Service mesh, communication patterns, and event-driven flows — microservice architecture diagrammed as code. AI-generated, version-controlled, reviewable.
Diagrams that capture the complexity of distributed systems.
Visualize how services connect through the mesh. Map sidecars, proxies, and communication paths.
Document sync vs async, request/reply vs pub/sub, and event-driven flows between services.
Map event producers, consumers, topics, and message queues. See how events propagate through the system.
Understand which services depend on which. Identify critical paths, single points of failure, and blast radius.
Diagram distributed transaction flows. Show compensation steps, failure handling, and state machines.
Describe your microservice architecture in English. Cybewave generates the diagram code instantly.
From microservice description to architecture diagram in three steps.
List your microservices, their responsibilities, communication patterns (REST, gRPC, events), and data stores. Mention specifics like Kafka topics, Redis caches, or API gateways and the AI tailors the output.
Cybewave produces a service topology map showing all services and their dependencies, sequence diagrams for key flows across service boundaries, and component diagrams detailing internal structure of critical services.
As you add services, split existing ones, or introduce event-driven patterns, update the Mermaid code in the same PR. The diagram always reflects the current service landscape, not a snapshot from the initial design.
Critical moments in microservice development where visual documentation prevents costly mistakes.
When splitting a monolith or extracting a new service, diagram the proposed service boundaries, the APIs between them, and the data that needs to migrate. A visual decomposition plan prevents the common mistake of creating services that are too chatty or too tightly coupled.
In event-driven architectures with Kafka, RabbitMQ, or SNS/SQS, request flows are non-obvious. A sequence diagram showing which service publishes which event, who consumes it, and what side effects occur makes debugging and designing new flows dramatically easier.
Visualize your Istio, Linkerd, or Envoy configuration as a topology diagram. Show traffic routing rules, circuit breakers, retry policies, and mTLS boundaries. When networking issues arise, the diagram tells the on-call engineer exactly where to look.
Distributed transactions across services need careful orchestration. Diagram the saga steps, compensation actions for each failure point, and the eventual consistency guarantees. Reviewers can trace every failure scenario before the pattern is implemented.
When multiple teams own different services, a dependency map shows which teams need to coordinate for a given feature. Show the API contracts between services owned by different teams and highlight where changes require cross-team PRs or breaking change negotiations.
When latency increases, diagram the full request path with expected latencies at each hop. Identify where N+1 calls happen, which services are synchronous bottlenecks, and where adding caching or async processing would have the most impact.
A monolith is complex but contained — you can grep the codebase to understand it. Microservices distribute that complexity across network boundaries, team boundaries, and often across different programming languages and data stores. The system becomes impossible to hold in one person's head.
This is why microservice architectures fail without good documentation. A developer adding a feature that touches three services needs to understand the contracts between them, the event flows that trigger side effects, and the failure modes at each boundary. Without a current architecture diagram, they either spend days reading code across repositories or make assumptions that lead to production incidents.
Code-based diagrams are particularly valuable for microservices because the architecture changes frequently. Services are added, split, merged, and deprecated as the system evolves. A diagram that lives in Git and is updated in the same PR that changes service boundaries ensures the documentation evolves at the same pace as the architecture itself.
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