How well does S3 checkpointing hold up when running Airflow on spot?

Apr 28, 2026 · 9:04 PM UTC ·19 min read · 0 reactions · 0 comments · 32 views

#airflow #spot instances #kubernetes #s3 checkpointing #cost optimization

TL;DR · WeSearch summary

Running Airflow on spot instances can significantly reduce infrastructure costs, with potential savings from $21 per month on on-demand instances to around $1.44 using spot instances. The setup uses Kubernetes with spot nodes for both control plane and workers, relying on Airflow's retry and task isolation capabilities to handle preemptions. This article examines how well S3 checkpointing supports resilience during node preemption in such an architecture.

Key facts

▪Spot instances on Rackspace can cost as low as $0.001 per hour due to an auction-based pricing model.
▪The Airflow deployment uses KubernetesExecutor with ephemeral pods and distributes control plane components across two spot nodes for redundancy.
▪S3 is used for checkpointing in the ML workflow, storing datasets, models, and evaluation metrics to ensure continuity after preemptions.

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Original publisher	Rackspace
Canonical URL	https://spot.rackspace.com/blog/building-fault-tolerant-airflow-pipelines-on-spot-infrastructure
Publication time	Tue, 28 Apr 2026 21:04:02 +0000
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Introduction‍Airflow can be deployed on spot instances to significantly reduce infrastructure costs.Based on current Rackspace Spot pricing, two spot instances could cost around $1.44 per month, while a single on-demand instance with similar CPU and memory specifications comes to roughly $21 per month.That difference largely comes from how the Rackspace Spot auction-based market works. Pricing is driven by competitive bids, which allows users to access unused capacity at much lower prices, in some cases as low as $0.001 per hour. You can find more context in this article on spot instance history and market dynamics.This auction-based market maintains preemption rates below 1%, meaning interruptions tend to be infrequent.

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