Architecture
A service mesh architecture diagram with Istio or Linkerd sidecar proxies handling mTLS encryption, traffic policies, circuit breaking, and distributed tracing across microservices. This template visualizes how a service mesh abstracts networking concerns away from application code, enabling zero-trust communication between services. Essential for teams adopting service mesh infrastructure to improve observability and security.
Full FlowZap Code
Ingress { # Ingress Controller
n1: circle label:"External Traffic"
n2: rectangle label:"TLS Termination"
n3: rectangle label:"Route to Service Mesh"
n1.handle(right) -> n2.handle(left)
n2.handle(right) -> n3.handle(left)
n3.handle(bottom) -> Mesh.n4.handle(top) [label="Enter Mesh"]
}
Mesh { # Service Mesh (Istio/Linkerd)
n4: rectangle label:"Sidecar Proxy Intercept"
n5: rectangle label:"mTLS Encryption"
n6: rectangle label:"Traffic Policy Check"
n7: diamond label:"Circuit Breaker Open?"
n8: rectangle label:"Load Balance Request"
n9: rectangle label:"Return Fallback"
n10: rectangle label:"Collect Telemetry"
n11: rectangle label:"Distributed Tracing"
n4.handle(right) -> n5.handle(left)
n5.handle(right) -> n6.handle(left)
n6.handle(right) -> n7.handle(left)
n7.handle(right) -> n8.handle(left) [label="Closed"]
n7.handle(bottom) -> n9.handle(top) [label="Open"]
n8.handle(bottom) -> Services.n12.handle(top) [label="Forward"]
n9.handle(bottom) -> Services.n18.handle(top) [label="Fallback"]
n10.handle(right) -> n11.handle(left)
}
Services { # Backend Services
n12: rectangle label:"Product Catalog Service"
n13: rectangle label:"Pricing Service"
n14: rectangle label:"Recommendation Engine"
n15: rectangle label:"Response Aggregation"
n16: rectangle label:"Sidecar Proxy Egress"
n17: circle label:"Response to Client"
n18: rectangle label:"Cached Fallback Response"
n12.handle(right) -> n13.handle(left) [label="Get Prices"]
n13.handle(right) -> n14.handle(left) [label="Enrich"]
n14.handle(right) -> n15.handle(left)
n15.handle(right) -> n16.handle(left)
n16.handle(right) -> n17.handle(left)
n18.handle(right) -> n16.handle(left) [label="Stale Data"]
n16.handle(top) -> Mesh.n10.handle(bottom) [label="Metrics"]
}
Why This Workflow?
As microservices scale beyond a dozen services, managing mTLS certificates, traffic policies, retries, and observability at the application level becomes unsustainable. A service mesh moves these concerns into infrastructure-level sidecar proxies, giving platform teams centralized control over service-to-service communication without requiring application code changes.
How It Works
- Step 1: External traffic enters through the ingress controller with TLS termination.
- Step 2: The sidecar proxy intercepts all inbound and outbound traffic for the service.
- Step 3: mTLS encryption is applied automatically between all services in the mesh.
- Step 4: Traffic policies and circuit breaker rules are enforced at the proxy level.
- Step 5: Requests are load-balanced across healthy service instances.
- Step 6: Telemetry data (metrics, traces) is collected by the sidecar and exported to the observability stack.
Alternatives
Implementing mTLS and circuit breaking in application code is error-prone and language-dependent. Managed service meshes like AWS App Mesh or GCP Traffic Director reduce operational overhead. This template helps teams understand the service mesh topology before adopting Istio or Linkerd.
Key Facts
| Template Name | Microservices Service Mesh Architecture |
| Category | Architecture |
| Steps | 6 workflow steps |
| Format | FlowZap Code (.fz file) |
Related templates
Architecture
An ambassador pattern architecture diagram with a local proxy sidecar handling authentication header injection, circuit breaking, retry logic, and metrics collection for outbound requests to external third-party APIs. This template models the ambassador pattern where a helper service running alongside the application offloads cross-cutting concerns for external communication. Useful for teams integrating with unreliable third-party services that need resilience wrappers.
Architecture
A zero trust security architecture diagram with device posture checks, MFA identity verification, risk-based policy decisions, short-lived JWT tokens, micro-segmentation, mTLS encryption, least-privilege access enforcement, and continuous monitoring. This template models the 'never trust, always verify' security paradigm where every request is authenticated and authorized regardless of network location. Essential for security architects implementing modern zero-trust frameworks in cloud-native environments.
Architecture
A microservices API gateway architecture diagram showing request routing, JWT authentication, rate limiting, service discovery, and response aggregation across distributed backend services. This template models the entry point for all client traffic in a microservices ecosystem, enforcing security policies before requests reach internal services. Ideal for platform engineers designing scalable API infrastructure with centralized cross-cutting concerns.
Architecture
A database-per-service architecture diagram where each microservice owns its dedicated data store, with event-driven synchronization via Kafka for cross-service data consistency. This template demonstrates the core microservices data isolation principle, showing how PostgreSQL and MongoDB coexist in a polyglot persistence strategy. Critical for architects enforcing service autonomy while maintaining eventual consistency.
Architecture
A microservices decomposition architecture diagram organized by business capabilities: Identity, Product Catalog, Pricing, and Order Fulfillment, each with independent data stores and APIs. This template shows how to break a monolith into services aligned with business domains, using a Backend-for-Frontend (BFF) pattern for client-specific aggregation. Useful for architects planning domain-driven microservice boundaries.
Architecture
A strangler fig migration architecture diagram showing the incremental replacement of a legacy monolith with new microservices, using a routing layer to split traffic between old and new systems. This template models the proven migration strategy where new features are built as microservices while legacy endpoints are gradually retired. Essential for teams modernizing legacy systems without risky big-bang rewrites.