Nikhil/cncfbloglinkfix

blog/cncf-sandbox-announcement/index.mdx

@@ -1,29 +1,31 @@
 ---
 authors:
-- Sanil Kumar
-- Jun Du
+  - Sanil Kumar
+  - Jun Du
 categories:
-- General
-- Announcements
+  - General
+  - Announcements
 date: 2019-03-19
 draft: false
 lastmod: 2019-03-19
 subtitle: KubeEdge was accepted into the CNCF sandbox in March 2019
-summary: KubeEdge is a Kubernetes Native Edge Computing Framework. KubeEdge was accepted
+summary:
+  KubeEdge is a Kubernetes Native Edge Computing Framework. KubeEdge was accepted
   into the CNCF sandbox in March 2019
 tags:
-- KubeEdge
-- kubeedge
-- edge computing
-- kubernetes edge computing
-- K8S edge orchestration
-- edge computing platform
-- cncf sandbox
-- cloud native
+  - KubeEdge
+  - kubeedge
+  - edge computing
+  - kubernetes edge computing
+  - K8S edge orchestration
+  - edge computing platform
+  - cncf sandbox
+  - cloud native
 title: 'From the K8S blog: KubeEdge - a Kubernetes Native Edge Computing Framework'
 ---
-The **KubeEdge** team presented their case for sandboxing at the CNCF TOC meeting on 12th March 2019.  
-
+
+The **KubeEdge** team presented their case for sandboxing at the CNCF TOC meeting on 12th March 2019.
+
 <!--truncate-->
 
 ## **Today we announce the acceptance of KubeEdge under the CNCF sandbox.**
@@ -36,23 +38,24 @@ Original Article: [Source](https://kubernetes.io/blog/2019/03/19/kubeedge-k8s-ba
 
 :::info
 
-CNCF Sandbox page:  [CNCF Sandbox Projects](https://www.cncf.io/sandbox-projects/)
+CNCF Sandbox page: [CNCF Sandbox Projects](https://www.cncf.io/sandbox-projects/)
 
 :::
 
 :::info
 
-[KubeEdge Repository](https://github.com/kubeedge/kubeedge)  | [KubeEdge Documentation](https://docs.kubeedge.io) | [Setup KubeEdge](https://docs.kubeedge.io/en/latest/setup/setup.html)
+[KubeEdge Repository](https://github.com/kubeedge/kubeedge) | [KubeEdge Documentation](https://docs.kubeedge.io) | [Setup KubeEdge](https://kubeedge.io/docs/category/setup)
 
-::: 
+:::
 
-## **KubeEdge becomes the first Kubernetes Native Edge Computing Platform with both Edge and Cloud components open sourced!**  
+## **KubeEdge becomes the first Kubernetes Native Edge Computing Platform with both Edge and Cloud components open sourced!**
 
 Open source edge computing is going through its most dynamic phase of development in the industry. So many open source platforms, so many consolidations and so many initiatives for standardization! This shows the strong drive to build better platforms to bring cloud computing to the edges to meet ever increasing demand. KubeEdge, which was announced last year, now brings great news for cloud native computing! It provides a complete edge computing solution based on Kubernetes with separate cloud and edge core modules. Currently, both the cloud and edge modules are open sourced.
 
 Unlike certain light weight kubernetes platforms available around, KubeEdge is made to build edge computing solutions extending the cloud. The control plane resides in cloud, though scalable and extendable. At the same time, the edge can work in offline mode. Also it is lightweight and containerized, and can support heterogeneous hardware at the edge. With the optimization in edge resource utlization, KubeEdge positions to save significant setup and operation cost for edge solutions. This makes it the most compelling edge computing platform in the world currently, based on Kubernetes!
 
 ### **_Kube(rnetes)Edge_!** - Opening up a new Kubernetes-based ecosystem for Edge Computing
+
 The key goal for KubeEdge is extending Kubernetes ecosystem from cloud to edge. From the time it was announced to the public at KubeCon in Shanghai in November 2018, the architecture direction for KubeEdge was aligned to Kubernetes, as its name!
 
 It started with its v0.1 providing the basic edge computing features. Now, with its latest release v0.2, it brings the cloud components to connect and complete the loop. With consistent and scalable Kubernetes-based interfaces, KubeEdge enables the orchestration and management of edge clusters similar to how Kubernetes manages in the cloud. This opens up seamless possibilities of bringing cloud computing capabilities to the edge, quickly and efficiently.
@@ -61,7 +64,6 @@ Based on its roadmap and architecture, KubeEdge tries to support all edge nodes,
 
 KubeEdge provides a containerized edge computing platform, which is inherently scalable. As it’s modular and optimized, it is lightweight (66MB foot print and ~30MB running memory) and could be deployed on low resource devices. Similarly, the edge node can be of different hardware architecture and with different hardware configurations. For the device connectivity, it can support multiple protocols and it uses a standard MQTT-based communication. This helps in scaling the edge clusters with new nodes and devices efficiently.
 
-
 ## **You heard it right!**
 
 > **KubeEdge Cloud Core modules are open sourced!**
@@ -91,16 +93,14 @@ Even if you want to add more control plane modules based on the architecture ref
 
 - KubeEdge provides scalable lightweight Kubernetes Native Edge Computing Platform which can work in offline mode.
 
-
 - It helps simplify edge application development and deployment.
 
-
 - Cloud vendor agnostic and can run the cloud core modules on any compute node.
 
 :::
 
-
 ## **Release 0.1 to 0.2 – game changer!**
+
 KubeEdge v0.1 was released at the end of December 2018 with very basic edge features to manage edge applications along with Kubernetes API primitives for node, pod, config etc. In ~2 months, KubeEdge v0.2 was release on March 5th, 2019. This release provides the cloud core modules and enables the end to end open source edge computing solution. The cloud core modules can be deployed to any compute node from any cloud vendors or on-prem.
 
 Now, the complete edge solution can be installed and tested very easily, also with a laptop.
@@ -117,13 +117,15 @@ The installation is simple and can be done in few steps:
 - The detailed steps for each are available at [KubeEdge Setup](https://docs.kubeedge.io/en/latest/setup/setup.html)
 
 ## **Future: Taking off with competent features and community collaboration**
+
 KubeEdge has been developed by members from the community who are active contributors to Kubernetes/CNCF and doing research in edge computing. The KubeEdge team is also actively collaborating with Kubernetes IOT/EDGE WORKING GROUP. Within a few months of the KubeEdge announcement it has attracted members from different organizations including JingDong, Zhejiang University, SEL Lab, Eclipse, China Mobile, ARM, Intel to collaborate in building the platform and ecosystem.
 
-KubeEdge has a clear [roadmap](https://docs.kubeedge.io/en/latest/getting-started/roadmap.html) for its upcoming major releases in 2019. v1.0 targets to provide a complete edge cluster and device management solution with standard edge to edge communication, while v2.0 targets to have advanced features like service mesh, function service , data analytics etc at edge. Also, for all the features, KubeEdge architecture would attempt to utilize the existing CNCF projects/software.
+KubeEdge has a clear [roadmap](https://kubeedge.io/docs/roadmap) for its upcoming major releases in 2019. v1.0 targets to provide a complete edge cluster and device management solution with standard edge to edge communication, while v2.0 targets to have advanced features like service mesh, function service , data analytics etc at edge. Also, for all the features, KubeEdge architecture would attempt to utilize the existing CNCF projects/software.
 
 The KubeEdge community needs varied organizations, their requirements, use cases and support to build it. Please join to make a kubernetes native edge computing platform which can extend the cloud native computing paradigm to edge cloud.
 
 ## **How to Get Involved?**
+
 We welcome more collaboration to build the Kubernetes native edge computing ecosystem. Please join us!
 
 :::info

i18n/zh/docusaurus-plugin-content-blog/reach-slsa-l3/index.md

@@ -34,7 +34,7 @@ Google 提出的用于保证整个软件供应链完整性的框架 SLSA，是
 
 截止目前，SLSA 标准处于 alpha 阶段，相关的定义可能会发生变化。
 
-下图描述了软件供应链中已知的攻击点。更多详细描述，可参考https://slsa.dev/。
+下图描述了软件供应链中已知的攻击点。更多详细描述，可参考https://slsa.dev/
 
 ![slsa-dev](./images/slsa-dev.png)
 
@@ -121,15 +121,15 @@ e) **第三方依赖的完整性：**Provenance 记录运行构建步骤时可
 
 在 KubeEdge 版本发布的流程（.github/workflows/release.yml）中，集成了 slsa-framework/slsa-github-generator/.github/workflows/generator_generic_slsa3.yml 和 slsa-framework/slsa-github-generator/.github/workflows/generator_container_slsa3.yml，可保障构建和发布产物（包括二进制文件和容器镜像）的流程满足 SLSA L3 等级的要求。
 
-更多关于 slsa-github-generator 的详细说明请见https://github.com/slsa-framework/slsa-github-generator。
+更多关于 slsa-github-generator 的详细说明请见https://github.com/slsa-framework/slsa-github-generator
 
 ### 关于 Provenance
 
 Provenance 是构建的元数据包括构建过程、构建源和依赖关系，是软件构建和发布执行流程的一种证明，并且是可以被验证的，包括构建的源码仓库、代码分支、配置文件等信息。在 SLSA L3 级别，Provenance 内容是真实的、防篡改的，并且不会被项目维护者更改。二进制发布产物的 Provenance 文件随发布软件包一起发布，名称为 multiple.intoto.jsonl，容器镜像的 Provenance 文件随镜像文件一起上传到 KubeEdge dockerhub 公开仓库中。具体的 Provenance 格式说明，请参考https://github.com/slsa-framework/slsa-github-generator/blob/main/internal/builders/generic/README.md#provenance-format。
 
 ### 如何校验 KubeEdge 发布产物是否满足 SLSA L3 等级
 
-详细步骤描述请见https://github.com/kubeedge/kubeedge/pull/4285。
+详细步骤描述请见https://github.com/kubeedge/kubeedge/pull/4285
 
 校验示例如下：
 

i18n/zh/docusaurus-plugin-content-docs/current/setup/keadm.md

@@ -68,7 +68,7 @@ KubeEdge cloudcore is running, For logs visit:  /var/log/kubeedge/cloudcore.log
 1. 自定义 `--set key=value`
    值可以参考 [KubeEdge Cloudcore Helm Charts README.md](https://github.com/kubeedge/kubeedge/blob/master/build/helm/charts/cloudcore/README.md)
 2. 您可以从 Keadm 的一个内置配置概要文件开始，然后根据您的特定需求进一步定制配置。目前，内置的配置概要文件关键字是 `version`
-   。请参考 [`version.yaml`](https://github.com/kubeedge/kubeedge/blob/master/build/helm/charts/profiles/version.yaml)
+   。请参考 [`version.yaml`](https://github.com/kubeedge/kubeedge/blob/master/manifests/profiles/version.yaml)
    ，您可以在这里创建您的自定义配置文件, 使用 `--profile version=v1.9.0 --set key=value` 来使用它。
 
 此外，还可使用 `--external-helm-root` 安装外部的 helm chart 组件，如 edgemesh 。
@@ -79,7 +79,7 @@ KubeEdge cloudcore is running, For logs visit:  /var/log/kubeedge/cloudcore.log
 # keadm beta init --set server.advertiseAddress="THE-EXPOSED-IP" --set server.nodeName=allinone  --kube-config=/root/.kube/config --force --external-helm-root=/root/go/src/github.com/edgemesh/build/helm --profile=edgemesh
 ```
 
-如果您对 Helm Chart 比较熟悉，可以直接参考 [KubeEdge Helm Charts](https://github.com/kubeedge/kubeedge/tree/master/build/helm/charts)
+如果您对 Helm Chart 比较熟悉，可以直接参考 [KubeEdge Helm Charts](https://github.com/kubeedge/kubeedge/tree/master/keadm/cmd/keadm/app/cmd/helm)
 进行安装。
 
 ### keadm beta manifest generate
@@ -214,7 +214,7 @@ KubeEdge edgecore is running, For logs visit:  /var/log/kubeedge/edgecore.log
    iptables -F && iptables -t nat -F && iptables -t mangle -F && iptables -X
    ```
 
-   > 现在可以通过 iptablesmanager 这个组件自动运维以上的 iptables 转发规则，参考 [cloudcore helm values](https://github.com/kubeedge/kubeedge/blob/master/build/helm/charts/cloudcore/values.yaml#L66).
+   > 现在可以通过 iptablesmanager 这个组件自动运维以上的 iptables 转发规则，参考 [cloudcore helm values](https://github.com/kubeedge/kubeedge/blob/master/manifests/charts/cloudcore/README.md#custom-values).
 
 5. `/etc/kubeedge/config/cloudcore.yaml` 和 `/etc/kubeedge/config/edgecore.yaml` 上 cloudcore 和 edgecore **都要** 修改。将 **cloudStream** 和 **edgeStream** 设置为 `enable: true` 。将服务器 IP 更改为 cloudcore IP（与 $ CLOUDCOREIPS 相同）。
 
@@ -368,7 +368,7 @@ KubeEdge edgecore is running, For logs visit:  /var/log/kubeedge/edgecore.log
    docker tag a24f71249d69 metrics-server-kubeedge:latest
    ```
 
-3. 部署 yaml 应用。可以参考相关部署文档：https://github.com/kubernetes-sigs/metrics-server/tree/master/manifests。
+3. 部署 yaml 应用。可以参考相关部署文档：https://github.com/kubernetes-sigs/metrics-server/tree/master/manifests
 
    注意：下面的那些 iptables 必须应用在机器上（精确地是网络名称空间，因此 metrics-server 也需要在主机网络模式下运行）metric-server 在其上运行。