BMC, out-of-band, and TPM initial configuration: Worked Example — System and Server Bring-up (NVIDIA-Certified Professional: AI Infrastructure)

Introduction

In the NVIDIA-Certified Professional: AI Infrastructure certification, System and Server Bring-up is a critical domain that includes configuring essential hardware management components. This worked example focuses on the initial configuration of the Baseboard Management Controller (BMC), out-of-band management, and the Trusted Platform Module (TPM) in a GPU-based AI server environment.

Scenario Overview

You are tasked with bringing up a new AI server node equipped with NVIDIA GPUs. The server requires proper setup of the BMC for remote management, enabling out-of-band (OOB) access for system administrators, and initializing the TPM to secure platform integrity. This setup ensures reliable monitoring, firmware control, and hardware security before deploying AI workloads.

Step 1: Accessing the BMC Interface

• Identify the BMC IP address: Use DHCP logs or server documentation to find the assigned IP or configure a static IP via the server's BIOS/UEFI.
• Connect to the BMC: Open a web browser or use a command-line tool (e.g., IPMItool) to access the BMC interface via HTTPS or IPMI protocol.
• Authenticate: Log in using default credentials provided by the hardware vendor, then immediately change to a secure password to prevent unauthorized access.

Step 2: Configuring Out-of-Band Management

• Enable OOB access: Within the BMC settings, enable remote management protocols such as IPMI, Redfish, or SSH depending on server capabilities.
• Set network parameters: Configure VLANs, static IPs, and gateway settings to ensure the BMC is reachable from the management network.
• Configure user roles: Create and assign user roles with appropriate privileges for administrators and operators.
• Test connectivity: From a management workstation, ping the BMC IP and attempt remote login to verify OOB access.

Step 3: TPM Initial Configuration

• Verify TPM presence: Access the server BIOS/UEFI to confirm the TPM module is detected and enabled.
• Initialize TPM: Use BIOS/UEFI options or vendor tools to initialize the TPM, which may include clearing previous ownership and setting new ownership credentials.
• Configure TPM settings: Enable features such as measured boot and secure storage if supported.
• Validate TPM status: Within the operating system or management software, check TPM readiness and health status.

Step 4: Firmware Upgrades and Fault Detection

• Check firmware versions: Use BMC interface to view current firmware for BMC, TPM, and other components.
• Apply updates: Upload and install firmware updates as recommended by NVIDIA and hardware vendors to ensure security and stability.
• Monitor fault logs: Review BMC event logs for hardware errors or warnings and address any detected issues.

Worked Example: Configuring BMC, OOB, and TPM on an NVIDIA GPU Server

Step 1: The server’s BMC IP is found to be 192.168.1.100 via DHCP logs. Accessing https://192.168.1.100 prompts for login.

Step 2: Logging in with default credentials admin/admin, immediately change the password to a strong one. Enable IPMI and Redfish protocols under remote management settings. Assign static IP 192.168.1.100 with gateway 192.168.1.1 on VLAN 10.

Step 3: Reboot server, enter BIOS, confirm TPM 2.0 is enabled. Initialize TPM by clearing previous ownership and setting a new owner password. Enable measured boot.

Step 4: Check firmware versions: BMC v1.2.3, TPM firmware v4.5. Update BMC firmware to v1.2.5 using vendor tool. Review BMC logs—no faults detected.

Outcome: The server is now remotely manageable via BMC with secure OOB access, and TPM is initialized to provide hardware security for AI workloads.

Conclusion

Proper initial configuration of the BMC, out-of-band management, and TPM is essential for secure and reliable AI infrastructure deployment. This step-by-step approach ensures administrators can remotely monitor and manage GPU servers while maintaining platform integrity and security, aligning with best practices tested in the NVIDIA-Certified Professional: AI Infrastructure exam.

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