Microservice Traffic Mesh
Interactive simulation of a microservice topology with real-time request routing, circuit breaker patterns, and health-based load balancing. Models the distributed systems principles applied at Rapid7 and Kiwibank for high-availability platforms.
Initialization • Click 'Initialize Simulation' to start the mesh visualization Operation • Watch requests (particles) flow between services in real time • Click any service node to toggle it offline — the circuit breaker engages • Click an offline node again to bring it back online • Adjust the 'Traffic Rate' slider to increase or decrease request volume Observation • Green nodes are healthy, yellow nodes are degraded, red nodes are offline • When a node goes down, traffic automatically reroutes to healthy peers • The metrics panel shows live throughput, latency, and error rate
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The Problem: Cascading Failures
In a microservice architecture, a single failing service can bring down the entire system. At Rapid7, our threat intelligence platform comprised dozens of services — if the enrichment service stalled under load, requests backed up through the ingestion pipeline, killing the entire data flow. At Kiwibank, a failing downstream API could cascade through the banking middleware, triggering OpsGenie alerts at 3 AM.
The solution is resilience engineering: circuit breakers, health-aware routing, and graceful degradation.
Circuit Breaker Pattern
This simulation implements the Circuit Breaker pattern (popularized by Michael Nygard in Release It!):
- Closed (Normal): Requests flow through to the downstream service. Failures are counted.
- Open (Tripped): After a failure threshold, the circuit “opens” — all requests are immediately rejected or rerouted, protecting the caller from a known-bad dependency.
- Half-Open (Probe): Periodically, a single request is allowed through. If it succeeds, the circuit closes and traffic resumes.
Health-Aware Load Balancing
Rather than naive round-robin, production systems route traffic based on health scores. Each service in this simulation reports its current state, and the mesh router preferentially sends requests to healthy nodes. This models the weighted load balancing used in Kubernetes Endpoints and AWS ALB target groups.
Real-World Application
- Rapid7: On-call production incident response for SaaS threat intelligence — circuit breakers were critical for isolating failures in the microservice mesh.
- Kiwibank: .NET API services deployed on AWS with Kubernetes — health checks and readiness probes determined routing decisions.
- GoTech: Migration from PHP monolith to Node.js microservices with Express, Redis, and RabbitMQ — service discovery and health monitoring were foundational.
References
[1] Nygard, M.T. (2018). Release It! Design and Deploy Production-Ready Software, 2nd Edition. Pragmatic Bookshelf.
[2] Newman, S. (2021). Building Microservices, 2nd Edition. O’Reilly Media.
[3] Burns, B. (2018). Designing Distributed Systems. O’Reilly Media.