fix: exclude __words__ keyword index from corruption detection and getStats()

The __words__ keyword index stores 50-5000 entries per entity (one per
word), which inflated avg entries/entity well above the corruption
threshold of 100. This caused:

1. validateConsistency() to falsely detect corruption on every startup,
   triggering unnecessary clearAllIndexData() + rebuild() cycles
2. getStats() to log false "Metadata index may be corrupted" warnings
   and report inflated totalEntries/totalIds stats

Both methods now skip __words__ when counting, so stats and health
checks reflect metadata fields only (noun, type, createdAt, etc.).
Keyword search is unaffected since the __words__ field index itself
is not modified.
This commit is contained in:
David Snelling 2026-01-27 15:38:21 -08:00
parent 32dbdcec61
commit 364360d447
128 changed files with 5637 additions and 5682 deletions

View file

@ -1,10 +1,9 @@
# AWS S3 Cost Optimization Guide for Brainy v4.0.0
# AWS S3 Cost Optimization Guide for Brainy
> **Cost Impact**: Reduce storage costs from $138k/year to $5.9k/year at 500TB scale (**96% savings**)
## Overview
Brainy v4.0.0 provides enterprise-grade cost optimization features for AWS S3 storage, enabling automatic tier transitions that dramatically reduce storage costs while maintaining performance.
Brainy provides enterprise-grade cost optimization features for AWS S3 storage, enabling automatic tier transitions that dramatically reduce storage costs while maintaining performance.
## Cost Breakdown (Before Optimization)
@ -39,10 +38,10 @@ import { S3CompatibleStorage } from '@soulcraft/brainy/storage'
// Initialize Brainy with S3 storage
const storage = new S3CompatibleStorage({
bucket: 'my-brainy-data',
region: 'us-east-1',
accessKeyId: process.env.AWS_ACCESS_KEY_ID,
secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY
bucket: 'my-brainy-data',
region: 'us-east-1',
accessKeyId: process.env.AWS_ACCESS_KEY_ID,
secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY
})
const brain = new Brainy({ storage })
@ -50,24 +49,24 @@ await brain.init()
// Set lifecycle policy for automatic archival
await storage.setLifecyclePolicy({
rules: [{
id: 'optimize-vectors',
prefix: 'entities/nouns/vectors/',
status: 'Enabled',
transitions: [
{ days: 30, storageClass: 'STANDARD_IA' }, // Infrequent Access after 30 days
{ days: 90, storageClass: 'GLACIER' }, // Glacier after 90 days
{ days: 365, storageClass: 'DEEP_ARCHIVE' } // Deep Archive after 1 year
]
}, {
id: 'optimize-metadata',
prefix: 'entities/nouns/metadata/',
status: 'Enabled',
transitions: [
{ days: 30, storageClass: 'STANDARD_IA' },
{ days: 180, storageClass: 'GLACIER' }
]
}]
rules: [{
id: 'optimize-vectors',
prefix: 'entities/nouns/vectors/',
status: 'Enabled',
transitions: [
{ days: 30, storageClass: 'STANDARD_IA' }, // Infrequent Access after 30 days
{ days: 90, storageClass: 'GLACIER' }, // Glacier after 90 days
{ days: 365, storageClass: 'DEEP_ARCHIVE' } // Deep Archive after 1 year
]
}, {
id: 'optimize-metadata',
prefix: 'entities/nouns/metadata/',
status: 'Enabled',
transitions: [
{ days: 30, storageClass: 'STANDARD_IA' },
{ days: 180, storageClass: 'GLACIER' }
]
}]
})
// Verify lifecycle policy
@ -84,10 +83,10 @@ console.log('Lifecycle policy active:', policy.rules.length, 'rules')
- 10% of data 365+ days old (Deep Archive)
```
Standard (200TB): 200TB × $0.023/GB × 12 = $55,200/year
Standard-IA (150TB): 150TB × $0.0125/GB × 12 = $22,500/year
Glacier (100TB): 100TB × $0.004/GB × 12 = $4,800/year
Deep Archive (50TB): 50TB × $0.00099/GB × 12 = $594/year
Standard (200TB): 200TB × $0.023/GB × 12 = $55,200/year
Standard-IA (150TB): 150TB × $0.0125/GB × 12 = $22,500/year
Glacier (100TB): 100TB × $0.004/GB × 12 = $4,800/year
Deep Archive (50TB): 50TB × $0.00099/GB × 12 = $594/year
Total Storage Cost: $83,094/year (instead of $138,000)
Total with Operations: ~$88,000/year
@ -133,11 +132,11 @@ Intelligent-Tiering automatically moves objects between:
- 30% Deep Archive Access
```
Frequent (75TB): 75TB × $0.023/GB × 12 = $20,700/year
Infrequent (100TB): 100TB × $0.0125/GB × 12 = $15,000/year
Archive (175TB): 175TB × $0.004/GB × 12 = $8,400/year
Deep Archive (150TB): 150TB × $0.00099/GB × 12 = $1,782/year
Monitoring: ~$300/year (minimal)
Frequent (75TB): 75TB × $0.023/GB × 12 = $20,700/year
Infrequent (100TB): 100TB × $0.0125/GB × 12 = $15,000/year
Archive (175TB): 175TB × $0.004/GB × 12 = $8,400/year
Deep Archive (150TB): 150TB × $0.00099/GB × 12 = $1,782/year
Monitoring: ~$300/year (minimal)
Total Storage Cost: $46,182/year
Total with Operations: ~$51,000/year
@ -157,21 +156,21 @@ await storage.enableIntelligentTiering('entities/verbs/vectors/', 'verbs-auto')
// Set lifecycle policy for metadata (less frequently accessed)
await storage.setLifecyclePolicy({
rules: [{
id: 'archive-old-metadata',
prefix: 'entities/nouns/metadata/',
status: 'Enabled',
transitions: [
{ days: 30, storageClass: 'STANDARD_IA' },
{ days: 60, storageClass: 'GLACIER' },
{ days: 180, storageClass: 'DEEP_ARCHIVE' }
]
}, {
id: 'cleanup-old-system-data',
prefix: '_system/',
status: 'Enabled',
expiration: { days: 365 } // Delete old statistics
}]
rules: [{
id: 'archive-old-metadata',
prefix: 'entities/nouns/metadata/',
status: 'Enabled',
transitions: [
{ days: 30, storageClass: 'STANDARD_IA' },
{ days: 60, storageClass: 'GLACIER' },
{ days: 180, storageClass: 'DEEP_ARCHIVE' }
]
}, {
id: 'cleanup-old-system-data',
prefix: '_system/',
status: 'Enabled',
expiration: { days: 365 } // Delete old statistics
}]
})
```
@ -179,19 +178,19 @@ await storage.setLifecyclePolicy({
**Vectors (300TB with Intelligent-Tiering):**
```
Frequent (45TB): 45TB × $0.023/GB × 12 = $12,420/year
Infrequent (60TB): 60TB × $0.0125/GB × 12 = $9,000/year
Archive (105TB): 105TB × $0.004/GB × 12 = $5,040/year
Deep Archive (90TB): 90TB × $0.00099/GB × 12 = $1,069/year
Frequent (45TB): 45TB × $0.023/GB × 12 = $12,420/year
Infrequent (60TB): 60TB × $0.0125/GB × 12 = $9,000/year
Archive (105TB): 105TB × $0.004/GB × 12 = $5,040/year
Deep Archive (90TB): 90TB × $0.00099/GB × 12 = $1,069/year
Subtotal: $27,529/year
```
**Metadata (200TB with Lifecycle Policy):**
```
Standard (60TB): 60TB × $0.023/GB × 12 = $16,560/year
Standard-IA (40TB): 40TB × $0.0125/GB × 12 = $6,000/year
Glacier (60TB): 60TB × $0.004/GB × 12 = $2,880/year
Deep Archive (40TB): 40TB × $0.00099/GB × 12 = $475/year
Standard (60TB): 60TB × $0.023/GB × 12 = $16,560/year
Standard-IA (40TB): 40TB × $0.0125/GB × 12 = $6,000/year
Glacier (60TB): 60TB × $0.004/GB × 12 = $2,880/year
Deep Archive (40TB): 40TB × $0.00099/GB × 12 = $475/year
Subtotal: $25,915/year
```
@ -206,16 +205,16 @@ Subtotal: $25,915/year
```typescript
await storage.setLifecyclePolicy({
rules: [{
id: 'aggressive-archival',
prefix: 'entities/',
status: 'Enabled',
transitions: [
{ days: 14, storageClass: 'STANDARD_IA' }, // IA after 2 weeks
{ days: 30, storageClass: 'GLACIER' }, // Glacier after 1 month
{ days: 90, storageClass: 'DEEP_ARCHIVE' } // Deep Archive after 3 months
]
}]
rules: [{
id: 'aggressive-archival',
prefix: 'entities/',
status: 'Enabled',
transitions: [
{ days: 14, storageClass: 'STANDARD_IA' }, // IA after 2 weeks
{ days: 30, storageClass: 'GLACIER' }, // Glacier after 1 month
{ days: 90, storageClass: 'DEEP_ARCHIVE' } // Deep Archive after 3 months
]
}]
})
```
@ -223,10 +222,10 @@ await storage.setLifecyclePolicy({
**After 1 year:**
```
Standard (50TB): 50TB × $0.023/GB × 12 = $13,800/year
Standard-IA (50TB): 50TB × $0.0125/GB × 12 = $7,500/year
Glacier (100TB): 100TB × $0.004/GB × 12 = $4,800/year
Deep Archive (300TB): 300TB × $0.00099/GB × 12 = $3,564/year
Standard (50TB): 50TB × $0.023/GB × 12 = $13,800/year
Standard-IA (50TB): 50TB × $0.0125/GB × 12 = $7,500/year
Glacier (100TB): 100TB × $0.004/GB × 12 = $4,800/year
Deep Archive (300TB): 300TB × $0.00099/GB × 12 = $3,564/year
Total Storage Cost: $29,664/year
Total with Operations: ~$34,000/year
@ -250,16 +249,16 @@ Note: Retrieval costs may be significant if archived data is accessed frequently
### Efficient Cleanup
```typescript
// v4.0.0: Batch delete (1000 objects per request)
// Batch delete (1000 objects per request)
const idsToDelete = [/* array of entity IDs */]
// Generate paths for both vector and metadata files
const paths = idsToDelete.flatMap(id => {
const shard = id.substring(0, 2)
return [
`entities/nouns/vectors/${shard}/${id}.json`,
`entities/nouns/metadata/${shard}/${id}.json`
]
const shard = id.substring(0, 2)
return [
`entities/nouns/vectors/${shard}/${id}.json`,
`entities/nouns/metadata/${shard}/${id}.json`
]
})
// Batch delete (much faster and cheaper than individual deletes)
@ -280,14 +279,14 @@ console.log('Active rules:', policy.rules)
// Example output:
// {
// rules: [
// {
// id: 'optimize-vectors',
// prefix: 'entities/nouns/vectors/',
// status: 'Enabled',
// transitions: [...]
// }
// ]
// rules: [
// {
// id: 'optimize-vectors',
// prefix: 'entities/nouns/vectors/',
// status: 'Enabled',
// transitions: [...]
// }
// ]
// }
```
@ -396,6 +395,5 @@ await storage.enableIntelligentTiering('entities/', 'new-config')
---
**Version**: v4.0.0
**Last Updated**: 2025-10-17
**Cloud Provider**: AWS S3