Good news
Best Regards --------------- Apache DolphinScheduler PMC Chair LidongDai [email protected] Linkedin: https://www.linkedin.com/in/dailidong Twitter: @WorkflowEasy <https://twitter.com/WorkflowEasy> --------------- On Mon, Jan 17, 2022 at 10:33 AM Jiajie Zhong <[email protected]> wrote: > Great, looking forward the new release for DolphinScheduler > And thanks Chong. > > On Mon, Jan 17, 2022 at 9:26 AM kerwin zhuang <[email protected]> wrote: > > > Hi all: > > > > Many thanks to everyone who is following the Apache DolphinScheduler > > community. > > > > Apache DolphinScheduler is pleased to announce that Apache > DolphinScheduler > > version 2.0.3 will be released on January 20th. > > > > > > If you have any questions, please refer to DolphinScheduler Resources: > > > > - Official website: https://dolphinscheduler.apache.org/ > > - GitHub:https://github.com/apache/dolphinscheduler > > - Issue: https://github.com/apache/dolphinscheduler/issues/ > > - Mailing list: [email protected] > > - Documents: > > > > > https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/quick-start.html > > > > > > *About DolphinScheduler:* > > > > Apache DolphinScheduler is a cloud-native visual Big Data workflow > > scheduler system. > > > > As a distributed and extensible data workflow scheduler platform with > rich > > directed acyclic graph (DAG) visual interfaces, DolphinScheduler solves > > complex task dependencies and triggers in the data pipeline. > > Out-of-the-box, > > its easy-to-extend processing connects numerous systems to 600,000-level > > data task scheduling. > > > > Apache DolphinScheduler is: > > > > - Cloud Native — support multi-cloud/data center workflow management, > also > > supports Kubernetes, Docker deployment and custom task types, distributed > > scheduling, with overall scheduling capability, increased linearly with > the > > scale of the cluster > > - Support multi-tenant > > - Highly Reliable — decentralized multi-master and multi-worker, high > > availability, supported by itself, overload processing > > - User-Friendly — all process definition operations are visualized, > defines > > key information at a glance, one-click deployment > > - Supports Rich Scenarios — includes streaming, pause, recover operation, > > and additional task types such as Spark, Hive, MR, Shell, > > Python, Flink, Sub_process, and more. > > > > Best Regards! > > > > > > - Apache DolphinScheduler Team > > > > -- > > Apache DolphinScheduler Committer > > zhuangchong > > [email protected] > > > > > -- > Best Wish > — Jiajie >
