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compute-future-reservations

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Evaluates future GPU and TPU reservation feasibility and calendar-mode booking options in Google Compute Engine (GCE). Use when planning future AI/ML training runs, checking reservation availability windows, verifying accelerator cluster topologies, or assessing future capacity lead times. Don't use for active on-demand reservations (use compute-on-demand-reservations), immediate Spot capacity queries (use compute-spot-capacity-advice), or Standard Future Reservations (--reservation-mode=DEFAULT).

skills/cloud/compute-future-reservations/SKILL.md

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# Compute Engine Future Reservations & Calendar-Mode Feasibility

The `compute-future-reservations` skill assesses future capacity availability and feasibility for high-demand AI/ML hardware (NVIDIA GPUs, H4D VMs, and Google Cloud TPUs). It enables infrastructure engineers to evaluate future reservation windows, match cluster topologies, and manage calendar-mode bookings.

> [!NOTE]
> **Scope Boundary (Calendar Mode vs. Standard Future Reservations)**: This skill covers **Calendar-Mode Future Reservations** (`--reservation-mode=CALENDAR`, backed by Dynamic Workload Scheduler for up to 90 days on supported families such as `a3*`, `a4*`, `h4d*`, and Cloud TPUs; for newly released machine series, verify Calendar Mode support dynamically via `gcloud compute advice calendar-mode` or the official [Calendar Mode documentation](https://docs.cloud.google.com/compute/docs/instances/provisioning-models.md.txt#instance-availability)). Do not apply Calendar-Mode flags (`--reservation-mode=CALENDAR`, `--deployment-type=DENSE`) to **Standard Future Reservations** (`--reservation-mode=DEFAULT` for general-purpose CPU families, `a2*`/`g2*` GPUs, `DRAFT` planning workflows, or multi-month/CUD commitments).

## Usage Attribution

**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you MUST read and follow the instructions in [Usage Attribution](references/attribution.md).

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## Prerequisites, IAM & Billing
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