform their observability capabilities require a solid foundation built on industry-leading AI-powered automation capabilities. IBM offers a deep portfolio of IBM offers a deep portfolio of industry-leading, AI-powered observability solutions that integrate automation at their core.
Read our new guide Modern Observability and Automation: A Strategy for Enterprise Transformation.
