0.3.0
- Fixed broken passing of
zone and project arguments in gce_vm, gce_vm_template, gce_get_external_ip, and gce_set_metadata.
- remove
gce_auth() to favour auth with JSON key (#79)
- Fix project-id error if numbers in project (#72)
- Block users using “rstudio” as a login name
- Remove defunct example from
gce_schedule_docker
- Support GPU images for Tensorflow, keras etc. (#101) via
gce_vm_gpu() and gce_vm(template = "rstudio-gpu") (#101)
- Support common instance metadata by supply
gce_set_metadata(instance = "project-wide")
- Support minCpuPlatform in instance creation and via
gce_set_mincpuplatform() (#112)
- Add ability to specify a startup-script in
gce_vm_container()
- Switch RStudio templates to use startup-scripts and metadata
- Switch to applying a nginx proxy service to deal with port routing for templates
- Add
gce_startup_logs() to track whts going on when launching an instance
- Vectorise
gce_vm_delete, gce_vm_stop, gce_vm_start and gce_vm_reset functions so you can pass in a list of instances
- Add
gce_vm_cluster() to make it easier to create clusters for future
0.2.0
Changes
- Update website
- Bug fixes
- Add R-Datalab Dockerfile example
- Let Rstudio users be added with staff rights so they can install packages etc.
- Add ability to specify disk size when creating a VM (#38) - thanks @jburos
- Add firewall functions (#34)
- Add global operation class
- Add
open_webports argument to gce_vm that will open web ports 80 and 443 if necessary
- Add GPU functions
- Migrate to use
system2 instead of system for cross-platform SSH (#35)
gce_shiny_addapp is now much more useful
- Add
gce_schedule_docker and gce_vm_scheduler for easy Dockerfile scheduling
- Add
gce_vm_logs to quickly browse to an instance logs online
- Fix custom machine types creation (#63) - thanks @Blaza
- Set environment vars on VMs from metadata via
gce_metadata_env
0.1.0
Major changes
- Start, stop and restart VMs
- Create instances using cloudinit
- Browser based SSH
- SSH from R
- Metadata
- Docker
- Google container registry
- VM templates
- Future asynch cluster computing