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code.v1.dodo.cloud / pcloud / 3ea9049184909283dc10ad436ccbaa5c75b870ba
commit3ea9049184909283dc10ad436ccbaa5c75b870ba[log] [tgz]
authorgiolekva <giolekva@gmail.com>Thu Mar 26 12:36:23 2020 +0400
committergiolekva <giolekva@gmail.com>Thu Mar 26 12:36:23 2020 +0400
tree5cc152c1c1535d84332e1fbdafb8448f12c3de16
parent53bcdf4673cb643df424a4fc9990d2310b277b7b [diff]
fix k8s config
3 files changed
tree: 5cc152c1c1535d84332e1fbdafb8448f12c3de16
  1. api/
  2. chunk/
  3. client/
  4. controller/
  5. docs/
  6. k8s/
  7. testing/
  8. .gitignore
  9. chunk_server.go
  10. client.go
  11. controller_server.go
  12. Dockerfile
  13. README.md
README.md

PCloud

PCloud is a set of distributed infrustructure tools meant for setting up a personal cloud on commodity hardware such as Raspberry Pi. Goal of the project is to provide:

  • Blob storage: distributed file storage with configurable replication for redundancy
  • Namespace service: built on top of Blob storage to expose it, at least in read only mode, as a mountable file system
  • Metadata service: storing Blob annotations such as objects and their locations detected in the pictures
  • Search infrastructure: to index Blob metadata and provide search API
  • App infrastructure: to easily set up and run third party applications such as custom in picture object detection models

To prove viability of the project first milestone will be to build fully functional image storage and indexing infrustructure. User experience setting it up will look something like:

  • Set up PCloud on 3 or more servers and pair mobile device with it
  • Configure IFTTT (if this then that) like worklfow to automatically:
    • Back up every newly taken picture on PCloud
    • Run face detection app on backed up pictures and store this information in Metadata service
    • Index face annotations and make them searchable

User must be able to configure all of these from previously paired mobile device.