Table of Contents
1. AI-driven DevOps platform
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?
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."
Home Technology peripherals AI How will AI enhance platform engineering and DevEx?

How will AI enhance platform engineering and DevEx?

Oct 31, 2023 pm 08:13 PM
AI platform project

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

The above is the detailed content of How will AI enhance platform engineering and DevEx?. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Topping the list of open source AI software engineers, UIUC's agent-less solution easily solves SWE-bench real programming problems Topping the list of open source AI software engineers, UIUC's agent-less solution easily solves SWE-bench real programming problems Jul 17, 2024 pm 10:02 PM

The AIxiv column is a column where this site publishes academic and technical content. In the past few years, the AIxiv column of this site has received more than 2,000 reports, covering top laboratories from major universities and companies around the world, effectively promoting academic exchanges and dissemination. If you have excellent work that you want to share, please feel free to contribute or contact us for reporting. Submission email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com The authors of this paper are all from the team of teacher Zhang Lingming at the University of Illinois at Urbana-Champaign (UIUC), including: Steven Code repair; Deng Yinlin, fourth-year doctoral student, researcher

Posthumous work of the OpenAI Super Alignment Team: Two large models play a game, and the output becomes more understandable Posthumous work of the OpenAI Super Alignment Team: Two large models play a game, and the output becomes more understandable Jul 19, 2024 am 01:29 AM

If the answer given by the AI ​​model is incomprehensible at all, would you dare to use it? As machine learning systems are used in more important areas, it becomes increasingly important to demonstrate why we can trust their output, and when not to trust them. One possible way to gain trust in the output of a complex system is to require the system to produce an interpretation of its output that is readable to a human or another trusted system, that is, fully understandable to the point that any possible errors can be found. For example, to build trust in the judicial system, we require courts to provide clear and readable written opinions that explain and support their decisions. For large language models, we can also adopt a similar approach. However, when taking this approach, ensure that the language model generates

A significant breakthrough in the Riemann Hypothesis! Tao Zhexuan strongly recommends new papers from MIT and Oxford, and the 37-year-old Fields Medal winner participated A significant breakthrough in the Riemann Hypothesis! Tao Zhexuan strongly recommends new papers from MIT and Oxford, and the 37-year-old Fields Medal winner participated Aug 05, 2024 pm 03:32 PM

Recently, the Riemann Hypothesis, known as one of the seven major problems of the millennium, has achieved a new breakthrough. The Riemann Hypothesis is a very important unsolved problem in mathematics, related to the precise properties of the distribution of prime numbers (primes are those numbers that are only divisible by 1 and themselves, and they play a fundamental role in number theory). In today's mathematical literature, there are more than a thousand mathematical propositions based on the establishment of the Riemann Hypothesis (or its generalized form). In other words, once the Riemann Hypothesis and its generalized form are proven, these more than a thousand propositions will be established as theorems, which will have a profound impact on the field of mathematics; and if the Riemann Hypothesis is proven wrong, then among these propositions part of it will also lose its effectiveness. New breakthrough comes from MIT mathematics professor Larry Guth and Oxford University

arXiv papers can be posted as 'barrage', Stanford alphaXiv discussion platform is online, LeCun likes it arXiv papers can be posted as 'barrage', Stanford alphaXiv discussion platform is online, LeCun likes it Aug 01, 2024 pm 05:18 PM

cheers! What is it like when a paper discussion is down to words? Recently, students at Stanford University created alphaXiv, an open discussion forum for arXiv papers that allows questions and comments to be posted directly on any arXiv paper. Website link: https://alphaxiv.org/ In fact, there is no need to visit this website specifically. Just change arXiv in any URL to alphaXiv to directly open the corresponding paper on the alphaXiv forum: you can accurately locate the paragraphs in the paper, Sentence: In the discussion area on the right, users can post questions to ask the author about the ideas and details of the paper. For example, they can also comment on the content of the paper, such as: "Given to

The first Mamba-based MLLM is here! Model weights, training code, etc. have all been open source The first Mamba-based MLLM is here! Model weights, training code, etc. have all been open source Jul 17, 2024 am 02:46 AM

The AIxiv column is a column where this site publishes academic and technical content. In the past few years, the AIxiv column of this site has received more than 2,000 reports, covering top laboratories from major universities and companies around the world, effectively promoting academic exchanges and dissemination. If you have excellent work that you want to share, please feel free to contribute or contact us for reporting. Submission email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com. Introduction In recent years, the application of multimodal large language models (MLLM) in various fields has achieved remarkable success. However, as the basic model for many downstream tasks, current MLLM consists of the well-known Transformer network, which

Axiomatic training allows LLM to learn causal reasoning: the 67 million parameter model is comparable to the trillion parameter level GPT-4 Axiomatic training allows LLM to learn causal reasoning: the 67 million parameter model is comparable to the trillion parameter level GPT-4 Jul 17, 2024 am 10:14 AM

Show the causal chain to LLM and it learns the axioms. AI is already helping mathematicians and scientists conduct research. For example, the famous mathematician Terence Tao has repeatedly shared his research and exploration experience with the help of AI tools such as GPT. For AI to compete in these fields, strong and reliable causal reasoning capabilities are essential. The research to be introduced in this article found that a Transformer model trained on the demonstration of the causal transitivity axiom on small graphs can generalize to the transitive axiom on large graphs. In other words, if the Transformer learns to perform simple causal reasoning, it may be used for more complex causal reasoning. The axiomatic training framework proposed by the team is a new paradigm for learning causal reasoning based on passive data, with only demonstrations

To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework Jul 25, 2024 am 06:42 AM

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

Nvidia plays with pruning and distillation: halving the parameters of Llama 3.1 8B to achieve better performance with the same size Nvidia plays with pruning and distillation: halving the parameters of Llama 3.1 8B to achieve better performance with the same size Aug 16, 2024 pm 04:42 PM

The rise of small models. Last month, Meta released the Llama3.1 series of models, which includes Meta’s largest model to date, the 405B model, and two smaller models with 70 billion and 8 billion parameters respectively. Llama3.1 is considered to usher in a new era of open source. However, although the new generation models are powerful in performance, they still require a large amount of computing resources when deployed. Therefore, another trend has emerged in the industry, which is to develop small language models (SLM) that perform well enough in many language tasks and are also very cheap to deploy. Recently, NVIDIA research has shown that structured weight pruning combined with knowledge distillation can gradually obtain smaller language models from an initially larger model. Turing Award Winner, Meta Chief A

See all articles