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Production AI Radar

Prefect

Python-native workflow orchestration for data and ML jobs.

TrialMLOpsNew
Why this ring
Approachable for mid-market Python teams; assess Dagster when asset lineage is the main need.
Production risk if ignored
Flow sprawl without ownership - same problem as unmanaged Airflow DAGs.
Typical effort
weeks
Low FinOps impact

Use cases

  • ML pipelines
  • Eval batches
  • Ingestion schedules

Adoption steps

  1. Deploy Prefect
  2. Migrate one cron
  3. Wire notifications
  4. Tag cost center

Related tools

In your assessment

Flow inventory + SLAs