30-Day On-Prem GPU Pod Pilot Checklist for Security and ISSM Review

The fastest way to waste an on-prem GPU pilot is to treat it like a hardware demo. A team installs the pod, runs a few workloads, confirms the GPUs work, and calls the exercise successful. Then the ISSM joins the production review and asks: How are identities managed? What leaves the environment? Where are logs retained? What happens when something fails? Who can administer the system? Those are pilot questions, not post-pilot questions.

If you are evaluating an on-prem GPU deployment for a security-sensitive environment, the 30 days should test whether the entire operating model works — identity, data movement, logging, support, and failure — not whether a card enumerates. Start with Pacific’s CMMC-oriented writeup on on-prem GPU infrastructure for CUI and ITAR and the mothership’s GPU capacity options. This page is a checklist for that evaluation. It is not a second product homepage.

Week 1: Prove the security boundary

Start with the boundary before benchmarking throughput. Document every network path into and out of the pod. Test administrative access, identity controls, service accounts, outbound connectivity, remote support procedures, and the path used to move models or datasets into the environment. The security lead should be able to answer basic questions without relying on architecture diagrams that describe some future production state.

Verify:

• Who can authenticate and administer the pod.
• Which systems the pod can communicate with.
• What telemetry or support data can leave the environment.
• How credentials and privileged access are handled.
• Whether relevant security events appear in the customer’s existing logging workflow.

The objective is not to claim that installing infrastructure makes an organization CMMC certified. It does not. Pacific does not make a customer CMMC certified. The purpose of week one is to test whether the compute architecture can operate within the organization’s required controls and evidence processes. If you still need a deployment-model contrast after that, stay on pacific.space/comparisons — do not expect those versus-pages to be re-hosted here.

Week 2: Run the workloads that can actually kill the project

A generic CUDA benchmark tells you very little. Use representative workloads — training, fine-tuning, inference, simulation, or data-processing that resembles production. Test the complete path from data ingestion to execution to artifact retrieval. Record where engineers still need manual intervention. Pay attention to container compatibility, drivers, storage throughput, orchestration, model dependencies, internal registries, job scheduling, and how users request compute.

The real question is whether your existing ML workflow can move onto the pod without creating a second infrastructure stack nobody wants to maintain. If capacity planning is part of the exercise, read reserved GPU capacity rather than extrapolating from synthetic tests.

Week 3: Break the operating model deliberately

A production GPU environment will encounter failed jobs, unavailable nodes, bad deployments, exhausted storage, expired credentials, or networking problems. Use the pilot to find out what happens next. Trigger recoverable failure conditions where appropriate. Confirm alerts reach the right people, logs contain enough to diagnose, administrators understand escalation, and workloads can return to a known state.

Security should participate. An infrastructure design can look clean during normal operation and become much less controlled when engineers debug under pressure. For a contrast of deployment models — on-prem, reserved, cloud — keep the writeups on the mothership comparisons index.

Week 4: Make the production decision from evidence

The last week should produce a decision packet, not another demo. Bring infrastructure, ML, security, and the ISSM back into the same room. Review what was proven, what failed, and what would have to change before production.

Final checklist:

• Workload compatibility.
• Observed performance against representative jobs.
• Network dependencies.
• Identity and privileged access.
• Logging and evidence.
• Support procedures.
• Failure recovery.
• Operational ownership.
• Unresolved security requirements.

Three questions decide the packet. Can the intended workloads run? Can the organization operate the environment safely? What specific work remains before production? When the answers are written down, book a 30-minute discussion with Harper. Pacific Intelligent Technologies, Inc. can help structure the compute and security evaluation without turning the pilot into a generic proof-of-concept. The calendar is the only booking path.

FAQ

What should an ISSM review during an on-prem GPU pilot?

The boundary, not the benchmark. Admin access, network paths, identity, logging, data movement, remote support, privileged operations, and incident handling. If those answers only exist as a future-state diagram, the pilot is not done. Pacific’s public control-boundary writeup is pacific.space/cmmc.

Should we benchmark GPUs during the pilot?

Yes — on representative workloads, not only synthetic CUDA scores. Benchmarking is useful after the boundary is documented, and only if the job path resembles production. For capacity planning, use Pacific GPU capacity options rather than treating a lab number as a reservation.

Is a successful pilot enough to establish CMMC compliance?

No. A successful pilot shows whether the operating model can sit inside the organization’s controls. It does not certify the organization. Pacific does not make a customer CMMC certified. Read that limit on the mothership CMMC page before anyone treats a signed-off pilot as a program close.

How should we compare an on-prem pod with other GPU deployment models?

Compare the complete operating model: boundary, identity, logging, support, failure, and ownership — not a single throughput slide. Vendor-versus-vendor and deployment-model writeups stay on pacific.space/comparisons. Start from pacific.space if you still need the mothership index. Do not expect this satellite to become a second comparison catalog.