Also known as Graphical Network Simulator-3
network software emulator
The GNS3 server manages emulators such as Dynamips, VirtualBox or Qemu/KVM. Clients like the GNS3 GUI and the GNS3 Web UI control the server using an HTTP REST API. In addition of Python dependencies listed in a section below, other software may be required, recommended or optional. uBridge is required, it interconnects the nodes. Dynamips is required for running IOS routers (using real IOS images) as well as the internal switches and hubs. VPCS is recommended, it is a builtin node simulating a very simple computer to perform connectitivy tests using ping, traceroute etc. Qemu is strongly recommended on Linux, as most node types are based on Qemu, for example Cisco IOSv and Arista vEOS. libvirt is recommended (Linux only), as it 's needed for the NAT cloud. Docker is optional (Linux only), some nodes are based on Docker. mtools is recommended to support data transfer to/from QEMU VMs using virtual disks. i386-libraries of libc and libcrypto are optional (Linux only), they are only needed to run IOU based nodes. Docker support needs the script program (bsdutils or util-linux package), when running a docker VM and a static busybox during installation (python3 setup.py install / pip3 install / package creation). master is the next stable release, you can test it in your day to day activities. Bug fixes or small improvements pull requests go here. Never use this branch for production. Pull requests for major new features go here. The following instructions have been tested with Ubuntu and Mint. You must be connected to the Internet in order to install the dependencies. You will find init sample scripts for various systems inside the init directory. All init scripts require the creation of a GNS3 user. You can change it to another user. If you want to test the current git version or contribute to the project, you can follow these instructions with virtualenvwrapper: and homebrew: . Please use GitHub's report a vulnerability feature. More information can be found in
Excerpt from the source-code README · 6,413 chars · not written by Vinony
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).