Media Curator
A personal automation project for coordinating media-management services. The engineering focus is API integration, persistent state, scheduling and decisions that account for finite storage.
02 / Problem
Problem
Related media-management services expose separate APIs and do not automatically share one view of scheduled work or available storage. Manual coordination makes it harder to understand what should run next.
03 / Objectives
Objectives
Coordinate service APIs through a manageable automation layer, persist application state and incorporate storage constraints into scheduled decisions.
04 / ARCHITECTURE
Follow the components.
- Scheduled work
- Python coordinator
- Service APIs
- SQLite state
- Storage constraints
05 / Implementation
Implementation
The project uses Python with Docker deployment and SQLite state, integrating media-management APIs with scheduling and storage-aware automation. The project boundary is service coordination; it does not replace the services themselves.
06 / SECURITY
Security boundaries
- Service API credentials and private endpoints are omitted.
- The public write-up concerns automation and storage management.
- Remote deployment health is not inferred from overlay connectivity.
07 / Testing
Testing
This account describes the existing implementation supplied in the project brief. The separate media host was reachable on the private overlay, but its application logs and test results were not available for a fresh audit. No uptime, throughput or automated-test result is claimed here.
08 / Challenges
Challenges
API state, scheduler state and physical free space are different inputs. An integration needs to make failures visible rather than allowing a successful API request to stand in for a completed workflow.
09 / Lessons
Lessons
Useful automation keeps the operator’s constraints visible. The next verification pass should inspect scheduled runs, failure handling and storage decisions on the actual deployment before publishing performance claims.