Scalability

Cloud-Native Execution

You can promote the same recommender.yaml from local development to OCI Data Science Jobs without rewriting your configuration.

# run locally for quick validation
ads operator run -f recommender.yaml

# submit to OCI Data Science Jobs (serverless)
ads operator run -f recommender.yaml -b job

The -b job flag uses your default job backend profile. Override shape, block storage, or networking by merging a backend config, for example:

ads operator run -f recommender.yaml -b backend_job_python_config.yaml

For detailed backend options see How To Run.

Data Throughput and Storage

  • Use Object Storage (oci:// URIs) for large interaction logs. The operator streams data through ADS I/O utilities, so you are limited primarily by network bandwidth.

  • For database sources, push filtering and aggregation into the sql statement to minimise data transfer. Supply connect_args such as wallet_dir or dsn for Autonomous Database connectivity.

  • When writing outputs back to Object Storage, point spec.output_directory.url to an oci:// URI so downstream AI Skills or Jobs can consume the artifacts.

Batch Size and Latency

Surprise SVD trains in-memory on the interaction matrix. To keep runs tractable:

  • Start with filtered cohorts (for example, a single region or product line) to validate signal before scaling out.

  • Increase compute shape (more OCPUs / memory) in the job backend when interaction counts grow beyond hundreds of thousands.

  • Consider sharding your audience and running the operator multiple times if you need very large coverage; you can merge the resulting recommendation CSVs downstream.

Operational Tips

  • Set spec.generate_report to false for automated batch runs to reduce artifact size.

  • Version control your YAML files and backend configs alongside infrastructure-as-code scripts so intake reviews can track exactly how the operator is used.

  • Monitor job logs in OCI Data Science to confirm the operator runs within expected time windows and to capture Surprise training diagnostics.