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Get the Linux kit version your Docker for Mac uses.You can get the files I mention below in the ebf-playground repo. In his case, symlinks were created automatically from /usr/src/$(uname -r) to those directories but that was not my reality. The steps below are mostly the same as Peter’s, except I added a start script and had to create volumes to /lib/modules/$(uname -r)/source and /lib/modules/$(uname -r)/build. Install and run Power BI on a PC, then use a remote viewer to control that PC. Install and run Power BI on a Virtual Machine, then remote in to that Virtual Machine. Since Power BI cant run on a Mac, here are our recommendations to run Power BI on Macintosh Devices. Hence I needed to find a way to compile and install them. Our 3 solutions for running Power BI on Mac. This means the regular install command ( apt-get install -y bpfcc-tools "linux-headers-$(uname -r)") won’t work, because there are no linux-headers. Install Docker Installing Docker is super easy in Mac.
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Download Docker Desktop dmg You can visit the official download site using the link below to obtain the latest version of Docker for Mac. Using DockerĮBPF tools such as BCC and bpftrace rely on Kernel headers which don’t ship with the Docker Desktop for macOS VM. Steps to Install Docker Desktop on macOS Catalina Step 1.
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If you’re only interested in doing the install, I suggest you skip to the “ Using Vagrant” section. However, it fell short on running some BCC tools and I had to change some stuff to get it working.
#How to install docker on mac os how to
I did find one article by Peter Malmgren that explains how to do this using Docker, which was really helpful. Most of the content assumes Ubuntu or some other Linux host. ĭoing this with Docker proved to be difficult, and I could barely find any articles that talked about installing BCC on an OS X host. One of the first requirements is to install BCC, and my first instinct was to use Docker. I recently began exploring eBPF, starting with Brendan Gregg’s BPF Performance Tools: Linux System and Application Observability.
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