Service Mesh

Controls the flow of requests between services with fine-grained routing rules, independent of application code.

• Load Balancing: Distributes requests using algorithms like round-robin, least connections, or ring hash.
• Traffic Splitting: Enables canary deployments and A/B testing by routing a percentage of traffic to different service versions.
• Circuit Breaking: Stops cascading failures by ejecting unhealthy hosts from the load balancing pool based on connection limits or error rates.
• Fault Injection: Deliberately introduces delays or aborts to test the resilience of the application without modifying source code.

Generates detailed telemetry data for every service-to-service interaction without requiring developers to instrument application code.

• Distributed Tracing: Injects headers to propagate a trace context across service boundaries, allowing a single request to be visualized across dozens of microservices.
• Metrics Collection: Automatically exports latency, request volume, and error rate statistics for each service endpoint.
• Access Logging: Records every network call with metadata such as source, destination, and response code, providing a full audit trail.

Enforces authentication, authorization, and encryption policies transparently at the network level.

• Mutual TLS (mTLS): Automatically provisions and rotates certificates to encrypt all service-to-service traffic and verify the identity of both the client and server.
• Fine-Grained Authorization: Applies role-based access control (RBAC) policies to permit or deny specific service-to-service requests based on attributes like HTTP method or path.
• Identity Provisioning: Assigns a cryptographically verifiable identity to each service instance, often using a SPIFFE-compliant framework, enabling zero-trust networking.

Implements patterns that allow the system to remain responsive in the face of partial failures.

• Retries with Backoff: Automatically re-attempts failed requests with exponential backoff and jitter to avoid thundering herd problems.
• Timeouts: Enforces maximum wait durations for requests to prevent resource exhaustion from hung downstream services.
• Outlier Detection: Passively monitors host behavior and ejects endpoints that exhibit elevated error rates, a pattern also known as passive health checking.

A service mesh is typically implemented using a sidecar proxy pattern.

• Data Plane: Composed of lightweight proxies (like Envoy or Linkerd-proxy) deployed alongside each service instance. These proxies intercept all network traffic and enforce policies.
• Control Plane: The centralized management layer that provides the API and configuration interface for operators. It programs the data plane proxies with routing rules, security policies, and discovery information.
• Service Discovery: The control plane integrates with the platform's service registry to dynamically populate the list of available endpoints for each proxy.

Several production-grade service mesh implementations exist, each with distinct architectural trade-offs.

• Istio: A feature-rich mesh with an Envoy-based data plane and a powerful control plane. It is extensible via WebAssembly and deeply integrated with Kubernetes.
• Linkerd: A CNCF graduated project focused on operational simplicity and minimal resource overhead, using a purpose-built Rust proxy.
• Consul Connect: Part of the HashiCorp ecosystem, it leverages a built-in service discovery mechanism and can operate across Kubernetes and virtual machine environments.
• Kuma: A universal control plane built on Envoy that supports both Kubernetes and traditional VM-based deployments.