Now that our service is deployed in the K8s cluster, we want to deploy a monitoring service to automatically monitor the resources in the K8s cluster. This blog is divided into two parts. First is using Prometheus to monitor the service for our K8s cluster, when the monitor service finds some node or pod has issues and sends an alert as soon as possible, our deployer can fix the issues asap. And the second page is coded as simply Shell scripts to test the cluster’s network.

目前我们的业务都部署在K8s集群上，我们想要搭建一个监控服务来对K8s集群的资源进行自动化监控。本文分两节，一个是使用Prometheus来检测K8s集群，当检测到节点或者容器出现异常时及时报警，快速发现并解决问题。另一个编写了一个简单的Shell脚本来测试集群网络。

Now we use DolphinScheduler version 2.0.5 to build our data platform, and we want to improve our platform stability and find the bugs as soon as pissboy, so we want to introduce an E2E test in our project. Writing for recording enabling the E2E test process and the resolution of the Could not connect to Ryuk question.

我们目前在使用DolphinScheduler 2.0.5版本搭建大数据调度平台，由于想要提高系统稳定性，尽早能发现bug，所以我们想在项目中引入E2E测试。本文记录启用E2E的过程和遇到Could not connect to Ryuk问题的解决过程。

We have deployed the log colleges system in the k8s cluster before, but have poor performance. The maximum resource of Fluentd is 800M memory and 1 CPU, it can only process and push almost 1500 logs per second. We need performance tuning.

之前我们已经在k8s集群中搭建好日志收集系统了，但是经过测试后性能很差，在设置Fulentd的最大资源是800M内存，1核CPU后进行压测，1秒中能处理并推送大约1500条日志，需要调优以提高性能。

After DolphinScheduler was deployed succeeded, I was thinking about how to inject the config data into the project. This document is for recording.

DolphinScheduler搭建好之后，思考了一下在Docker和Kubernetes不同模式下配置参数是如何注入到项目里的。

Recently we are working on deployment dolphinscheduler on docker & k8s following the official guide.

最近在跟着官方文档搭建docker和k8s模式的dolphinscheduler，遇到了一些问题记录下来。