Lokvin Wiki
(Created page with "= docs = == linkerd offical doc == * https://linkerd.io/advanced/")
 
 
(6 intermediate revisions by the same user not shown)
Line 3: Line 3:
 
== linkerd offical doc ==
 
== linkerd offical doc ==
 
* https://linkerd.io/advanced/
 
* https://linkerd.io/advanced/
  +
  +
== dtab ==
  +
* https://linkerd.io/advanced/dtabs/
  +
  +
=== finagle ===
  +
* https://twitter.github.io/finagle/guide/Names.html
  +
  +
== Service Mesh Docs ==
  +
* https://buoyant.io/2016/05/04/real-world-microservices-when-services-stop-playing-well-and-start-getting-real/
  +
  +
* What is service mesh
  +
<blockquote>
  +
a service mesh is a layer that manages the communication between apps (or between parts of the same app, e.g. microservices). In traditional apps, this logic is built directly into the application itself: retries and timeouts, monitoring/visibility, tracing, service discovery, etc. are all hard-coded into each application.
  +
</blockquote>
  +
  +
* A service mesh like linkerd provides critical features to multi-service applications running at scale:
  +
# Baseline resilience: retry budgets, deadlines, circuit-breaking
  +
# Top-line service metrics: success rates, request volumes, and latencies.
  +
# latency and failure tolerance: Failure- and latency-aware load balancing that can route around slow or broken service instances.
  +
# Distributed tracing a la Zipkin and OpenTracing
  +
# Service discovery: locate destination instances.
  +
# Protocol upgrades: wrapping cross-network communication in TLS, or converting HTTP/1.1 to HTTP/2.0.
  +
# Routing: route requests between different versions of services, failover between clusters, etc.

Latest revision as of 08:58, 19 April 2018

docs[]

linkerd offical doc[]

dtab[]

finagle[]

Service Mesh Docs[]

  • What is service mesh

a service mesh is a layer that manages the communication between apps (or between parts of the same app, e.g. microservices). In traditional apps, this logic is built directly into the application itself: retries and timeouts, monitoring/visibility, tracing, service discovery, etc. are all hard-coded into each application.

  • A service mesh like linkerd provides critical features to multi-service applications running at scale:
  1. Baseline resilience: retry budgets, deadlines, circuit-breaking
  2. Top-line service metrics: success rates, request volumes, and latencies.
  3. latency and failure tolerance: Failure- and latency-aware load balancing that can route around slow or broken service instances.
  4. Distributed tracing a la Zipkin and OpenTracing
  5. Service discovery: locate destination instances.
  6. Protocol upgrades: wrapping cross-network communication in TLS, or converting HTTP/1.1 to HTTP/2.0.
  7. Routing: route requests between different versions of services, failover between clusters, etc.