Infrastructure · Software component

Scheduled Scaler

Software componentInfrastructureInfrastructurearc:ScheduledAutoscaler

An autoscaler that deploys known capacity at known times according to a schedule rather than reacting to live metrics.

Responsibility. Applies predetermined replica counts on a time schedule.

Also known as: Scheduled scaling, Pre-warming nodes for anticipated peaks, Time-based scaling, CronJob scaling schedule

Variant of Autoscaler abstract

When to choose. Choose when traffic patterns are extremely predictable, making schedule-based capacity simpler and equally effective.

Direct neighbourhood (hover for relationship types)

Relationships

As stated by the sources; verify before use.

Example schedule 25 replicas at 08:00, 8 at 18:00, 2 at 00:00; time-based scaling cut a 50-GPU A100 fleet from $108,000 to $43,200/month (60% saving) (Ch7.5).

Patterns: Scheduled scaling
Quality attributes: Maintainability (ISO/IEC 25010)Reliability (ISO/IEC 25010 | NIST AI RMF: valid and reliable)
Risks mitigated: Scale-up lag violating latency SLAs

Ch1.8: T. Nguyen, "Scalability and Production Deployment," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.8. ISBN: 9798244538229.
Ch7.5: T. Nguyen, "NeMo Curator, Riva Speech AI & Multimodal Integration," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 7.5. ISBN: 9798244538229.
Ref4.03: M. Zhang, J. Wyman, I. M. Bhosale, and W. Tan, "Scaling LLMs with NVIDIA Triton and NVIDIA TensorRT-LLM using Kubernetes," NVIDIA Technical Blog, Oct. 22, 2024. [Online]. Available: https://developer.nvidia.com/blog/scaling-llms-with-nvidia-triton-and-nvidia-tensorrt-llm-using-kubernetes/
Ref7.17: "Scaling Agentic AI Systems: Patterns and Strategies," unpublished reference note (17-Scalability-Patterns.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note