Curated articles, resources, tips and trends from the DevOps World.
The demand for data scientists is at a fever pitch. A 2022 survey revealed that insufficient talent or headcount is the biggest barrier to the successful enterprise adoption of data science.
Editor’s note: Today marks the launch of Tech Works, a new monthly column by longtime New Stack contributor Jennifer Riggins that will explore workplace conditions, management ideas, career development and the tech job market as it affects the people who build and run the software the world relies
GitOps is one of the most impactful evolutions that has happened during Kubernetes’ rise to the top. We had been building our kubefirst instant cloud native platform for more than a year when we discovered GitOps. It wrecked us.
There’s this marketing manager who is trying to time a launch. She asks the developer team when the service will be ready. The dev team says maybe a few months. Let’s say three months from now in April. The marketing manager begins prepping for the release.
It should come as little surprise that when enterprise and IT leaders turned their attention to the cloud, so did attackers. Today’s cloud-first approach to building dynamic work environments blurs the boundaries of where the corporate network begins and ends, and which apps belong to the company.
The rise of platform engineering is changing DevOps. DevOps have the task of creating internal developer portals to help others (mostly developers) consume services. But this isn’t the entire story.
New data on developers and how they do their jobs not only confirms that far more devs work remotely now than before the COVID-19 pandemic but offers a glimpse at which tools they’re using. Before the pandemic, 67% of participants in a new survey by JetBrains said they mainly worked at an office.
Microsoft has made its Azure Load Testing Service generally available to help developers optimize the performance, scalability and capacity of their applications.
Rapid growth in users and activity has tested the scalability of many Mastodon servers, and has stressed their administrators. According to a TechCrunch interview with Mastodon’s creator, Eugen Rochko, Mastodon grew to 2.
NASA and IBM are working together to create foundation models based on NASA’s data sets — including geospatial data — with the goal of accelerating the creation of AI models.
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