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Installation of Minikube on MacOS Minikube has emerged the easiest drop-in replacement for Docker Desktop. minikube is used to run a Kubernetes cluster on local environment. But it also runs a docker daemon that can be used to run containers. On macOS, minikube runs on a lot of virtualization technologies, but hyperkit is the easiest to use. Install Hyperkit and Minikube brew install hyperkit brew install minikube Install Docker CLI brew install docker brew install docker-compose Start minikube minikube start Tell Docker CLI to talk to minikube’s VM eval $(minikube docker-env) Save IP to a Hostname echo "`minikube ip` docker....

SSH into a running Container on Minikube If you only need to forward some exposed container ports out of Minikube so they are accessible on your host machine, you can run an SSH tunnel. This is useful if you are using Minikube as a Docker Desktop replacement and aren’t running K8s services. For example, forward traffic on exposed container port 8000 to the host machine on port 8000: ssh -g -L 8000:localhost:8000 -N -i ~/....

Brew Cleanup Brew cleanup frees up space in macOS and Linux devices by removing old versions of formulae and small kegs of data. Let’s look at sample instructions: Remove a Formula $ brew cleanup <formula> # clean everything up at once $ brew cleanup We can access “help” using -h. $ brew cleanup -h brew cleanup [--prune=days] [--dry-run] [-s] [formulae]: For all installed or specific formulae, remove any older versions from the cellar....

Login to AWS with SSO instead of Credentials File Setup AWS IAM Follow the steps described in: https://docs.aws.amazon.com/singlesignon/latest/userguide/what-is.html Create a IAM user After completing the steps described in the documentation above, you should have An IAM user An assigned SSO role to that user A Start URL for your SSO Login page On your local profile you should find under “~/.aws/config” a section looking like this: [profile <profile-name>] sso_session = <username> sso_account_id = <some-id> sso_role_name = <selected role, e....

Selecting a Python Virtual Environment in VS Code for Jupyter Notebooks Follow these steps to select a Python virtual environment located in the .venv/ directory of your current workspace for use with Jupyter notebooks in Visual Studio Code (VS Code). Open Command Palette Press Ctrl+Shift+P (Windows/Linux) or Cmd+Shift+P (macOS) to open the Command Palette. Select Interpreter Type Python: Select Interpreter and hit Enter. Choose the .venv Environment From the list, select the interpreter that corresponds to your ....