ServiceMesh案例

      服务网格（Service Mesh）是致力于解决服务间通讯的基础设施层。它负责在现代云原生应用程序的复杂服务拓扑来可靠地传递请求。实际上，Service Mesh 通常是通过一组轻量级网络代理（Sidecar proxy），与应用程序代码部署在一起来实现，而无需感知应用程序本身。

数据面

• Service discovery: What are all of the upstream/backend service instances that are available?
• Health checking: Are the upstream service instances returned by service discovery healthy and ready to accept network traffic? This may include both active (e.g., out-of-band pings to a /healthcheck endpoint) and passive (e.g., using 3 consecutive 5xx as an indication of an unhealthy state) health checking.
• Routing: Given a REST request for /foo from the local service instance, to which upstream service cluster should the request be sent?
• Load balancing: Once an upstream service cluster has been selected during routing, to which upstream service instance should the request be sent? With what timeout? With what circuit breaking settings? If the request fails should it be retried?
• Authentication and authorization: For incoming requests, can the caller be cryptographically attested using mTLS or some other mechanism? If attested, is the caller allowed to invoke the requested endpoint or should an unauthenticated response be returned?
• Observability: For each request, detailed statistics, logging, and distributed tracing data should be generated so that operators can understand distributed traffic flow and debug problems as they occur.

控制面

• The human: There is still a (hopefully less grumpy) human in the loop making high level decisions about the overall system.
• Control plane UI: The human interacts with some type of UI to control the system. This might be a web portal, a CLI, or some other interface. Through the UI, the operator has access to global system configuration settings such as deploy control (blue/green and/or traffic shifting), authentication and authorization settings, route table specification (e.g., when service A requests /foo what happens), and load balancer settings (e.g., timeouts, retries, circuit breakers, etc.).
• Workload scheduler: Services are run on an infrastructure via some type of scheduling system (e.g., Kubernetes or Nomad). The scheduler is responsible for bootstrapping a service along with its sidecar proxy.
• Service discovery: As the scheduler starts and stops service instances it reports liveness state into a service discovery system.
• Sidecar proxy configuration APIs: The sidecar proxies dynamically fetch state from various system components in an eventually consistent way without operator involvement. The entire system composed of all currently running service instances and sidecar proxies eventually converge.

  目前行业流行数据planes与控制planes:

• Data planes: Linkerd, NGINX, HAProxy, Envoy, Traefik
• Control planes: Istio, Nelson, SmartStack

场景

另一案例是：

基于 Istio+Envoy 的方案：

• 数据面以 Envoy Proxy 作为代理组件
• 控制面以 Pilot 为核心组件
• 平台开放与扩展主要通过 Kubernetes CRD与Mesh Configuration Protocol（简称为 MCP，一套标准 GRPC 协议）
• 高可用设计主要基于 Kubernetes 及 Istio 机制实现

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今天先到这儿，希望对云原生，技术领导力， 企业管理，系统架构设计与评估，团队管理, 项目管理, 产品管理，团队建设 有参考作用 , 您可能感兴趣的文章:
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作者：Petter Liu
出处：http://www.cnblogs.com/wintersun/
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