Where to start
- Start - how to get access to the cluster and intros
- Get access: Getting authenticated in the cluster
- Quick start: Basic info, links to external tutorials
- Policies: VERY IMPORTANT section! Please read to avoid issues running in the cluster
- Available resources: Additional resources you can get in the cluster
- Tutorials - step-by-step tutorials for working with the cluster
- Docker: Using docker locally, finding and building containers
- Basic kubernetes: Exrloding the system, running simple pods
- Scaling and exposing: Scaling, load balancing, exposing services to outside
- Scheduling: Scheduling and requesting resources
- Batch jobs: Running batch jobs
- Images: How to choose the right container image or build your own
- Storage: Using persistent storage in the cluster
- Running: running various kinds of jobs in the cluster efficiently
- Jupyter&Tensorflow2 example: A comprehensive example on how to run the image we provide, containing most popular python libraries for ML
- Running batch jobs
- Dealing with high I/O
- Running permanent services
- Idle pods: How to run “login” pods
- GPUs: Requesting GPUs
- Client scripts: How to use a script from your laptop and not get blocked
- More computing resources: How to get maximum from the cluster
- Storage: accessing persistent storage in the cluster
- Ceph storage: How to get persistent filesystem attached to your pod
- Ceph S3: Better scalable Object storage for billions of files
- Local: Attaching high-speed local scratch space
- Nextcloud: How to share your data and move data into the cluster
- Development: building your own containers and working with your own code efficiently
- GitLab: Getting access to unlimited space and CI/CD for your projects through our hosted GitLab
- Private repo: How to keep your project private and work with it in Nautilus