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Design Batch Reboots for Machines

Last updated: May 14, 2026

Quick Overview

This question evaluates a candidate's competency in designing reliable, capacity-aware operational systems for large-scale machine management, including orchestration, failure handling, state tracking, observability, and integration with infrastructure services.

  • medium
  • Coreweave
  • System Design
  • Site Reliability Engineer

Design Batch Reboots for Machines

Company: Coreweave

Role: Site Reliability Engineer

Category: System Design

Difficulty: medium

Interview Round: Onsite

Design a production system that can safely batch reboot `N` machines in a fleet. Context: You operate a large fleet of machines used for production workloads. Operators need a reliable way to reboot many machines, for example after kernel upgrades, hardware remediation, firmware updates, or node recovery. The system must avoid taking down too much capacity at once and must provide visibility into progress and failures. Address the following: 1. How users submit a batch reboot request. 2. How the system selects and validates the target machines. 3. How to schedule reboots in safe batches or waves. 4. How to prevent service-impacting outages. 5. How to track machine state before, during, and after reboot. 6. How to handle failures, retries, timeouts, and partial completion. 7. How the system should integrate with infrastructure such as Kubernetes or a machine inventory service. 8. What observability, auditability, and safety controls are required.

Quick Answer: This question evaluates a candidate's competency in designing reliable, capacity-aware operational systems for large-scale machine management, including orchestration, failure handling, state tracking, observability, and integration with infrastructure services.

Coreweave logo
Coreweave
Feb 13, 2026, 12:00 AM
Site Reliability Engineer
Onsite
System Design
4
0
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Design a production system that can safely batch reboot N machines in a fleet.

Context: You operate a large fleet of machines used for production workloads. Operators need a reliable way to reboot many machines, for example after kernel upgrades, hardware remediation, firmware updates, or node recovery. The system must avoid taking down too much capacity at once and must provide visibility into progress and failures.

Address the following:

  1. How users submit a batch reboot request.
  2. How the system selects and validates the target machines.
  3. How to schedule reboots in safe batches or waves.
  4. How to prevent service-impacting outages.
  5. How to track machine state before, during, and after reboot.
  6. How to handle failures, retries, timeouts, and partial completion.
  7. How the system should integrate with infrastructure such as Kubernetes or a machine inventory service.
  8. What observability, auditability, and safety controls are required.

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