Curated articles, resources, tips and trends from the DevOps World.
The early days of artificial intelligence research had a community feel — to openly share ideas, and work together to improve technologies. But a lot changed with ChatGPT, which took the world by storm last year.
A ZeroOps philosophy helps organizations focus more on innovation and less on infrastructure while helping accelerate development and save both time and money.
Cloud services like software-as-a-service apps, data storage and media streaming, are becoming more common, which makes application architecture more complicated. Not all applications are easy to move from a local server to the cloud.
When OpenAI released ChatGPT-3 in November — and especially after it unveiled the GPT-4 version in March — a flurry of articles about prompt engineering hit the mainstream and business press.
If you’re using a Docker-based development approach, you’re already well on your way toward creating cloud-native software.
Distributed tracing has been around for over a decade, and it arrived on the scene with great fanfare. There were promises that distributed tracing would unlock the mysteries of large, complex microservices environments.
“Generative AI is one of the best augmentation means — not substitution, augmentation. Augmenting the professions that actually exist. Augmenting an auditor, augmenting a tax advisor, augmenting a legal expert, augmenting a strategic adviser.”
When choosing a supplier to partner with, organizations need to perform their due diligence and assess the cyber risks associated with each particular supplier using risk assessment evaluations.
Cloud platform engineering isn’t easy, but when it’s done right the business benefits make it worthwhile. In this post, author Ashley Petherick we shares insights into the lessons learnt from building a cloud platform for a FTSE 100 financial services business.
There have been some misleading headlines floating around the mainstream media as of late regarding cloud computing.
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