Cloud Controller

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Cloud Controller in Cloud Foundry Application Runtime provides you with REST API endpoints to access the system. Cloud Controller maintains a database with tables for orgs, spaces, services, user roles, and more.

Refer to the following diagram for information about internal and external communications of the Cloud Controller.

Internal and external Cloud Controller communications

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Diego Auction

The Cloud Controller uses the Diego Auction to balance application processes over the Diego Cells in a Cloud Foundry installation.

Database (CC_DB)

The Cloud Controller database has been tested with Postgres and MySQL.


To stage and run apps, Cloud Foundry manages and stores the following types of binary large object (blob) files:

Blob Type Description Location in Blobstore
App Packages Full contents of app directories, including source code and resource files, zipped into single blob files. /cc-packages
Buildpacks Buildpack directories, which Diego cells download to compile and stage apps with. /cc-buildpacks
Resource Cache Large files from app packages that the Cloud Controller stores with a SHA for later re-use. To save bandwidth, the Cloud Foundry Command Line Interface (cf CLI) only uploads large application files that the Cloud Controller has not already stored in the resource cache. /cc-resources
Buildpack Cache Large files that buildpacks generate during staging, stored for later re-use. This cache lets buildpacks run more quickly when staging apps that have been staged previously. cc-droplets/buildpack_cache
Droplets Staged apps packaged with everything needed to run in a container. /cc-droplets

Cloud Foundry blobstores use the Fog Ruby gem to store blobs in services like Amazon S3, WebDAV, or the NFS filesystem. The file system location of an internal blobstore is /var/vcap/store/shared.

A single blobstore typically stores all five types of blobs, but you can configure the Cloud Controller to use separate blobstores for each type.

Automatic blob cleanup

After a blob deletion fails silently or something else goes wrong, the blobstore might contain blobs that the Cloud Controller no longer needs or lists in its database. These are called orphan blobs, and they waste blobstore capacity.

Cloud Controller detects and removes orphan blobs by scanning part of the blobstore daily and checking for any blobs that its database does not account for. The process scans through the entire blobstore every week, and only removes blobs that show as orphans for three consecutive days.

Cloud Controller performs this automatic cleanup when the cloud_controller_worker job property cc.perform_blob_cleanup is set to true.

Manual blob cleanup

Cloud Controller does not track resource cache and buildpack cache blob types in its database, so it does not clean them up automatically as it does with app package, buildpack, and droplet type blobs.

To clean up the buildpack cache, admin users can run cf curl -X DELETE /v2/blobstores/buildpack_cache. This empties the buildpack cache completely, which is a safe operation.

To clean up the resource cache, delete it as follows:

  • Internal blobstore: Run bosh ssh to connect to the blobstore VM (NFS or WebDav) and rm * the contents of the /var/vcap/store/shared/cc-resources directory.
  • External blobstore: Use the file store’s API to delete the contents of the resources bucket.

Do not manually delete app package, buildpack, or droplet blobs from the blobstore. To free up resources from those locations, run cf delete-buildpack for buildpacks or cf delete for app packages and droplets.


By default rspec runs a test suite with the SQLite in-memory database. Specify a connection string using the DB_CONNECTION environment variable to test against Postgres and MySQL. For example:

    DB_CONNECTION="postgres://postgres@localhost:5432/ccng" rspec
    DB_CONNECTION="mysql2://root:password@localhost:3306/ccng" rspec

Travis currently runs two build jobs against Postgres and MySQL.

For more information about how Cloud Foundry aggregates and streams logs and metrics, see Overview of Logging and Metrics.

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