Compare Grafana Cloud vs. IntelliMagic Vision for z/OS

Grafana Labs delivers the leading AI-powered observability platform, built around Grafana—the most widely adopted open source technology for dashboards and visualization. Recognized as a Leader in the 2025 Gartner® Magic Quadrant™ for Observability Platforms, Grafana Labs supports more than 25 million users and thousands of organizations worldwide, from startups to Fortune 500 enterprises. Grafana Cloud is the open observability cloud, designed to help engineering teams observe everything and solve anything. Built on open source, open standards, and open ecosystems, it unifies metrics, logs, traces, and profiles in a single platform for full-stack visibility across applications, infrastructure, and digital experiences. At the core is the open-source LGTM stack: Grafana for dashboards and visualization, Mimir for metrics, Loki for logs, and Tempo for distributed tracing. Native OpenTelemetry and Prometheus support allow teams to ingest telemetry from virtually any environment, while hundreds of integrations connect existing tools and data sources without costly rip-and-replace migrations. Grafana Cloud combines powerful analytics with AI-driven observability. Grafana Assistant helps engineers investigate issues, explore telemetry, and troubleshoot faster. Adaptive Telemetry identifies the data that matters most and aggregates the rest, helping organizations reduce telemetry costs while preserving valuable insights . With solutions for Kubernetes monitoring, application observability, digital experience monitoring, incident response, synthetic monitoring, and performance testing, Grafana Cloud delivers a complete observability platform that scales with your business.

Traditional RMF/SMF data analysis often relies on static reports that are not only costly and challenging to maintain but also take years to master, leading to the creation of knowledge silos within teams. In contrast, IntelliMagic Vision offers customizable reports paired with an exceptional level of built-in z/OS intelligence, enabling analysts to uncover hidden risks, optimize workloads for substantial cost reductions, enhance the contributions of experts, and speed up the training and efficiency of new employees. By leveraging AI-driven analytics, organizations can optimize performance management of z/OS systems, allowing for proactive monitoring and management of the environment, which helps avert disruptions, minimize expenses, and maintain the reliability and availability synonymous with mainframes. Additionally, by providing deep insights into cost drivers such as suboptimal CPU usage, configuration challenges, workload imbalances across hardware, and potential consolidation opportunities, organizations can achieve significant cost savings. This comprehensive approach not only enhances operational efficiency but also fosters a more collaborative and knowledgeable workforce.