managing-milvus

name	managing-milvus
description	Use when working with Milvus — milvus vector database management, collection schema inspection, index build monitoring, and query node health analysis. Covers partition management, segment compaction, resource group allocation, replica configuration, and consistency level tuning. Read this skill before any Milvus operations.
connection_type	milvus
preload	false

Milvus Management Skill

Monitor, analyze, and optimize Milvus vector database instances safely.

MANDATORY: Discovery-First Pattern

Always check cluster health and list collections before any search or insert operations. Never assume collection names, field schemas, or index types.

Phase 1: Discovery

#!/bin/bash

MILVUS_URL="${MILVUS_URL:-http://localhost:9091}"
MILVUS_GRPC="${MILVUS_HOST:-localhost}:${MILVUS_PORT:-19530}"

echo "=== Health Check ==="
curl -s "$MILVUS_URL/healthz" 2>/dev/null || curl -s "$MILVUS_URL/api/v1/health" 2>/dev/null

echo ""
echo "=== Metrics Summary ==="
curl -s "$MILVUS_URL/metrics" 2>/dev/null | grep -E "^milvus_" | grep -E "num_collections|num_partitions|num_loaded|query_node" | head -15

echo ""
echo "=== Collections (via REST v2) ==="
curl -s -X POST "${MILVUS_URL%:9091}:19530/v2/vectordb/collections/list" \
    -H "Content-Type: application/json" \
    -d '{}' 2>/dev/null | python3 -c "
import sys, json
data = json.load(sys.stdin)
for c in data.get('data', []):
    print(f\"Collection: {c}\")
" 2>/dev/null || echo "REST v2 not available"

echo ""
echo "=== Using pymilvus if available ==="
python3 -c "
from pymilvus import connections, utility
connections.connect(host='${MILVUS_HOST:-localhost}', port=${MILVUS_PORT:-19530})
collections = utility.list_collections()
print(f'Collections: {len(collections)}')
for c in collections:
    print(f'  {c}')
" 2>/dev/null || echo "pymilvus not available"

echo ""
echo "=== Component Health ==="
curl -s "$MILVUS_URL/api/v1/health" 2>/dev/null | python3 -c "
import sys, json
data = json.load(sys.stdin)
print(f\"isHealthy: {data.get('isHealthy','?')}\")
for reason in data.get('reasons', []):
    print(f\"  {reason}\")
" 2>/dev/null

Phase 1 outputs: Health status, collection list, component health, key metrics.

Phase 2: Analysis

#!/bin/bash

MILVUS_URL="${MILVUS_URL:-http://localhost:9091}"
COLLECTION="${1:-my_collection}"

echo "=== Collection Details ==="
python3 -c "
from pymilvus import connections, Collection, utility
connections.connect(host='${MILVUS_HOST:-localhost}', port=${MILVUS_PORT:-19530})
c = Collection('$COLLECTION')
c.load()
schema = c.schema
print(f'Collection: {c.name}')
print(f'Description: {schema.description}')
print(f'Num entities: {c.num_entities}')
print(f'Fields:')
for f in schema.fields:
    print(f'  {f.name}: {f.dtype.name} | primary={f.is_primary} | dim={f.params.get(\"dim\",\"-\")}')
print(f'Indexes:')
for idx in c.indexes:
    print(f'  Field: {idx.field_name} | Type: {idx.params.get(\"index_type\",\"?\")} | Metric: {idx.params.get(\"metric_type\",\"?\")}')
print(f'Partitions: {[p.name for p in c.partitions]}')
" 2>/dev/null || echo "pymilvus required for detailed inspection"

echo ""
echo "=== Compaction Status ==="
curl -s "$MILVUS_URL/metrics" 2>/dev/null | grep -E "compaction" | head -5

echo ""
echo "=== Query Node Stats ==="
curl -s "$MILVUS_URL/metrics" 2>/dev/null | grep -E "query_node" | grep -E "search|query|loaded" | head -10

echo ""
echo "=== Resource Groups ==="
python3 -c "
from pymilvus import connections, utility
connections.connect(host='${MILVUS_HOST:-localhost}', port=${MILVUS_PORT:-19530})
groups = utility.list_resource_groups()
print(f'Resource groups: {groups}')
" 2>/dev/null ||  

 
 
python3 -c  2>/dev/null ||  

Output Format

MILVUS ANALYSIS
===============
Health: [healthy/unhealthy] | Collections: [count]
Total Entities: [count] | Query Nodes: [count]

ISSUES FOUND:
- [issue with affected collection/index]

RECOMMENDATIONS:
- [actionable recommendation]

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative