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golangcookbook.com | ||
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philiplaine.com
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| | | | | It has been an issue for a long time to run Docker images on multiple architectures. I remember the first time I got the idea to install Docker on my Raspberry Pi and I realized quickly that what I was trying to do would not work. The issue of course was that I was trying to use an AMD64 compiled Docker image on a ARM 32 bit CPU. Anyone who works with any lower level languages would call me an idiot for realizing this sooner than later. I would agree with them. Docker just seems to work like magic, running on most machines without any issue, like running Linux containers on Windows. One thing that has not been easy though is building Docker images on one type of CPU and running them on another. | |
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peter0x44.github.io
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| | | | | Cross compilation is a common task during development, but different compilers and programming languages handle it in their own ways, and I wanted to write about the various flavors of trade-offs and design decisions that you will find across different tooling. I feel like I have absorbed a lot of information about how cross compilation works across different targets, tools and languages, so I figured it was time to condense my knowledge into a blog post. This is not a tutorial, but it still contains practically applicable knowledge. I don't claim to get every detail correct, merely explaining how things work to my understanding. | |
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paul.totterman.name
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| | | | | Like many other developers, I have to work with computers with different processor architectures. For me it's amd64 (x86_64) on the laptop and arm64 (aarch64) on the server. For some it may be the other way around. Fortunately I mostly write Go, which makes cross-compilation quite easy. Docker adds some extra steps, but is very nice for deploying software. | |
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www.opensourceforu.com
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| | | Kubernetes is more than just a tool; it serves as a robust platform, streamlining the deployment of applications, as well as their scaling and operation in | ||
