Sarcouncil Journal of Engineering and Computer Sciences

Abstract: Hyperscale cloud and distributed artificial intelligence (AI) infrastructures enforce five-nines (99.999%) availability, permitting ≤ 5.26 minutes of annual node downtime. In gang-scheduled AI clusters scaling to 32,768 accelerators, a single node reboot stalls synchronous AllReduce collective barriers, desynchronizes parameters, aborts training, and strands ~30 MWh of energy. Consequently, engineers cannot afford downtime for security patching, microcode remediation, or driver upgrades. This paper presents an architectural survey of hitless firmware and software upgrades across cloud and AI datacenters. We formalize a five-tier taxonomy spanning silicon microcode, peripheral controllers, accelerators, operating systems, and userspace data planes. We analyze state preservation via PCIe SerDes Link L0 keep-alive, Completion Timeout Range C extensions, dynamic ftrace livepatching, and SCM_RIGHTS socket migration. We evaluate critical edge cases, including voltage regulator load-line transients (dI/dt) and IEEE 1588 PTP holdover. Finally, we examine Hardware-in-the-Loop chaos validation, canary pipelines, and empirical deployments across Google Jupiter OCS, Titanium, Andromeda 2.2, and Cloud SQL.