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Regression after the closing-slide removal surfaced a separate bug: _adapt_flat_spec() only emitted metadata + summary + cost, so decks generated from the MCP flat payload collapsed to 3-5 slides of title + summary. The deck generator's ECAL sections (service_tiering, architecture_principles, environment_catalogue, operational_raci, etc.) all check top-level spec keys the adapter never produced. Adapter now also emits, from the flat payload + kb/patterns defaults: - service_tiering from services[] (preserves any tier/uptime/rto/rpo) - architecture / architecture_principles (ECAL "always" picks) - ha_dr tiers derived from the distinct service tiers present - security baseline (IAM/network/database/monitoring controls) - environment_catalogue (Prod/Pre-Prod/Dev-Test, +DR if enabled) - operational_raci co_managed default from the KB - next_steps skeleton Flat MCP payload now renders 11 content slides instead of 3-5, and the proposal-spec.yaml path (non-flat) is unchanged — still 16 slides for examples/proposal-spec.yaml. Also documents the new data_services SKUs in docs/bom-cookbook.md as Recipe 4 (BDS/DS/DF) so MCP payloads can use the catalog codes directly. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
191 lines
6.7 KiB
Markdown
191 lines
6.7 KiB
Markdown
# BOM Cookbook — Building `generate_bom` Payloads
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Copy-paste recipes that map common customer requirements to the exact OCI SKUs the
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`generate_bom`, `generate_bom_appca`, and `generate_cost_estimate` MCP tools expect.
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The goal is to skip the "grep the catalog and guess SKUs" exploration loop that
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burns tool calls on well-known patterns.
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> **If the requirement does not match any recipe below, consult
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> [`kb/services/`](../kb/services/) and
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> [`kb/pricing/oci-sku-catalog.yaml`](../kb/pricing/oci-sku-catalog.yaml)
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> before inventing SKUs.** All SKUs below are verified against the catalog as of
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> 2026-04-20; re-`grep` the catalog if a recipe ever fails.
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## Payload Shape
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All three tools accept the same envelope:
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```json
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{
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"customer_id": "acme-prod",
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"discount_pct": 0.35,
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"currency": "USD",
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"services": [
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{ "sku": "B90777", "quantity": 1 }
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]
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}
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```
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- `customer_id`: free-form identifier, used for output file naming.
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- `discount_pct`: decimal (0.35 = 35%). Applied to every line unless overridden.
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- `services[].quantity`: integer or float depending on the SKU metric (ECPUs, GB, hours).
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---
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## Recipe 1 — Exadata Cloud Service (ExaCS) X11M, BYOL
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**When it matches:** "ExaCS X11M BYOL, N ECPUs, M TB storage, no DR" — customer-managed
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Oracle Database on dedicated Exadata hardware, BYOL licensing.
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**SKUs:**
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| SKU | Component | Typical qty |
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|-----|-----------|-------------|
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| `B90777` | Exadata Infrastructure — Base System | `1` per rack |
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| `B110627` | Exadata Database Server — X11M | `2` (Base/Quarter) — adjust per rack config |
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| `B110629` | Exadata Storage Server — X11M | `3` (Base/Quarter) — adjust per rack config |
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| `B110632` | Exadata Database ECPU — Dedicated Infra BYOL (X11M) | One per ECPU |
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Swap `B110632` → `B110631` for PAYG (license-included) pricing.
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**Payload (120 ECPUs, 120 TB, BYOL, standard Base System):**
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```json
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{
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"customer_id": "acme-exacs",
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"discount_pct": 0.35,
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"currency": "USD",
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"services": [
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{ "sku": "B90777", "quantity": 1 },
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{ "sku": "B110627", "quantity": 2 },
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{ "sku": "B110629", "quantity": 3 },
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{ "sku": "B110632", "quantity": 120 }
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]
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}
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```
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---
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## Recipe 2 — Autonomous Database Dedicated (ADB-D), BYOL
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**When it matches:** "ADB Dedicated, N ECPUs, M TB, BYOL" — Autonomous Database running
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on dedicated Exadata infrastructure.
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**⚠️ Gotcha that burns tool calls:** ADB-Dedicated has **no separate infrastructure
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SKUs** in the catalog. It reuses the same Exadata dedicated infra SKUs as ExaCS
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(`B90777`, `B110627`, `B110629`) plus the same Exadata ECPU SKU (`B110631`/`B110632`).
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The Autonomous-vs-customer-managed distinction is a tenancy-level configuration,
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not a billing line item. Do not search for `autonomous_dedicated` SKUs — they do
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not exist.
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**SKUs:** identical to Recipe 1.
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**Payload (64 ECPUs, BYOL):**
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```json
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{
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"customer_id": "acme-adbd",
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"discount_pct": 0.35,
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"currency": "USD",
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"services": [
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{ "sku": "B90777", "quantity": 1 },
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{ "sku": "B110627", "quantity": 2 },
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{ "sku": "B110629", "quantity": 3 },
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{ "sku": "B110632", "quantity": 64 }
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]
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}
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```
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---
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## Recipe 3 — Autonomous Database Serverless (ADB-S) + Block Volume + FastConnect
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**When it matches:** "ADB-S ATP, N ECPUs, M TB data + block storage for app tier +
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FastConnect to on-prem" — the typical "app on OCI Compute, DB on ADB-S" pattern.
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**SKUs:**
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| SKU | Component | Metric |
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|-----|-----------|--------|
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| `B95701` | ADB ECPU (ATP or ADW) — license-included | ECPU/hour |
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| `B95703` | ADB ECPU BYOL — use instead of B95701 if BYOL | ECPU/hour |
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| `B95706` | ADB ATP data storage | GB/month |
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| `B95754` | ADB ADW data storage — use instead of B95706 for warehouse | GB/month |
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| `B95754a` | ADB backup storage | GB/month |
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| `B91961` | Block Volume storage (app tier) | GB/month |
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| `B91962` | Block Volume performance (VPU) — optional, for higher IOPS tiers | VPU/GB/month |
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| `B88326` | FastConnect 10 Gbps port | port-hour |
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Swap `B88326` → `B88325` (1 Gbps) or `B93126` (100 Gbps) as needed.
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**Payload (16 ECPUs ATP license-included, 2 TB data + 1 TB backup, 500 GB block, 10 G FastConnect):**
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```json
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{
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"customer_id": "acme-adbs",
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"discount_pct": 0.35,
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"currency": "USD",
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"services": [
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{ "sku": "B95701", "quantity": 16 },
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{ "sku": "B95706", "quantity": 2048 },
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{ "sku": "B95754a", "quantity": 1024 },
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{ "sku": "B91961", "quantity": 500 },
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{ "sku": "B88326", "quantity": 1 }
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]
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}
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```
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---
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## Recipe 4 — Big Data Service + Data Science + Data Flow (analytics stack)
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**When it matches:** "HDFS-managed cluster for ETL", "notebooks + model deployment",
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"managed Spark pipelines" — typical OCI analytics/AI workload mix.
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**SKUs:**
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| SKU | Component | Metric |
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|-----|-----------|--------|
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| `B91128` | Big Data Service — Compute Standard (real) | OCPU/hour |
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| `B91129` | Big Data Service — Compute Dense I/O (real) | OCPU/hour |
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| `B91130` | Big Data Service — Compute HPC (real) | OCPU/hour |
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| `B93555` | Big Data Service — Core (real) | OCPU/hour |
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| `EST-DS-NOTEBOOK` | **[Estimate]** Data Science notebook session — priced as underlying VM.Standard OCPU | OCPU/hour |
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| `EST-DS-MODEL` | **[Estimate]** Data Science model-deployment endpoint — priced as underlying VM.Standard OCPU | OCPU/hour |
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| `EST-DF-SPARK` | **[Estimate]** Data Flow managed Spark runtime — priced as underlying VM.Standard OCPU | OCPU/hour |
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OCI Data Science and OCI Data Flow have no dedicated SKUs in the Oracle public
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pricing API — both are billed via the underlying Compute shape + Block/Object
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Storage consumed. The `EST-*` entries are placeholder estimates (VM.Standard3.Flex
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OCPU rate) so BOMs can include them as line items with an explicit "estimate"
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flag; confirm the actual shape and hours with the customer before quoting.
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**Payload (16 BDS Standard + 8 BDS Dense I/O + 4 notebook + 2 model + 8 Spark):**
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```json
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{
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"customer_id": "acme-analytics",
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"discount_pct": 0.30,
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"currency": "USD",
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"services": [
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{ "sku": "B91128", "quantity": 16 },
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{ "sku": "B91129", "quantity": 8 },
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{ "sku": "EST-DS-NOTEBOOK", "quantity": 4 },
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{ "sku": "EST-DS-MODEL", "quantity": 2 },
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{ "sku": "EST-DF-SPARK", "quantity": 8 }
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]
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}
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```
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Add `B91961` (Block Volume) and `B91628` (Object Storage Standard) when the
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customer needs dedicated storage beyond the compute default.
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---
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## When a recipe doesn't fit
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1. Grep the catalog: `grep -n "<product keyword>" kb/pricing/oci-sku-catalog.yaml`
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2. Check service docs under `kb/services/` for deployment-specific guidance.
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3. Check `kb/field-knowledge/` for known sizing/pricing gotchas.
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4. If a SKU still cannot be located, surface the gap to the user rather than guessing — fabricated SKUs break the BOM silently.
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