The article also provides a guide on how to install and configure `dstack`. It explains how to set up a `dstack` server, configure backends, start the server, and set up the CLI. It also outlines how `dstack` works, including defining configurations and applying them either via the `dstack apply` CLI command or through a programmatic API. The article concludes by inviting contributions to the `dstack` project and providing links for additional information and examples.
Key takeaways:
- `dstack` is an alternative to Kubernetes and Slurm, designed for AI, simplifying container orchestration for AI workloads in the cloud and on-prem.
- `dstack` supports `NVIDIA GPU`, `AMD GPU`, and `Google Cloud TPU` out of the box.
- It allows users to define configurations for different aspects like dev environments, tasks, services, fleets, volumes, and gateways.
- `dstack` can be installed and configured via CLI or API, and it can be used with any cloud provider or on-prem servers.