Resource Requirements Guide

This guide helps you plan the resources needed for your document processing and search infrastructure.

Quick Reference

Component	Minimum CPU	Minimum Memory	Recommended Storage
Pharia Search	2 CPU	1Gi	-
PostgreSQL	2 CPU	1Gi	128Gi
Qdrant	2 CPU	64Gi	96Gi
Pharia Data API	800m	1Gi	-
ETL Service	500m	1.5Gi	-

Detailed Requirements

Pharia Search

• CPU: 2-4 cores
• Memory: 1-2Gi
• Scaling Factor: documentBatchSize * averageDocumentSize * 2 + 256Mi

💡 Tip: For large documents or high concurrency, consider increasing CPU to 4 cores.

Database (PostgreSQL)

• CPU: 2-4 cores
• Memory: 1-2Gi
• Storage: Calculate as rawDocumentData * 1.1

Example: A 2.8 million document corpus (like German Wikipedia) needs about 10GB storage.

Vector Database (Qdrant)

Resource requirements per replica (default is 3 replicas):

• CPU: 2-4 cores
• Memory: 64Gi recommended
• Storage: 96Gi minimum

Memory usage depends on:

1. Number of documents
2. Chunk size and overlap
3. Search features enabled

Memory Calculator

For each index, estimate:

• Base: 4Gi * (512/chunkSize) * (1 + overlapPercentage)
• With BM25: Add 100% more for 512 token chunks
• With FilterIndex: Add numberOfChunks * chunkSize * (1 + overlapPercentage) * metadataSize

Example: For 2.8M documents with:

• 256 token chunks
• 50% overlap
• BM25 enabled
• String metadata (20 chars average)

Total: 4Gi * 2 * 2 + 8Gi + (6M * 2 * 2 * 20B) = ~25Gi

Pharia Data API

• CPU: 800m-1 core
• Memory: 1-2Gi
• Scaling: Horizontal scaling recommended for high concurrency

ETL Service

• CPU: 500m-1 core per replica
• Memory: 1.5-3Gi per replica
• Replicas: 3 recommended

Best Practices

1. Start Conservative: Begin with recommended minimums
2. Monitor Usage: Watch resource utilization during initial operations
3. Scale Gradually: Increase resources based on actual usage patterns
4. Consider Growth: Plan for 30% headroom above current needs