Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Architectural logic: Glue Jobs = serverless Spark; Triggers = orchestration (schedule, event, on-demand). Flow: Define job (script, DPU, timeout) → add Trigger (cron, e.g., 0 6 * * ? *) → chain jobs if needed. Job bookmarks enable incremental processing. Scalability: DPU...
Architectural logic: Glue Jobs = serverless Spark; Triggers = orchestration (schedule, event, on-demand). Flow: Define job (script, DPU, timeout) → add Trigger (cron, e.g., 0 6 ? *) → chain jobs if needed. Job bookmarks enable incremental processing. Scalability: DPU auto-scales; Triggers can fan-out. Cost: DPU-hours; over-provisioning wastes money. Best practice: Right-size DPUs; job bookmarks for incremental; scripts in S3; continuous logging to CloudWatch; Blueprint for multi-job workflows.
Red Flag: Full-scan jobs when incremental is possible. Pro-Move: 'We use job bookmarks and partition predicates—daily job processes only new partitions; DPU time dropped 70%.'
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