用 Docker 把開發要用到的服務都架在本機的紀錄，從版控、私有套件庫、CI，到一整套可觀測性堆疊的設定檔。
## ———-MSSQL———-
–不掛Volume
docker run --name sqlserver_novolume -e 'ACCEPT_EULA=Y' -e 'SA_PASSWORD=<your-password>' -p 1433:1433 -d shilvain/linux_sqlserver:v1
–掛Volume(不設定root) is work (還原資料庫用)
docker run --name sqlserver -e 'ACCEPT_EULA=Y' -e 'SA_PASSWORD=<your-password>' -p 1433:1433 -v C:\\Users\\User\\Docker\\MSSQL\\DATA:/var/opt/mssql/data -d shilvain/linux_sqlserver:v1
複製檔案
docker cp sqlserver:/var/opt/mssql/data/database.bak 'C:\\Users\\User\\Docker\\MSSQL\\database.bak'
docker cp sqlserver:/var/opt/mssql/data/database.bak C:\\Users\\User\\Docker\\MSSQL\\database.bak docker cp 'C:\\Users\\User\\Docker\\MSSQL\\database.bak' sqlserver1:/var/opt/mssql/data/database.bak
———-Mongo DB———-
拉 mongodb image
docker pull mongo
建立mongodb container
docker run -d --name mongodb -p 27017:27017 -v C:\\Users\\User\\Docker\\MongoDB\\data:/data/db -e MONGO_INITDB_ROOT_USERNAME=sa -e MONGO_INITDB_ROOT_PASSWORD=1qaz@WSX3edc mongo
Git Server
docker run -d --name gitea -p 3000:3000 -p 222:22 -v C:\users\user01\data:/data -e GITEA__security__SECRET_KEY=ShilvainSecretKey123! gitea/gitea:latest
設定資料庫的時候順便設定管理員帳戶。
查看目前 repos：
docker exec -u git -it gitea gitea repo list --config /data/gitea/conf/app.ini
列出某 user：
docker exec -u git -it gitea gitea repo list --user admin --config /data/gitea/conf/app.ini
NuGet Server
docker run -d --name baget -p 5555:80 -e ApiKey=MySecretKey loicsharma/baget
docker-compose.yml（只啟 BaGet）
version: '3.8'
services:
baget:
image: loicsharma/baget:latest
container_name: baget
ports:
- '5555:80'
environment:
# ===== API Key（NuGet push 用）=====
ApiKey: MySecretKey
# ===== 套件儲存 =====
Storage__Type: FileSystem
Storage__Path: /var/baget/packages
# ===== 使用既有 MSSQL =====
Database__Type: SqlServer
Database__ConnectionString: >
Server=192.168.1.10,1433;
Database=BaGet;
User Id=baget_user;
Password=StrongPassword!;
TrustServerCertificate=True;
volumes:
- ./baget-data:/var/baget
restart: always
1️⃣ 註冊 NuGet Source（只做一次）
dotnet nuget add source http://localhost:5555/v3/index.json --name BaGetMSSQL --username any --password MySecretKey --store-password-in-clear-text
2️⃣ 建立 NuGet 套件
dotnet pack -c Release
產生：
bin/Release/Your.Package.1.0.0.nupkg
3️⃣ Push 套件（關鍵）
dotnet nuget push \
bin/Release/*.nupkg \
--source BaGetMSSQL \
--api-key MySecretKey
成功訊息：
Your.Package.1.0.0.nupkg was pushed successfully.
🎉 套件已經存在你的 MSSQL + 檔案系統中
驗證下載
dotnet add package Your.Package --source BaGetMSSQL
或 NuGet.config：
<configuration>
<packageSources>
<add key='BaGetMSSQL'
value='http://localhost:5555/v3/index.json' />
</packageSources>
</configuration>
Jenkins
docker run -d --name jenkins -p 8080:8080 -p 50000:50000 -v jenkins_home:/var/jenkins_home jenkins/jenkins:lts
- 8080 → Web UI
- 50000 → Agent 通訊
- jenkins_home → 所有設定、Job、Plugin 都在這
- lts → 長期支援版（穩定）
OpenTelemetry
docker-compose.yml
version: '3.9'
services:
# ======================
# Grafana UI
# ======================
grafana:
image: grafana/grafana:10.3.1
container_name: grafana
ports:
- '3000:3000'
environment:
- GF_SECURITY_ADMIN_USER=admin
- GF_SECURITY_ADMIN_PASSWORD=admin
volumes:
- grafana-data:/var/lib/grafana
depends_on:
- prometheus
- tempo
- loki
# ======================
# Prometheus (Metrics)
# ======================
prometheus:
image: prom/prometheus:v2.49.1
container_name: prometheus
ports:
- '9090:9090'
volumes:
- ./prometheus.yml:/etc/prometheus/prometheus.yml
command:
- '--config.file=/etc/prometheus/prometheus.yml'
# ======================
# Tempo (Traces)
# ======================
tempo:
image: grafana/tempo:2.4.1
user: '0:0'
container_name: tempo
ports:
- '3200:3200' # Tempo UI / Query
#- '4317:4317' # OTLP gRPC
#- '4318:4318' # OTLP HTTP
volumes:
- ./tempo.yml:/etc/tempo.yml
- tempo-data:/tmp/tempo
command: ['-config.file=/etc/tempo.yml']
# ======================
# Loki (Logs)
# ======================
loki:
image: grafana/loki:2.9.4
container_name: loki
ports:
- '3100:3100'
volumes:
- ./loki.yml:/etc/loki/loki.yml
command: ['-config.file=/etc/loki/loki.yml']
# ======================
# OpenTelemetry Collector
# ======================
otel-collector:
image: otel/opentelemetry-collector-contrib:0.95.0
container_name: otel-collector
ports:
- '4317:4317' # OTLP gRPC
- '4318:4318' # OTLP HTTP
- '8889:8889'
volumes:
- ./otel-collector-config.yml:/etc/otelcol/config.yml
command: ['--config=/etc/otelcol/config.yml']
depends_on:
- prometheus
- tempo
- loki
volumes:
grafana-data:
tempo-data:
otel-collector-config.yml
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
memory_limiter: # << 加在這裡
limit_mib: 512 # 最大使用 512 MB
spike_limit_mib: 256 # 突發量允許再增加 256 MB
check_interval: 5s # 每 5 秒檢查一次記憶體
exporters:
# Metrics → Prometheus
prometheus:
endpoint: '0.0.0.0:8889'
# Traces → Tempo
otlp/tempo:
endpoint: tempo:4317
tls:
insecure: true
# Logs → Loki
loki:
endpoint: http://loki:3100/loki/api/v1/push
service:
pipelines:
metrics:
receivers: [otlp]
processors: [memory_limiter, batch]
exporters: [prometheus]
traces:
receivers: [otlp]
processors: [memory_limiter, batch]
exporters: [otlp/tempo]
logs:
receivers: [otlp]
processors: [memory_limiter, batch]
exporters: [loki]
prometheus.yml
global:
scrape_interval: 15s
scrape_configs:
- job_name: 'otel-collector'
static_configs:
- targets: ['otel-collector:8889']
tempo.yml
server:
http_listen_port: 3200
distributor:
receivers:
otlp:
protocols:
grpc:
http:
ingester:
lifecycler:
ring:
kvstore:
store: inmemory
replication_factor: 1
compactor:
compaction:
block_retention: 24h
storage:
trace:
backend: local
local:
path: /tmp/tempo
wal:
path: /tmp/tempo/wal
loki.yml
auth_enabled: false
server:
http_listen_port: 3100
common:
path_prefix: /tmp/loki
replication_factor: 1
storage:
filesystem:
chunks_directory: /tmp/loki/chunks
rules_directory: /tmp/loki/rules
ring:
kvstore:
store: inmemory
schema_config:
configs:
- from: 2024-01-01
store: boltdb-shipper
object_store: filesystem
schema: v13
index:
prefix: index_
period: 24h