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Distributed cluster management tool

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评估

难度
5/5
预计耗时
一周以上
新手友好度
25/100
Issue 类型
功能
描述清晰度
需要澄清
活跃度
冷清
技术栈
haskell

调研方向

先阅读 Cloud Haskell Process 和 Node 的概念,然后研究 distributed-process-simplelocalnet 如何处理节点发现。围绕节点发现、部署、状态查询和迁移,定义所提议的 agent 和命令行工具的范围;在实现之前就 toolkit 设计达成一致,即视为完成。

由索引模型根据 Issue 内容生成。

描述

enhancement Feature Request

There are a few issues with Cloud Haskell today that I think are showstoppers. The three that come to mind are:

  • Peer discovery must be hand-rolled. distributed-process-simplelocalnet improves somewhat on this, but multicast isn't supported in cloud environments such as AWS, Azure, and GCP;
  • A cluster must effectively run the same binary at this time to use spawn. Cluster version upgrades must be hand-rolled;
  • Cluster management (e.g. resource provisioning) must be hand-rolled.

Inspired by other tools such as Keter, I propose the creation of a toolkit that addresses these issues all at once.

The toolkit would have two parts.
The first is an agent that runs as a separate Cloud Haskell Process on every Node. This agent has an understanding of the underlying infrastructure (from Cloud or other, more bespoke environments), such that it can do peer discovery (via e.g. DNS), as well as peer registration needed to be discovered.
The second part of this toolkit is a command-line tool that allows to manage a cluster. The command-line tool interacts with the node agents to:

  • Deploy applications;
  • Query status;
  • Perform system migrations from version to version, using the attached agent for inter-version communication;

I think that having a toolkit like this would be a huge improvement for productivity, and remove much of the friction in getting started with Cloud Haskell.

I am putting this on my (ever growing) list of things to do, but if someone is really keen on getting this to work, I'm happy to provide support!

主要语言
Haskell
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环境准备

  • 没有 Dockerfile 或 Docker Compose 文件
  • 没有 Pull Request 模板
  • 阅读贡献指南

从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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