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title: How Netflix Maps Thousands of Microservices in Real-Time
description: Netflix has detailed its internal Service Topology system, which builds and maintains a real-time dependency graph across thousands of microservices. The...
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# How Netflix Maps Thousands of Microservices in Real-Time

**[InfoQ](https://daily.dev/sources/infoq)** · 4 min read · 0 upvotes · 0 comments

## Summary

Netflix has detailed its internal Service Topology system, which builds and maintains a real-time dependency graph across thousands of microservices. The system merges three data sources — eBPF network flow logs, IPC metrics from instrumented services, and aggregated distributed traces — into a single queryable graph. A three-stage aggregation pipeline collapses multi-hop network paths into direct service-to-service edges. The processing stack runs on Apache Pekko Streams with multi-region Kafka consumers, a custom distributed graph store, and a gRPC API with sub-second response requirements. Historical queries use time-window aggregation to avoid snapshot storage costs. Key design lessons include the failure of static dependency maps in fast-deploy environments and the danger of incomplete data leading engineers to wrong conclusions during incidents. Future plans include adding deployment/config change events and using the graph for automated root cause analysis.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.infoq.com/news/2026/06/netflix-microservices-realtime>

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- [How Netflix Scaled Its Real-Time Service Map](https://daily.dev/posts/how-netflix-scaled-its-real-time-service-map-u7xt8lptw) · InfoQ · 2 upvotes · 0 comments
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---

Tags: [#linux](https://daily.dev/tags/linux), [#observability](https://daily.dev/tags/observability), [#microservices](https://daily.dev/tags/microservices), [#distributed-systems](https://daily.dev/tags/distributed-systems), [#service-mesh](https://daily.dev/tags/service-mesh)

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