b48d155c1b
6 CLI improvements from MCP integration testing + deck bug fixes: - kb_cli.py: --json on search, new arch-search and ecal-score subcommands, _load_yaml handles multi-document YAML (fixes health command on 32 files) - findings_cli.py: --json on search/list/stats, filter flags on search (--product, --severity, --tag, --client, --status, --category) - validate-architecture.py: --profile optional, --output defaults to stdout - common-objections.yaml + ecal-artefacts-catalog.yaml: merge front matter - oci_deck_gen.py: fix slide 9 cost_notes char iteration, fix slide 12 migration field mapping (duration/milestones), dynamic phase spacing - proposal-spec.yaml: replace real name with fictional Carlos Mendoza All 14 skill options validated with generated deliverables. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
126 lines
5.2 KiB
JSON
126 lines
5.2 KiB
JSON
[
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{
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"id": "FF-202603-008",
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"date": "2026-03-14",
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"contributor": {
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"name": "Diego Cabrera",
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"team": "Field Architecture",
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"client": "Vector Search Customer",
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"context": "AI Vector Search engagement",
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"confidence": "validated"
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},
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"product": "ADB-S",
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"version": "23ai",
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"severity": "HIGH",
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"category": "limitation",
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"summary": "Distributed HNSW indexes not available \u2014 100M+ vector search requires partitioning workaround",
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"detail": "ADB-S AI Vector Search supports HNSW indexes but they are node-local on\nmulti-node RAC (\u226564 ECPUs). At 100M+ vectors, queries on a 2-node RAC\nmiss vectors on the other node. Results are either incomplete or require\ncross-node scan that blows P95 >200ms.\n\nWorkaround from internal DB PM team: hash-partition vector table on\nvector_id, create partition-local HNSW index. Queries hit single\npartition on single node, maintaining <50ms at 100M scale.\n\nRequires table redesign \u2014 cannot be applied to existing unpartitioned\nvector tables without data reload.\n",
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"workaround": "Hash-partition vector table by vector_id. Create HNSW index as LOCAL\n(partition-level). Ensure partition pruning in queries.\nSource: internal DB PM team contact [name].\nValidated on ADB-S 23ai with 120M vectors, P95 = 38ms on 64 ECPU.\n",
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"oracle_sr": "",
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"status": "acknowledged",
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"resolved_date": null,
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"resolution": null,
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"affects_matrix": "AI Vector Search (HNSW)",
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"tags": [
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"vector-search",
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"hnsw",
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"distributed",
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"rac",
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"partitioning",
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"100m",
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"latency",
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"ai-vector-search"
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]
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},
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{
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"id": "FF-202603-002",
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"date": "2026-03-08",
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"contributor": {
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"name": "Diego Cabrera",
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"team": "Field Architecture",
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"client": "Strategic Migration Customer",
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"context": "Production migration",
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"confidence": "validated"
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},
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"product": "ADB-S Dedicated Elastic Pool (DEP)",
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"version": "23ai",
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"severity": "HIGH",
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"category": "limitation",
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"summary": "ADG must be disabled before joining Dedicated Elastic Pool",
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"detail": "When attempting to add an ADB-S instance with active Autonomous Data Guard\nto a Dedicated Elastic Pool, the operation fails. ADG must be explicitly\ndisabled before the instance can join the DEP. This is a known issue\nacknowledged by Oracle but not prominently documented.\n\nImpact: requires a brief HA gap during DEP onboarding. Must coordinate\nwith the customer's change window.\n",
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"workaround": "Disable ADG \u2192 join DEP \u2192 re-enable ADG. Plan for ~15 min HA gap.",
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"oracle_sr": "",
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"status": "acknowledged",
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"resolved_date": null,
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"resolution": null,
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"affects_matrix": "Elastic Pool Membership",
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"tags": [
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"dep",
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"adg",
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"elastic-pool",
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"ha",
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"limitation"
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]
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},
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{
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"id": "FF-202603-004",
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"date": "2026-03-01",
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"contributor": {
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"name": "Diego Cabrera",
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"team": "Field Architecture",
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"client": "Strategic Migration Customer",
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"context": "Production migration",
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"confidence": "validated"
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},
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"product": "ADB-S",
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"version": "23ai",
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"severity": "MEDIUM",
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"category": "gotcha",
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"summary": "DEP provisioning takes days to weeks depending on capacity",
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"detail": "Dedicated Elastic Pool provisioning is NOT instant like ADB-S Serverless.\nIt requires physical Exadata infrastructure allocation. Lead time varies\nfrom 3 days (if capacity available in region) to 2-3 weeks (if capacity\nneeds to be provisioned).\n\nBilling starts only at AVAILABLE state, not at request time.\nCo-location of existing ADB-S instances happens at the next maintenance\nwindow after joining, not immediately.\n",
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"workaround": "Request DEP early in the project timeline. Don't make it a critical-path dependency in week 1.",
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"oracle_sr": "",
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"status": "acknowledged",
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"resolved_date": null,
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"resolution": null,
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"affects_matrix": "Elastic Pool Membership",
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"tags": [
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"dep",
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"provisioning",
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"lead-time",
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"capacity",
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"planning"
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]
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},
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{
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"id": "FF-202603-007",
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"date": "2026-02-10",
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"contributor": {
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"name": "Diego Cabrera",
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"team": "Field Architecture",
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"client": "Pepe SRL",
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"context": "Discovery engagement",
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"confidence": "validated"
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},
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"product": "ADB-S",
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"version": "23ai",
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"severity": "INFO",
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"category": "gotcha",
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"summary": "ADB-S Serverless RAC node split threshold at 64 ECPUs",
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"detail": "ADB-S Serverless runs on 1 RAC node at \u226424 ECPUs and splits to 2 nodes\nat 64 ECPUs (16 cpu_count each). The gv$instance view only shows nodes\nwhere the PDB is open.\n\nThis affects connection pooling behavior and session distribution.\nApplications should use UCP or JDBC connection pool with FAN events\nto handle the multi-node scenario properly.\n",
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"workaround": "Ensure connection pool configuration handles multi-node. Use UCP with FAN.",
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"oracle_sr": "",
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"status": "acknowledged",
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"resolved_date": null,
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"resolution": null,
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"affects_matrix": null,
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"tags": [
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"adb-s",
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"rac",
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"ecpu",
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"node-split",
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"connection-pooling"
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]
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}
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]
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