Remove Continuous Delivery Remove DevOps Remove Product Management
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6 enterprise DevOps mistakes to avoid

CIO

It may surprise you, but DevOps has been around for nearly two decades. Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps.

DevOps 214
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Rethinking DevOps and automation with a layered approach

CIO

Despite the talk about how automation can make employees and businesses more productive, managing it across the entire DevOps chain is a complex task. Automation doesn’t happen on an island The DevOps stack is composed of a multitude of layers, all handling different points in the development lifecycle from start to finish.

DevOps 166
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CircleCI Surfaces More DevOps Insights

DevOps.com

CircleCI today announced it is making it easier for DevOps teams to determine the amount of resources being consumed by its continuous integration/continuous delivery (CI/CD) platform to help make application development teams more efficient. The post CircleCI Surfaces More DevOps Insights appeared first on DevOps.com.

DevOps 114
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Practical Skills for The AI Product Manager

O'Reilly Media - Ideas

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products.

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A DevOps Guide for Product Managers

Speaker: Suzie Prince, Head of DevOps, Atlassian

In an ever changing world Product Managers are being pushed now, more than ever, to keep up with business and customer demands. Luckily, the culture of DevOps and the practice of Continuous Delivery supports product managers and their teams as modern software development evolves at a rapid pace.

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AI Product Management After Deployment

O'Reilly Media - Ideas

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed.

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Article: Data-Driven Decision Making – Product Development with Continuous Delivery Indicators

InfoQ Culture Methods

The Data-Driven Decision Making Series provides an overview of how the three main activities in the software delivery - Product Management, Development and Operations - can be supported by data-driven decision making. In Development, Continuous Delivery Indicators can be used to steer the efficiency of the development process.