ansible

Containerlab is rapidly emerging as a viable solution on macOS, thanks to the increasing availability of ARM64-based NOS container images. The following Containerlab kinds work excellent with macOS on Apple Silicon: Nokia SR Linux Arista cEOS Cisco IOL with Rosetta Prerequisites Mac computer with Apple silicon macOS 13.0 or later Git Steps Download OrbStack and open it. Open your favorite terminal emulator. We will work from the command line for the following steps. ...

Before we work our way through the steps, I will start by pointing out GNS3 server has the following constraints when running on Apple Silicon: Lack of Linux KVM for x86_64 virtualized guests Slight performance penalty with emulated x86_64 Linux binaries (Rosetta ) The following are my results after testing a number of different Cisco device types: Device Working? Information IOL ✅ - IOL L2 ✅ - IOSv ✅ - IOSv L2 ✅ - ASAv ❌ Requires SSSE3 CPU instructions for cryptographic operations Catalyst 8000V ❌ Requires vmx or svm CPU flag for Linux KVM Nexus 9000v ❌ Requires vmx or svm CPU flag for Linux KVM As you can see, we’re primarily limited to Cisco (IOL , IOSv , Dynamips ) images, VPCS, and Docker containers. The upside is that we’re rarely CPU-bound running labs on Apple Silicon. The amount of system memory in the Mac is usually the limiting factor. And let’s face it: connecting to a dedicated x86_64 GNS3 compute server with ample CPU cores and RAM is the ideal solution for running large labs. ...

Microsoft Azure is one of the big three public cloud computing providers for services such as virtual machines (VMs), containers, server-less computing, and machine learning. Azure is a large platform, but we’re focused solely on the Infrastructure as a Service (IaaS) resources in this guide. The GNS3 architecture is comprised of three primary components: User Interface (UI), Controller, and the (Compute) Server. The Server is the component that puts a strain on computer hardware resources. The more routers, switches, firewalls, and servers we add to our GNS3 topologies, the more CPU, RAM, and data storage we require. We usually come to a point where the hardware requirements of our GNS3 labs may exceed what our laptops and desktops can deliver. ...