Context: With the adoption of cloud computing and the evolution of IT and software engineering practices, observability, the ability to systematically measure and monitor software systems, becomes a growing concern. Cloud computing is very heterogeneous, and thus creating, maintaining, and observing systems built on it requires integration of multiple tools. Open source software (OSS) tooling emerged as a de-facto standard in multiple areas, including cloud observability. The ecosystem formed by OSS observability tooling is large and often difficult to navigate. Objective: The main goal of this paper is to present the OSS Ecosystem formed by cloud computing observability tooling, by providing an overview of the main tools and identifying trends on their integration. Method: We searched the literature for studies on cloud observability and used an automated named-entity recognition (NER) method to extract candidate observability tools from abstracts. We selected the OSS observability tools according to well-defined criteria. Following this, we used keyword matching on the tools’ source codes, revealing integration code, documentation, and other types of relations. Results: As a result, we found 45 OSS observability tools and derived quantitative measures on their relations to one another. The tools serve different roles in observability stacks, with our results serving as a proxy measure on how strongly they relate to one another. Conclusion: We present an overview of different tools, how frequently they appear, their functionality, and a visualization of their relations. Some trends are identified, such as the centrality of some tools (e.g. Prometheus), common stacks (e.g. ELK, TICK), and outliers (Thingspeak). We discuss topics such as measuring relations, standardization, proprietary lock-in, among others.