Take a closer look at your options for leveraging AI-powered observability, and see which one—or which combination of options—is the right fit for your organization.

Grafana is an open-source analytics and monitoring platform that allows users to visualize and analyze metrics from various data sources. The Grafana blog covers topics such as data visualization, monitoring best practices, and new features in Grafana software. Developers and data engineers can learn how to leverage Grafana for monitoring infrastructure, analyzing performance metrics, and creating interactive dashboards for data-driven decision-making.

Grafana Labs

A framework for choosing between building, buying, or using open source for AI-powered observability. The three options are framed as lanes: building in-house offers maximum control but requires significant ongoing investment; open source provides a flexible foundation but leaves teams responsible for AI orchestration, prompt design, and evaluation; and managed solutions like Grafana Cloud offer out-of-the-box AI capabilities including Grafana Assistant and Assistant Investigations. The post argues these aren't mutually exclusive—Grafana's ecosystem allows teams to combine approaches, shift strategies over time, and extend managed AI with custom agents and internal knowledge sources via open APIs.

Build, buy, or open source? Understanding your options with Grafana’s AI-powered observability

Lane 1. Build: Maximum control, maximum overhead

Lane 2. Open source: Flexible and powerful, but not a complete AI solution

Lane 3. Buy: Out-of-the-box intelligence, tuned to your context

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