DevOps.com

SEPTEMBER 7, 2023

In this week’s The Long View: Birmingham looks like the Detroit of the UK—is it Oracle’s fault? Plus: Was Toyota’s factory failure caused by running out of disk space?

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Altexsoft

NOVEMBER 12, 2020

For over a decade, two similar concepts — DevOps and Site Reliability Engineering (SRE) — have been coexisting in the world of software development. This article explains how DevOps and SRE facilitate building reliable software, where they overlap, how they differ from each other, and when they can efficiently work side by side.

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Storm Consulting

DECEMBER 7, 2017

After almost two years of frustratingly slow progress, the DevOps transformation leaders at MIB (Massive Investment Bank, whose name is interesting but not important) are re-evaluating their choice of key performance indicators (KPIs). Figure 1 Indicative figures showing positive jaws of DevOps metrics: releases vs incidents.

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CIO

DECEMBER 22, 2022

It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. According to Gartner, DataOps also aims “to deliver value faster by creating predictable delivery and change management of data, data models, and related artifacts.”

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CircleCI

DECEMBER 21, 2021

Most developers and DevOps teams do not prioritize security when developing and working with applications and infrastructure. Adopt a change management practice. Change management practices, such as a regular change cadence and a change review group, can significantly reduce the chance of misconfiguration.

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Accenture

DECEMBER 5, 2019

A communication and change management process to gain and maintain momentum and to facilitate feedback loops. Whether to bring in external support in the form of training, coaching, consulting and change management. How to maintain profitability in the midst of the change. So much more….

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Blue Sentry

MAY 17, 2021

Even construction companies — who have a tendency to struggle with change management — are finding value in machine learning across a variety of use cases, including supply chain management, inventory control, and safety management. Many go over budget, over time, and get trapped in the bottomless pit of scalability.

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