GPU orchestration is the software layer that schedules, allocates, and monitors GPU jobs across shared infrastructure. It decides which workload gets access to which accelerator, when jobs run, how memory and compute are divided, and how resources are reclaimed when a task finishes. In an AI platform, orchestration turns expensive GPUs into a pooled service instead of isolated machines.
It matters in cyber security because the orchestration plane controls privileged access to high-value compute and often to sensitive data paths. If it is misconfigured or compromised, attackers may steal capacity, spy on neighboring tenants, disrupt training jobs, or pivot through management APIs and cluster credentials. Defenders use orchestration for quotas, tenant isolation, logging, policy enforcement, and secure scheduling, making it a key control for multi-tenant AI systems and regulated research environments.