Anchore uses a local directory for image analysis operations including downloading layers and unpacking the image content for the analysis process. This space is necessary on each analyzer worker service and should not be shared. The scratch space is ephemeral and can have its lifecycle bound to that of the service container.
The layer cache is an extension of the analyzer’s scratch space that is used to cache layer downloads to reduce analysis time and network usage during the analysis process itself. See: Layer Caching
Anchore Engine is a data intensive system and uses external storage systems for all data persistence. None of the services are stateful in themselves.
For structured data that must be quickly queried and indexed, Anchore relies on PostgreSQL as its primary data store. Any database that is compatible with PostgresSQL 9.6+ should work (e.g. Amazon Aurora, Google Cloud SQL,…).
For less structured data, Anchore implements an internal object store that can be overlayed on different backend providers, but defaults to also using the main postgres db to reduce the out-of-the-box dependencies. However, S3 and Swift APIs are both supported for leveraging external systems.
For more information on configuration and requirements for the core database and object stores see: Object Storage
To aid in capacity management, anchore provides a separate storage location that completed image analysis can be moved to in order to reduce consumption of database capacity and primary object storage and remove the analysis from most API actions but make it available to restore into the primary storage systems in the future as needed. The analysis archive is configured as an alternate object store. See: Configuring Analysis Archive for more information.
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