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Fog Dong

ChatGPT is taking the tech industry by storm, thanks to its unparalleled natural language processing capabilities. As a powerful AI language model, it has the ability to understand and generate human-like responses, revolutionizing communication in various industries. From streamlining customer service chatbots to enabling seamless language translation tools, ChatGPT has already proved its mettle in creating innovative solutions that improve efficiency and user experience.

Now the question is, can we leverage ChatGPT to transform the way we deliver applications? With the integration of ChatGPT into DevOps workflows, we are witnessing the possible emergence of a new era of automation called PromptOps. This advancement in AIOps technology is revolutionizing the way businesses operate, allowing for faster and more efficient application delivery.

In this article, we will explore how to integrate ChatGPT into your DevOps workflow to deliver applications.

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Serverless 应用引擎(SAE) 是一款底层基于 Kubernetes,实现了 Serverless 架构与微服务架构结合的云产品。作为一款不断迭代的云产品,在快速发展的过程中也遇到了许多挑战。如何在蓬勃发展的云原生时代中解决这些挑战,并进行可靠快速的云架构升级?SAE 团队和 KubeVela 社区针对这些挑战开展了紧密合作,并给出了云原生下的开源可复制解决方案——KubeVela Workflow。

本文将详细介绍 SAE 使用 KubeVela Workflow 进行架构升级的解决方案,并对多个实践场景进行一一解读。

Serverless 时代下的挑战

Serverless 应用引擎(SAE)是面向业务应用架构、微服务架构的一站式应用托管平台,是一款底层基于 Kubernetes,实现了 Serverless 架构与微服务架构结合的云产品。


如上架构图,SAE 的用户可以将多种不同类型的业务应用托管在 SAE 之上。而在 SAE 底层,则会通过 JAVA 业务层处理相关的业务逻辑,以及与 Kubernetes 资源进行交互。在最底层,则依靠高可用,免运维,按需付费的弹性资源池。

在这个架构下,SAE 主要依托其 JAVA 业务层为用户提供功能。这样的架构在帮助用户一键式部署应用的同时,也带来了不少挑战。