Modern distributed systems rely on complex networks of interconnected services, creating direct or indirect dependencies that can propagate faults and cause cascading failures. To localize the root cause of performance degradation in these environments, constructing a service dependency graph is highly beneficial. However, building an accurate service dependency graph is impaired by complex routing techniques, such as Network Address Translation (NAT), an essential mechanism for connecting services across networks. NAT obfuscates the actual hosts running the services, causing existing run-time approaches that passively observe network metadata to fail in accurately inferring service dependencies. To this end, this paper introduces Ripple, a run-time system for constructing process-level service dependency graphs. It operates without source code instrumentation and remains resilient under complex network routing mechanisms, including NAT. Ripple implements a non-disruptive method of injecting metadata onto a TCP packet's header that maintains protocol correctness across host boundaries. In other words, if no receiving agent is present, the instrumentation leaves existing TCP connections unaffected, ensuring non-disruptive operation when it is partially deployed across hosts. We evaluated Ripple extensively against three state-of-the-art systems across nine scenarios, involving three network configurations (NAT-free, internal-NAT, external-NAT) and three microservice benchmarks. Ripple was the only approach that performed consistently across networking configurations. With regards to correctness, it performed on par with, or better than, the state-of-the-art with precision and recall values of 100% in the majority of the scenarios.

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