  Observability is important to ensure the reliability of microservice
applications. These applications are often prone to failures, since they have
many independent services deployed on heterogeneous environments. When employed
"correctly", observability can help developers identify and troubleshoot faults
quickly. However, instrumenting and configuring the observability of a
microservice application is not trivial but tool-dependent and tied to costs.
Practitioners need to understand observability-related trade-offs in order to
weigh between different observability design alternatives. Still, these
architectural design decisions are not supported by systematic methods and
typically just rely on "professional intuition".
  To assess observability design trade-offs with concrete evidence, we advocate
for conducting experiments that compare various design alternatives. Achieving
a systematic and repeatable experiment process necessitates automation. We
present a proof-of-concept implementation of an experiment tool - Observability
eXperiment eNgine (OXN). OXN is able to inject arbitrary faults into an
application, similar to Chaos Engineering, but also possesses the unique
capability to modify the observability configuration, allowing for the
straightforward assessment of design decisions that were previously left
unexplored.
