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AI for OpenStack Difficulty: Intermediate ClaudeChatGPT

Blazar Host Reservation and Lease Design Prompt

Design Blazar resource reservation — dedicated host leases, instance reservations, and capacity carve-outs without starving general scheduling.

Target user
OpenStack architects offering reserved/dedicated capacity
Difficulty
Intermediate
Tools
Claude, ChatGPT

The prompt

You are a senior OpenStack operator who has run Blazar (resource reservation) in production and understands host plugins, instance plugins, lease lifecycle (start/end/before_end), and Blazar's interaction with Nova host aggregates and the placement service.

I will provide:
- The reservation goal (dedicated hosts for a team, time-boxed burst capacity, reserved flavors)
- Current cloud capacity, host aggregates, and Nova scheduler filters in use
- Tenant/project demand and the SLA you must honor
- Any existing Blazar config and freepool host count

Your job:

1. **Choose the plugin** — host reservation (whole hosts via the freepool) vs instance reservation (capacity slices), with the trade-offs of each.
2. **Design the freepool** — which hosts to dedicate, how the reservable aggregate interacts with the general scheduling pool, and headroom to keep.
3. **Model the lease lifecycle** — start_date/end_date behavior, before_end actions (snapshot vs default), and what happens to running instances at lease end.
4. **Integrate with the scheduler** — required AggregateInstanceExtraSpecsFilter / reservation filter config so reserved hosts are not used by general workloads.
5. **Plan capacity math** — ensure carve-outs don't starve the general pool; compute overcommit and failure-domain impact.
6. **Define tenant UX** — how users request leases, quotas on reservations, and notifications before expiry.
7. **Add guardrails** — monitoring on freepool exhaustion and lease-end reclamation.

Output as: a capacity allocation table, a recommended plugin + lease policy, the exact `openstack reservation lease create` examples, and the scheduler/aggregate config required.

Caution: lease end can terminate or snapshot running instances depending on policy — make the end-of-lease action explicit so tenants are not surprised by data loss.

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