zh-translation: /blog/2019/performance-best-practices/index.md #1134 #6243

3ks · 2019-12-30T01:23:02Z

istio-testing · 2019-12-30T01:23:17Z

Hi @gorda. Thanks for your PR.

I'm waiting for a istio member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.

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SataQiu

/ok-to-test

ilylia

建议修改

ilylia · 2019-12-30T02:40:58Z

content/zh/blog/2019/performance-best-practices/index.md


-Why test with only two pods? Because scaling up throughput (RPS) and connections (threads) has a greater effect on Envoy's performance than increasing the total size of the service registry — or, the total number of pods and services in the Kubernetes cluster. When the size of the service registry grows, Envoy does have to keep track of more endpoints, and lookup time per request does increase, but by a tiny constant. If you have many services, and this constant becomes a latency concern, Istio provides a [Sidecar resource](/zh/docs/reference/config/networking/sidecar/), which allows you to limit which services each Envoy knows about.
+为什么只用两个吊舱测试？因为增加吞吐量（RPS）和连接（线程）对 Envoy 的性能的影响比增加服务注册表的总大小（或 Kubernetes 集群中 Pod 和服务的总数）更大。当服务注册表的大小增加时，Envoy 必须跟踪更多的端点，并且每个请求的查找时间确实增加了，但是增加了一个很小的常数。如果您有许多服务，并且此常数成为延迟问题，则 Istio 提供 [Sidecar 资源](/zh/docs/reference/config/networking/sidecar/)，它使您可以限制每个 Envoy 知道的服务。


吊舱，pod

ilylia · 2019-12-30T02:41:22Z

content/zh/blog/2019/performance-best-practices/index.md


-In the [Istio Tools repository](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark), you’ll find scripts and instructions for measuring Istio's data plane performance, with additional instructions on how to run the scripts with [Linkerd](https://linkerd.io), another service mesh implementation. [Follow along](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark#setup) as we detail some best practices for each step of the performance test framework.
+在[Istio Tools 库](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark) 中，您将找到用于测量 Istio 数据平面性能的脚本和说明，以及有关如何使用另一服务网格实现 [Linkerd](https://linkerd.io) 运行脚本的其他说明。在我们详细介绍性能测试框架的每个步骤的一些最佳实践时，请[遵循](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark#setup)。


库，仓库

ilylia · 2019-12-30T02:45:29Z

content/zh/blog/2019/performance-best-practices/index.md

@@ -75,7 +75,7 @@ In the 90th percentile, with 16 concurrent connections, Istio adds **6ms**; with
    caption=""


alt 和 title 也需要翻译吧

建议修改

@ilylia 感谢细心 review，相关建议已修改

ilylia

/LGTM

rootsongjc

/LGTM

zh-translation: /blog/2019/performance-best-practices/index.md istio#…

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3ks requested a review from a team as a code owner December 30, 2019 01:23

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apply ilylia's advise

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zh-translation: /blog/2019/performance-best-practices/index.md #1134 #6243

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		Why test with only two pods? Because scaling up throughput (RPS) and connections (threads) has a greater effect on Envoy's performance than increasing the total size of the service registry — or, the total number of pods and services in the Kubernetes cluster. When the size of the service registry grows, Envoy does have to keep track of more endpoints, and lookup time per request does increase, but by a tiny constant. If you have many services, and this constant becomes a latency concern, Istio provides a [Sidecar resource](/zh/docs/reference/config/networking/sidecar/), which allows you to limit which services each Envoy knows about.
		为什么只用两个吊舱测试？因为增加吞吐量（RPS）和连接（线程）对 Envoy 的性能的影响比增加服务注册表的总大小（或 Kubernetes 集群中 Pod 和服务的总数）更大。当服务注册表的大小增加时，Envoy 必须跟踪更多的端点，并且每个请求的查找时间确实增加了，但是增加了一个很小的常数。如果您有许多服务，并且此常数成为延迟问题，则 Istio 提供 [Sidecar 资源](/zh/docs/reference/config/networking/sidecar/)，它使您可以限制每个 Envoy 知道的服务。


		In the [Istio Tools repository](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark), you’ll find scripts and instructions for measuring Istio's data plane performance, with additional instructions on how to run the scripts with [Linkerd](https://linkerd.io), another service mesh implementation. [Follow along](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark#setup) as we detail some best practices for each step of the performance test framework.
		在[Istio Tools 库](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark) 中，您将找到用于测量 Istio 数据平面性能的脚本和说明，以及有关如何使用另一服务网格实现 [Linkerd](https://linkerd.io) 运行脚本的其他说明。在我们详细介绍性能测试框架的每个步骤的一些最佳实践时，请[遵循](https://github.com/istio/tools/tree/3ac7ab40db8a0d595b71f47b8ba246763ecd6213/perf/benchmark#setup)。

		@@ -75,7 +75,7 @@ In the 90th percentile, with 16 concurrent connections, Istio adds 6ms; with
		caption=""

zh-translation: /blog/2019/performance-best-practices/index.md #1134 #6243

zh-translation: /blog/2019/performance-best-practices/index.md #1134 #6243

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