Podman Desktop

1. Start a local Kubernetes cluster using Kind or Minikube.

2. Deploy your application's YAML configuration.

3. Access your application through the exposed service.

4. Debug your application using logs and metrics.

1. Build a container image from a Containerfile.

2. Push the image to a container registry (Docker Hub, Quay.io).

3. Pull the image from the registry to your local machine.

4. Start a container from the image.

1. Identify the container or pod experiencing issues.

2. Access the container's logs through the Podman Desktop interface.

3. Monitor the container's metrics for performance bottlenecks.

4. Use debugging tools to diagnose and resolve issues.

1. Develop your application on your preferred operating system.

2. Build a container image from your application's source code.

3. Run the container image on any supported platform.

4. Test your application to ensure cross-platform compatibility.

1. Install Podman Desktop and Podman.

2. Configure Podman to use the same container registries as Docker.

3. Import your Docker Compose files into Podman Desktop.

4. Run your applications using Podman.

1. Configure Podman Desktop to use your GPU.

2. Build a container image with your AI model and dependencies.

3. Run the container with GPU acceleration enabled.

4. Train and test your AI model.