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In today's cloud-native landscape, GPU workloads are becoming increasingly critical. From training large language models to running inference APIs, organizations are investing heavily in GPU infrastructure. But with this investment comes a challenge: how do you safely test and deploy new GPU schedulers without risking your entire production environment?

Related talks: Watch my SREDay Paris Q4 2025 talk on this topic. Also presenting at Conf42 Kube Native 2025. Check the talks page for more details.

This technique is useful when a program you can't modify calls CLI tools on your machine. For example, pet search pipes output directly to fzf with no filtering options. PATH hijacking lets you intercept and modify this behavior without changing either program.

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Introduction​