How will AI enhance platform engineering and DevEx?

Author | Heather Joslyn

Please rewrite the following content into Chinese: Xingxuan

For many companies adopting DevOps, scaling and creating value by increasing developer productivity is a huge challenge. In this article, we discuss the latest AI-driven approaches in platform engineering.

1. AI-driven DevOps platform

Digital.ai is an industry-leading AI-driven technology company dedicated to helping global enterprises achieve digital transformation. Its customers include large enterprises: financial institutions, insurance organizations and gaming companies. One of the biggest problems they face is scale.

Today I want to reveal to you how the DevOps platform in an AI-driven company is implemented

Of course, according to the Digital.ai value stream delivery platform and DevOps Vice President of Engineering and DevOps General Manager Wing To said in a foreign media podcast that they are all adopting modern development methods such as agile DevOps. However, in large organizations (e.g. thousands of developers), the real challenge they face is how to scale to reap the benefits of fast delivery and stay relevant to end users, while still being able to do this at scale

This article will discuss with you the latest progress in platform engineering and how artificial intelligence can help enhance automation.

Wing To said: "Of course, they are all using modern development methods such as agile DevOps." Added Digital.ai Vice President of Value Stream Delivery Platform and DevOps Engineering

In large organizations , especially when you have tens of thousands of developers organized, the real challenge we face is how to achieve rapid delivery while scaling, stay close to the end user, and then still be able to do that at scale. In this issue of Makers, TNS's To and Heather Joslyn discuss the latest advances in platform engineering and how artificial intelligence can help enhance automation and improve productivity. Where is the value?

In addition to the challenges of promoting DevOps practices, there’s another question to consider: If these practices help developers write more code and release more frequently, is that a good thing?

There is also a new challenge, he added. "I believe everyone is talking about the development of AI-assisted or AI-augmented, especially in large enterprises, and they see the potential to increase productivity. But, how do you implement this across the entire organization?"

What if a company has highly productive developers but can't match them in terms of what happens after the software is built? To said: "As we all know, delivering code is not just about writing code. There are many processes after that." "The follow-up also needs to keep up with the same pace."

3. Combine automation with artificial intelligence

Platform Engineering is a set of practices and tools designed to free developers from having to worry so much about Kubernetes and infrastructure, and from having operations engineers take on repetitive tasks in serving those developers. "As the team grows in size, the challenge we face is that the new junior developers (and) mid-level developers are not very skilled, and we don't want our senior developers to spend all their time on infrastructure," To said. on."

digital.ai focuses on incorporating artificial intelligence into automation to help developers create and deliver code and help organizations gain more business value from software production. So, how do we scale? How do we arrange things so that we can achieve reusable, common orchestration?

Digital.ai’s current work includes applying templates to capture and replicate hard-to-change parts of an organization’s software delivery process. In addition, they also use artificial intelligence technology to help quickly automate the setup of developer environments and create tools for developers

According to my understanding, what this sentence means is that Digital.ai is working hard to improve their "internal Developer Platform" and they are using a variety of different tools to achieve this, such as creating pipelines, executing individual tasks, or setting up

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