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# ==============================
# 魂镜数据基础设施编排（关系库 / 缓存 / 向量 / 图库 / 对象存储）。
# 与应用层 docker-compose.app.yml 解耦：本文件创建并拥有共享网络 hunjing-net 与全部命名卷，
# 应用层以 external 方式引用该网络连接数据库等服务。
# 本地开发默认 SQLite，无需启动本文件；详见根目录 CLAUDE.md 与 docker/README.md。
#
# 常用命令：
# # 启动全部基础设施（首次会创建 hunjing-net 网络）
# docker compose -f docker/docker-compose.infra.yml up -d
# # 仅启动部分按需服务
# docker compose -f docker/docker-compose.infra.yml up -d hunjing-postgres hunjing-redis
# # 启用后期大规模图数据库 NebulaGraph（需带 --profile）
# docker compose -f docker/docker-compose.infra.yml --profile nebulagraph up -d hunjing-nebula-graphd hunjing-nebula-console-init
# # 停止并保留数据卷
# docker compose -f docker/docker-compose.infra.yml down
# # 停止并清除数据卷（谨慎，会丢失数据）
# docker compose -f docker/docker-compose.infra.yml down -v
#
# 内存限制：每个服务通过 deploy.resources.limits/reservations 约束内存，
# 默认值为本地模拟正式环境的保守配置，可按宿主机规格调整。
# ==============================
name: hunjing
networks:
hunjing-net:
name: hunjing-net
driver: bridge
volumes:
hunjing-pg-data:
hunjing-redis-data:
hunjing-neo4j-data:
hunjing-neo4j-logs:
hunjing-nebula-data:
hunjing-nebula-logs:
hunjing-etcd-data:
hunjing-minio-data:
hunjing-milvus-data:
services:
# ============================== 金匮 · 正式环境关系型数据库（PostgreSQL） ==============================
hunjing-postgres:
image: postgres:16-alpine
container_name: hunjing-postgres
restart: unless-stopped
networks: [hunjing-net]
environment:
POSTGRES_DB: ${POSTGRES_DB:-hunjing}
POSTGRES_USER: ${POSTGRES_USER:-hunjing}
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-change-me}
TZ: ${TIMEZONE:-Asia/Shanghai}
volumes:
- hunjing-pg-data:/var/lib/postgresql/data
ports:
- "${POSTGRES_PORT:-5432}:5432"
healthcheck:
test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-hunjing} -d ${POSTGRES_DB:-hunjing}"]
interval: 10s
timeout: 5s
retries: 5
deploy:
resources:
limits: { memory: 512M }
reservations: { memory: 128M }
# ============================== 灵泉 · 缓存与后台任务队列（Redis） ==============================
hunjing-redis:
image: redis:7-alpine
container_name: hunjing-redis
restart: unless-stopped
networks: [hunjing-net]
command: ["redis-server", "--appendonly", "yes"]
volumes:
- hunjing-redis-data:/data
ports:
- "${REDIS_PORT:-6379}:6379"
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 5s
retries: 5
deploy:
resources:
limits: { memory: 256M }
reservations: { memory: 64M }
# ============================== 玄络 · 图数据库 Neo4j（原型 / 中小规模，默认图库） ==============================
hunjing-neo4j:
image: neo4j:5-community
container_name: hunjing-neo4j
restart: unless-stopped
networks: [hunjing-net]
environment:
NEO4J_AUTH: ${NEO4J_USER:-neo4j}/${NEO4J_PASSWORD:-change-me}
NEO4J_PLUGINS: '["apoc"]'
TZ: ${TIMEZONE:-Asia/Shanghai}
volumes:
- hunjing-neo4j-data:/data
- hunjing-neo4j-logs:/logs
ports:
- "7474:7474" # Neo4j Browser（HTTP）
- "7687:7687" # Bolt 协议
deploy:
resources:
limits: { memory: 1G }
reservations: { memory: 256M }
# ============================== 玄络 · 图数据库 NebulaGraph（后期大规模，二选一） ==============================
# NebulaGraph 由 metad（元数据）、storaged（存储）、graphd（查询）三个服务组成，
# 首次启动需通过 console 注册 storage hosts 并创建 space（由下方 console-init 自动完成）。
# 启用方式（需带 --profile nebulagraph）：
# docker compose -f docker/docker-compose.infra.yml --profile nebulagraph up -d hunjing-nebula-graphd hunjing-nebula-console-init
# 同时在 .env 中设置 GRAPH_DB_TYPE=nebulagraph；默认不启用、不随 up 拉起。
hunjing-nebula-metad:
image: vesoft/nebula-metad:v3.6.0
container_name: hunjing-nebula-metad
profiles: ["nebulagraph"]
restart: unless-stopped
networks: [hunjing-net]
environment:
USER: root
TZ: ${TIMEZONE:-Asia/Shanghai}
command:
- --meta_server_addrs=hunjing-nebula-metad:9559
- --local_ip=hunjing-nebula-metad
- --ws_ip=hunjing-nebula-metad
- --port=9559
- --data_path=/data/meta
- --log_dir=/logs/meta
volumes:
- hunjing-nebula-data:/data
- hunjing-nebula-logs:/logs
deploy:
resources:
limits: { memory: 512M }
reservations: { memory: 128M }
hunjing-nebula-storaged:
image: vesoft/nebula-storaged:v3.6.0
container_name: hunjing-nebula-storaged
profiles: ["nebulagraph"]
restart: unless-stopped
networks: [hunjing-net]
environment:
USER: root
TZ: ${TIMEZONE:-Asia/Shanghai}
command:
- --meta_server_addrs=hunjing-nebula-metad:9559
- --local_ip=hunjing-nebula-storaged
- --ws_ip=hunjing-nebula-storaged
- --port=9779
- --data_path=/data/storage
- --log_dir=/logs/storage
volumes:
- hunjing-nebula-data:/data
- hunjing-nebula-logs:/logs
depends_on:
hunjing-nebula-metad:
condition: service_started
deploy:
resources:
limits: { memory: 1G }
reservations: { memory: 256M }
hunjing-nebula-graphd:
image: vesoft/nebula-graphd:v3.6.0
container_name: hunjing-nebula-graphd
profiles: ["nebulagraph"]
restart: unless-stopped
networks: [hunjing-net]
environment:
USER: root
TZ: ${TIMEZONE:-Asia/Shanghai}
command:
- --meta_server_addrs=hunjing-nebula-metad:9559
- --ws_ip=hunjing-nebula-graphd
- --port=9669
- --log_dir=/logs/graph
volumes:
- hunjing-nebula-logs:/logs
ports:
- "${NEBULAGRAPH_PORT:-9669}:9669" # 应用连接端口
depends_on:
hunjing-nebula-metad:
condition: service_started
deploy:
resources:
limits: { memory: 512M }
reservations: { memory: 128M }
# 一次性初始化：注册 storage hosts 并创建 space。
# 若 storaged 尚未 ONLINE 导致失败，待几秒后重跑：
# docker compose -f docker/docker-compose.infra.yml --profile nebulagraph up hunjing-nebula-console-init
hunjing-nebula-console-init:
image: vesoft/nebula-console:v3.6.0
container_name: hunjing-nebula-console-init
profiles: ["nebulagraph"]
restart: "no"
networks: [hunjing-net]
depends_on:
hunjing-nebula-graphd:
condition: service_started
hunjing-nebula-storaged:
condition: service_started
environment:
NEBULA_USER: ${NEBULAGRAPH_USER:-root}
NEBULA_PASSWORD: ${NEBULAGRAPH_PASSWORD:-nebula}
NEBULA_SPACE: ${NEBULAGRAPH_SPACE:-hunjing}
entrypoint:
- sh
- -c
- |
echo "等待 graphd 就绪..."
for i in $$(seq 1 30); do
if nebula-console -addr=hunjing-nebula-graphd -port=9669 -u "$$NEBULA_USER" -p "$$NEBULA_PASSWORD" -e "SHOW HOSTS;" >/dev/null 2>&1; then
echo "graphd 就绪，开始注册 hosts 并创建 space"
nebula-console -addr=hunjing-nebula-graphd -port=9669 -u "$$NEBULA_USER" -p "$$NEBULA_PASSWORD" -e \
"ADD HOSTS \"hunjing-nebula-storaged\":9779; CREATE SPACE IF NOT EXISTS $$NEBULA_SPACE(vid_type=FIXED_STRING(64), partition_num=10, replica_factor=1);"
echo "初始化完成"
exit 0
fi
echo "graphd 尚未就绪，2s 后重试 ($$i/30)"
sleep 2
done
echo "graphd 在超时内未就绪" >&2
exit 1
deploy:
resources:
limits: { memory: 256M }
reservations: { memory: 64M }
# ============================== 灵犀 · 向量数据库（Milvus）及其依赖 ==============================
# 灵犀 standalone 依赖 etcd（灵犀·元册，元数据）与 minio（玉函，对象存储块）。
hunjing-etcd:
image: quay.io/coreos/etcd:v3.5.16
container_name: hunjing-etcd
restart: unless-stopped
networks: [hunjing-net]
environment:
- ETCD_AUTO_COMPACTION_MODE=revision
- ETCD_AUTO_COMPACTION_RETENTION=1000
- ETCD_QUOTA_BACKEND_BYTES=4294967296
- ETCD_SNAPSHOT_COUNT=50000
volumes:
- hunjing-etcd-data:/etcd
command: >-
etcd
-advertise-client-urls=http://127.0.0.1:2379
-listen-client-urls=http://0.0.0.0:2379
--data-dir=/etcd
healthcheck:
test: ["CMD", "etcdctl", "endpoint", "health"]
interval: 30s
timeout: 20s
retries: 3
deploy:
resources:
limits: { memory: 512M }
reservations: { memory: 128M }
# 玉函 · 对象存储 MinIO（兼灵犀块存储）
hunjing-minio:
image: minio/minio:RELEASE.2024-11-07T00-52-20Z
container_name: hunjing-minio
restart: unless-stopped
networks: [hunjing-net]
# MinIO 同时作为 Milvus 的存储后端与魂镜对象存储（STORAGE_PROVIDER=minio）。
environment:
MINIO_ROOT_USER: ${MINIO_ACCESS_KEY_ID:-minioadmin}
MINIO_ROOT_PASSWORD: ${MINIO_SECRET_ACCESS_KEY:-minioadmin}
volumes:
- hunjing-minio-data:/minio_data
command: minio server /minio_data --console-address ":9001"
ports:
- "${MINIO_EXTERNAL_PORT:-9000}:9000" # S3 API
- "9001:9001" # 管理控制台
healthcheck:
test: ["CMD-SHELL", "mc ready local || exit 0"]
interval: 30s
timeout: 20s
retries: 3
deploy:
resources:
limits: { memory: 512M }
reservations: { memory: 128M }
# 灵犀 · 向量数据库 Milvus
hunjing-milvus:
image: milvusdb/milvus:v2.4.17
container_name: hunjing-milvus
restart: unless-stopped
networks: [hunjing-net]
command: ["milvus", "run", "standalone"]
security_opt:
- seccomp:unconfined
environment:
ETCD_ENDPOINTS: hunjing-etcd:2379
MINIO_ADDRESS: hunjing-minio:9000
TZ: ${TIMEZONE:-Asia/Shanghai}
volumes:
- hunjing-milvus-data:/var/lib/milvus
ports:
- "${MILVUS_PORT:-19530}:19530"
- "9091:9091" # 健康检查 / metrics
depends_on:
hunjing-etcd:
condition: service_healthy
hunjing-minio:
condition: service_started
healthcheck:
test: ["CMD-SHELL", "curl -sf http://localhost:9091/healthz || exit 1"]
interval: 30s
start_period: 120s
timeout: 20s
retries: 3
deploy:
resources:
limits: { memory: 2G }
reservations: { memory: 512M }
# ============================== 灵犀·观 · Milvus 可视化管理（Attu） ==============================
# Attu 是 Milvus 官方 Web 管理界面，用于查看 collection、数据与运行查询。
# 启动 Milvus 后访问 http://localhost:${ATTU_PORT:-8001}，连接地址默认指向 hunjing-milvus。
hunjing-attu:
image: zilliztech/attu:v2.4
container_name: hunjing-attu
restart: unless-stopped
networks: [hunjing-net]
environment:
MILVUS_URL: hunjing-milvus:19530
TZ: ${TIMEZONE:-Asia/Shanghai}
ports:
- "${ATTU_PORT:-8001}:3000"
depends_on:
hunjing-milvus:
condition: service_started
deploy:
resources:
limits: { memory: 256M }
reservations: { memory: 64M }
# ============================== 金匮·摹本 · PostgreSQL 备份 / 恢复（手动触发，profile: backup） ==============================
# 备份：docker compose -f docker/docker-compose.infra.yml --profile backup run --rm hunjing-pg-backup
# 恢复：见 docker/backup/backup-restore.sh 顶部命令（需 override entrypoint 并传 RESTORE_FILE）。
# 备份产物落在项目根 backups/ 目录（已加入 .gitignore）。
hunjing-pg-backup:
image: postgres:16-alpine
container_name: hunjing-pg-backup
profiles: ["backup"]
restart: "no"
networks: [hunjing-net]
environment:
PGHOST: hunjing-postgres
PGPORT: "5432"
PGUSER: ${POSTGRES_USER:-hunjing}
PGPASSWORD: ${POSTGRES_PASSWORD:-change-me}
PGDATABASE: ${POSTGRES_DB:-hunjing}
BACKUP_RETAIN_DAYS: ${BACKUP_RETAIN_DAYS:-7}
volumes:
- ./backup:/backup:ro
- ../backups:/backups
entrypoint: ["/bin/sh", "/backup/backup-postgres.sh"]
deploy:
resources:
limits: { memory: 256M }
reservations: { memory: 64M }