云原生数据库解决方案指南
云原生数据库是专为容器化和Kubernetes环境设计的数据库系统，具备弹性伸缩、自动故障转移、声明式配置等特性。本指南深入探讨主流云原生数据库的架构、部署模式和最佳实践。
🗄️ 云原生数据库架构
数据库云原生化演进
yaml
cloud_native_evolution:
traditional_databases:
deployment: "虚拟机或物理机"
scaling: "垂直扩展为主"
availability: "主从复制、故障手动切换"
operations: "人工运维"
limitations:
- "资源利用率低"
- "扩展能力受限"
- "恢复时间长"
- "运维成本高"
containerized_databases:
deployment: "容器化部署"
scaling: "支持水平扩展"
availability: "自动故障检测"
operations: "半自动化运维"
improvements:
- "资源隔离和利用率提升"
- "快速部署和扩容"
- "统一管理平台"
- "配置标准化"
challenges:
- "存储持久化"
- "网络性能"
- "状态管理复杂"
- "数据安全性"
cloud_native_databases:
deployment: "Kubernetes Operator管理"
scaling: "自动弹性伸缩"
availability: "自愈能力"
operations: "完全自动化"
characteristics:
architecture:
- "存储计算分离"
- "多租户支持"
- "分布式架构"
- "API优先设计"
operations:
- "声明式配置"
- "自动备份恢复"
- "在线升级"
- "智能调优"
observability:
- "指标实时采集"
- "日志集中管理"
- "分布式追踪"
- "可视化监控"yaml
database_selection:
selection_criteria:
workload_type:
oltp:
description: "在线事务处理"
characteristics:
- "高并发读写"
- "低延迟要求"
- "ACID事务支持"
recommended:
- "CockroachDB"
- "TiDB"
- "YugabyteDB"
olap:
description: "在线分析处理"
characteristics:
- "大数据量分析"
- "复杂查询"
- "列式存储"
recommended:
- "ClickHouse"
- "Apache Druid"
- "TimescaleDB"
htap:
description: "混合事务分析处理"
characteristics:
- "同时支持OLTP和OLAP"
- "实时分析能力"
- "灵活负载处理"
recommended:
- "TiDB"
- "YugabyteDB"
- "CockroachDB"
consistency_model:
strong_consistency:
databases: ["CockroachDB", "YugabyteDB", "TiDB"]
use_cases: ["金融交易", "库存管理", "订单系统"]
eventual_consistency:
databases: ["Cassandra", "MongoDB", "Couchbase"]
use_cases: ["社交媒体", "内容分发", "日志收集"]
scaling_requirements:
horizontal_scaling:
description: "添加更多节点扩展"
databases:
- "CockroachDB"
- "TiDB"
- "Cassandra"
- "MongoDB Sharding"
vertical_scaling:
description: "增加单节点资源"
databases:
- "PostgreSQL"
- "MySQL"
- "MongoDB"🐘 主流云原生数据库
CockroachDB
yaml
cockroachdb:
architecture:
description: "分布式SQL数据库，兼容PostgreSQL"
key_features:
- "强一致性(Serializable隔离级别)"
- "自动分片和rebalancing"
- "多活架构(Multi-Active)"
- "地理分布式部署"
- "无单点故障"
architecture_layers:
sql_layer:
- "SQL解析和优化"
- "分布式执行计划"
- "PostgreSQL兼容协议"
transaction_layer:
- "分布式事务协调"
- "MVCC并发控制"
- "基于时间戳的冲突解决"
distribution_layer:
- "Range分片(默认64MB)"
- "Raft副本协议"
- "自动负载均衡"
storage_layer:
- "RocksDB存储引擎"
- "LSM-Tree结构"
- "压缩和垃圾回收"
kubernetes_deployment:
operator_based: |
# 使用CockroachDB Operator部署
apiVersion: crdb.cockroachlabs.com/v1alpha1
kind: CrdbCluster
metadata:
name: cockroachdb
namespace: database
spec:
dataStore:
pvc:
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
storageClassName: fast-ssd
resources:
requests:
cpu: "2"
memory: "4Gi"
limits:
cpu: "4"
memory: "8Gi"
tlsEnabled: true
image:
name: cockroachdb/cockroach:v23.1.0
nodes: 3
additionalLabels:
app: cockroachdb
environment: production
manual_deployment: |
# 手动StatefulSet部署
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: cockroachdb
namespace: database
spec:
serviceName: cockroachdb
replicas: 3
selector:
matchLabels:
app: cockroachdb
template:
metadata:
labels:
app: cockroachdb
spec:
affinity:
podAntiAffinity:
preferredDuringSchedulingIgnoredDuringExecution:
- weight: 100
podAffinityTerm:
labelSelector:
matchExpressions:
- key: app
operator: In
values:
- cockroachdb
topologyKey: kubernetes.io/hostname
containers:
- name: cockroachdb
image: cockroachdb/cockroach:v23.1.0
imagePullPolicy: IfNotPresent
ports:
- containerPort: 26257
name: grpc
- containerPort: 8080
name: http
livenessProbe:
httpGet:
path: /health
port: http
scheme: HTTPS
initialDelaySeconds: 30
periodSeconds: 5
readinessProbe:
httpGet:
path: /health?ready=1
port: http
scheme: HTTPS
initialDelaySeconds: 10
periodSeconds: 5
volumeMounts:
- name: datadir
mountPath: /cockroach/cockroach-data
- name: certs
mountPath: /cockroach/cockroach-certs
env:
- name: COCKROACH_CHANNEL
value: kubernetes-insecure
command:
- /bin/bash
- -ecx
- |
exec /cockroach/cockroach start \
--logtostderr \
--certs-dir=/cockroach/cockroach-certs \
--advertise-host=$(hostname -f) \
--http-addr=0.0.0.0 \
--join=cockroachdb-0.cockroachdb,cockroachdb-1.cockroachdb,cockroachdb-2.cockroachdb \
--cache=25% \
--max-sql-memory=25%
volumes:
- name: certs
secret:
secretName: cockroachdb-node
defaultMode: 0400
volumeClaimTemplates:
- metadata:
name: datadir
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
storageClassName: fast-ssd
initialization: |
# 初始化集群
kubectl exec -it cockroachdb-0 -n database -- \
/cockroach/cockroach init \
--certs-dir=/cockroach/cockroach-certs \
--host=cockroachdb-0.cockroachdb
# 创建用户和数据库
kubectl exec -it cockroachdb-0 -n database -- \
/cockroach/cockroach sql \
--certs-dir=/cockroach/cockroach-certs \
--host=cockroachdb-0.cockroachdb \
--execute="CREATE USER myuser WITH PASSWORD 'mypassword'; CREATE DATABASE mydb; GRANT ALL ON DATABASE mydb TO myuser;"
best_practices:
schema_design:
- "使用UUID作为主键避免热点"
- "合理设计索引减少跨节点查询"
- "利用分区表优化大表查询"
- "避免大事务影响性能"
performance_tuning:
- "调整--cache和--max-sql-memory参数"
- "使用连接池管理连接"
- "启用查询缓存"
- "监控慢查询并优化"
high_availability:
- "至少3个节点保证可用性"
- "跨可用区部署"
- "配置区域感知副本"
- "定期测试故障转移"yaml
tidb:
architecture:
description: "分布式NewSQL数据库，兼容MySQL"
components:
tidb_server:
role: "SQL层，无状态"
responsibilities:
- "SQL解析和优化"
- "查询执行"
- "MySQL协议兼容"
scaling: "水平扩展"
pd_server:
role: "调度和元数据管理"
responsibilities:
- "集群元数据存储"
- "时间戳分配"
- "数据调度决策"
deployment: "3-5节点，奇数"
tikv_server:
role: "分布式KV存储"
responsibilities:
- "数据存储"
- "Raft副本协议"
- "事务支持"
scaling: "水平扩展"
tiflash:
role: "列式存储引擎"
responsibilities:
- "OLAP查询加速"
- "实时数据同步"
- "列式存储"
optional: true
kubernetes_deployment:
tidb_operator: |
# 安装TiDB Operator
helm repo add pingcap https://charts.pingcap.org/
helm install tidb-operator pingcap/tidb-operator \
--namespace tidb-admin \
--create-namespace \
--version v1.5.0
# 部署TiDB集群
apiVersion: pingcap.com/v1alpha1
kind: TidbCluster
metadata:
name: basic
namespace: tidb-cluster
spec:
version: v7.1.0
timezone: UTC
pvReclaimPolicy: Retain
enableDynamicConfiguration: true
configUpdateStrategy: RollingUpdate
pd:
baseImage: pingcap/pd
maxFailoverCount: 0
replicas: 3
requests:
cpu: "1"
memory: "2Gi"
limits:
cpu: "2"
memory: "4Gi"
storageClassName: fast-ssd
storageSize: "10Gi"
config:
log:
level: info
replication:
max-replicas: 3
location-labels: ["zone", "rack", "host"]
tikv:
baseImage: pingcap/tikv
maxFailoverCount: 0
replicas: 3
requests:
cpu: "2"
memory: "4Gi"
limits:
cpu: "4"
memory: "8Gi"
storageClassName: fast-ssd
storageSize: "100Gi"
config:
storage:
reserve-space: "10GB"
rocksdb:
max-open-files: 10000
raftdb:
max-open-files: 10000
tidb:
baseImage: pingcap/tidb
maxFailoverCount: 0
replicas: 2
service:
type: LoadBalancer
annotations:
cloud.google.com/load-balancer-type: "Internal"
requests:
cpu: "2"
memory: "4Gi"
limits:
cpu: "4"
memory: "8Gi"
config:
log:
level: info
performance:
max-procs: 0
tcp-keep-alive: true
tiflash:
baseImage: pingcap/tiflash
maxFailoverCount: 0
replicas: 1
storageClaims:
- resources:
requests:
storage: 100Gi
storageClassName: fast-ssd
requests:
cpu: "2"
memory: "4Gi"
limits:
cpu: "4"
memory: "8Gi"
monitoring_setup: |
# 配置监控
apiVersion: pingcap.com/v1alpha1
kind: TidbMonitor
metadata:
name: basic
namespace: tidb-cluster
spec:
clusters:
- name: basic
namespace: tidb-cluster
prometheus:
baseImage: prom/prometheus
version: v2.40.0
requests:
cpu: "1"
memory: "2Gi"
limits:
cpu: "2"
memory: "4Gi"
storage: 50Gi
storageClassName: standard
config:
commandOptions:
- --log.level=info
- --storage.tsdb.retention.time=30d
grafana:
baseImage: grafana/grafana
version: 9.3.0
service:
type: LoadBalancer
username: admin
password: admin
initializer:
baseImage: pingcap/tidb-monitor-initializer
version: v7.1.0
reloader:
baseImage: pingcap/tidb-monitor-reloader
version: v1.0.1
backup_restore:
backup_configuration: |
# 使用BR进行备份
apiVersion: pingcap.com/v1alpha1
kind: Backup
metadata:
name: demo1-backup
namespace: tidb-cluster
spec:
backupType: full
br:
cluster: basic
clusterNamespace: tidb-cluster
sendCredToTikv: true
from:
host: ${tidb_host}
port: ${tidb_port}
user: ${tidb_user}
secretName: backup-demo1-tidb-secret
s3:
provider: aws
secretName: s3-secret
region: us-west-2
bucket: tidb-backup
prefix: backup-folder
storageClassName: standard
storageSize: 100Gi
restore_configuration: |
# 从备份恢复
apiVersion: pingcap.com/v1alpha1
kind: Restore
metadata:
name: demo1-restore
namespace: tidb-cluster
spec:
backupType: full
br:
cluster: basic
clusterNamespace: tidb-cluster
sendCredToTikv: true
to:
host: ${tidb_host}
port: ${tidb_port}
user: ${tidb_user}
secretName: restore-demo1-tidb-secret
s3:
provider: aws
secretName: s3-secret
region: us-west-2
bucket: tidb-backup
prefix: backup-folder/backup-20231201
storageClassName: standard
storageSize: 100GiMongoDB和Cassandra
yaml
mongodb:
kubernetes_operator:
community_operator: |
# 使用MongoDB Community Operator
# 安装Operator
kubectl apply -f https://raw.githubusercontent.com/mongodb/mongodb-kubernetes-operator/master/config/crd/bases/mongodbcommunity.mongodb.com_mongodbcommunity.yaml
kubectl apply -f https://raw.githubusercontent.com/mongodb/mongodb-kubernetes-operator/master/config/manager/manager.yaml
# 部署MongoDB副本集
apiVersion: mongodbcommunity.mongodb.com/v1
kind: MongoDBCommunity
metadata:
name: mongodb-replica-set
namespace: mongodb
spec:
members: 3
type: ReplicaSet
version: "6.0.5"
security:
authentication:
modes: ["SCRAM"]
users:
- name: admin
db: admin
passwordSecretRef:
name: mongodb-admin-password
roles:
- name: clusterAdmin
db: admin
- name: userAdminAnyDatabase
db: admin
scramCredentialsSecretName: mongodb-admin-scram
- name: appuser
db: myapp
passwordSecretRef:
name: mongodb-app-password
roles:
- name: readWrite
db: myapp
scramCredentialsSecretName: mongodb-app-scram
additionalMongodConfig:
storage:
wiredTiger:
engineConfig:
cacheSizeGB: 2
operationProfiling:
mode: slowOp
slowOpThresholdMs: 100
statefulSet:
spec:
template:
spec:
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchExpressions:
- key: app
operator: In
values:
- mongodb-replica-set
topologyKey: kubernetes.io/hostname
containers:
- name: mongod
resources:
requests:
cpu: "1"
memory: "2Gi"
limits:
cpu: "2"
memory: "4Gi"
- name: mongodb-agent
resources:
requests:
cpu: "100m"
memory: "256Mi"
limits:
cpu: "200m"
memory: "512Mi"
volumeClaimTemplates:
- metadata:
name: data-volume
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
storageClassName: fast-ssd
- metadata:
name: logs-volume
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi
storageClassName: standard
sharded_cluster: |
# MongoDB分片集群配置
apiVersion: mongodbcommunity.mongodb.com/v1
kind: MongoDBCommunity
metadata:
name: mongodb-sharded
namespace: mongodb
spec:
type: ShardedCluster
version: "6.0.5"
shardCount: 3
mongosCount: 2
configServerCount: 3
# Config Server配置
configServer:
members: 3
podSpec:
resources:
requests:
cpu: "500m"
memory: "1Gi"
limits:
cpu: "1"
memory: "2Gi"
persistence:
single:
storage: 10Gi
storageClass: fast-ssd
# Mongos路由配置
mongos:
count: 2
podSpec:
resources:
requests:
cpu: "1"
memory: "2Gi"
limits:
cpu: "2"
memory: "4Gi"
# Shard配置
shardPodSpec:
podTemplate:
spec:
containers:
- name: mongod
resources:
requests:
cpu: "2"
memory: "4Gi"
limits:
cpu: "4"
memory: "8Gi"
persistence:
multiple:
data:
storage: 200Gi
storageClass: fast-ssd
journal:
storage: 10Gi
storageClass: fast-ssd
logs:
storage: 10Gi
storageClass: standardyaml
cassandra:
k8ssandra_operator:
description: "K8ssandra - Cassandra on Kubernetes的完整解决方案"
installation: |
# 安装K8ssandra Operator
helm repo add k8ssandra https://helm.k8ssandra.io/stable
helm repo update
helm install k8ssandra-operator k8ssandra/k8ssandra-operator \
--namespace k8ssandra-operator \
--create-namespace
cluster_deployment: |
# 部署Cassandra集群
apiVersion: k8ssandra.io/v1alpha1
kind: K8ssandraCluster
metadata:
name: demo
namespace: cassandra
spec:
cassandra:
serverVersion: "4.0.7"
datacenters:
- metadata:
name: dc1
size: 3
storageConfig:
cassandraDataVolumeClaimSpec:
storageClassName: fast-ssd
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
config:
jvmOptions:
heapSize: 2Gi
heapNewGenSize: 400Mi
cassandraYaml:
num_tokens: 16
authenticator: PasswordAuthenticator
authorizer: CassandraAuthorizer
concurrent_reads: 32
concurrent_writes: 32
concurrent_counter_writes: 32
commitlog_sync: periodic
commitlog_sync_period_in_ms: 10000
racks:
- name: rack1
affinityLabels:
topology.kubernetes.io/zone: us-east-1a
- name: rack2
affinityLabels:
topology.kubernetes.io/zone: us-east-1b
- name: rack: rack3
affinityLabels:
topology.kubernetes.io/zone: us-east-1c
resources:
requests:
cpu: "2"
memory: "4Gi"
limits:
cpu: "4"
memory: "8Gi"
# Stargate API网关
stargate:
size: 2
heapSize: 1Gi
resources:
requests:
cpu: "1"
memory: "2Gi"
limits:
cpu: "2"
memory: "4Gi"
# Reaper修复服务
reaper:
autoScheduling:
enabled: true
resources:
requests:
cpu: "100m"
memory: "256Mi"
limits:
cpu: "500m"
memory: "512Mi"
# Medusa备份
medusa:
storageProperties:
storageProvider: s3
bucketName: cassandra-backup
region: us-east-1
storageSecretRef:
name: medusa-bucket-key
resources:
requests:
cpu: "100m"
memory: "256Mi"
limits:
cpu: "500m"
memory: "512Mi"
backup_restore: |
# 创建备份
apiVersion: medusa.k8ssandra.io/v1alpha1
kind: CassandraBackup
metadata:
name: backup-20231201
namespace: cassandra
spec:
cassandraDatacenter: dc1
name: backup-20231201
# 从备份恢复
apiVersion: medusa.k8ssandra.io/v1alpha1
kind: CassandraRestore
metadata:
name: restore-20231201
namespace: cassandra
spec:
cassandraDatacenter:
name: dc1
backup: backup-20231201
inPlace: true
performance_tuning:
jvm_configuration:
- "根据节点内存调整堆大小"
- "使用G1GC垃圾收集器"
- "配置合适的GC日志"
- "启用JMX监控"
cassandra_yaml:
- "调整并发读写参数"
- "优化compaction策略"
- "配置缓存大小"
- "设置合适的超时时间"
schema_design:
- "基于查询模式设计表"
- "合理使用分区键"
- "避免大分区问题"
- "使用物化视图优化查询"📊 云原生数据库运维
监控和性能优化
yaml
monitoring_solution:
prometheus_stack:
exporters:
postgres_exporter: |
# PostgreSQL监控
apiVersion: apps/v1
kind: Deployment
metadata:
name: postgres-exporter
spec:
replicas: 1
template:
spec:
containers:
- name: postgres-exporter
image: prometheuscommunity/postgres-exporter:latest
env:
- name: DATA_SOURCE_NAME
value: "postgresql://user:password@postgres:5432/postgres?sslmode=disable"
ports:
- containerPort: 9187
mongodb_exporter: |
# MongoDB监控
apiVersion: apps/v1
kind: Deployment
metadata:
name: mongodb-exporter
spec:
template:
spec:
containers:
- name: mongodb-exporter
image: percona/mongodb_exporter:latest
env:
- name: MONGODB_URI
value: "mongodb://user:password@mongodb:27017"
ports:
- containerPort: 9216
cassandra_exporter: |
# Cassandra监控（JMX）
apiVersion: v1
kind: ConfigMap
metadata:
name: cassandra-exporter-config
data:
config.yml: |
startDelaySeconds: 0
ssl: false
lowercaseOutputName: false
lowercaseOutputLabelNames: false
whitelistObjectNames:
- org.apache.cassandra.metrics:type=ClientRequest,*
- org.apache.cassandra.metrics:type=Compaction,*
- org.apache.cassandra.metrics:type=Storage,*
alerting_rules: |
groups:
- name: database-alerts
rules:
# 通用数据库告警
- alert: DatabaseDown
expr: up{job=~".*-exporter"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Database is down"
- alert: HighDiskUsage
expr: (node_filesystem_size_bytes - node_filesystem_free_bytes) / node_filesystem_size_bytes * 100 > 85
for: 5m
labels:
severity: warning
annotations:
summary: "Database disk usage is high"
# PostgreSQL特定告警
- alert: PostgreSQLReplicationLag
expr: pg_replication_lag > 100*1024*1024
for: 2m
labels:
severity: critical
# MongoDB特定告警
- alert: MongoDBReplicationLag
expr: mongodb_mongod_replset_member_replication_lag > 10
for: 2m
labels:
severity: warning
# Cassandra特定告警
- alert: CassandraNodeDown
expr: cassandra_node_up == 0
for: 1m
labels:
severity: criticalyaml
performance_optimization:
query_optimization:
slow_query_analysis: |
# PostgreSQL慢查询分析
kubectl exec -it postgres-0 -- psql -U postgres -c "
SELECT query,
calls,
total_time,
mean_time,
max_time
FROM pg_stat_statements
ORDER BY mean_time DESC
LIMIT 10;
"
# MongoDB慢查询
kubectl exec -it mongodb-0 -- mongo --eval "
db.setProfilingLevel(1, { slowms: 100 });
db.system.profile.find().limit(10).sort({ ts: -1 }).pretty();
"
# Cassandra慢查询（通过nodetool）
kubectl exec -it cassandra-0 -- nodetool settraceprobability 0.01
kubectl exec -it cassandra-0 -- nodetool gettraceprobability
index_optimization:
postgresql: |
# 查找缺失索引
SELECT schemaname, tablename,
seq_scan, seq_tup_read,
idx_scan, idx_tup_fetch
FROM pg_stat_user_tables
WHERE seq_scan > 0
ORDER BY seq_tup_read DESC
LIMIT 10;
# 查找未使用的索引
SELECT schemaname, tablename, indexname, idx_scan
FROM pg_stat_user_indexes
WHERE idx_scan = 0
AND indexrelname NOT LIKE '%_pkey';
mongodb: |
# 分析查询计划
db.collection.find({field: value}).explain("executionStats")
# 创建复合索引
db.collection.createIndex(
{ field1: 1, field2: 1 },
{ background: true }
)
cassandra: |
# 创建二级索引
CREATE INDEX ON keyspace.table (column);
# 使用物化视图
CREATE MATERIALIZED VIEW keyspace.view AS
SELECT * FROM keyspace.table
WHERE column IS NOT NULL
PRIMARY KEY (column, id);
connection_pooling:
pgbouncer_config: |
# PgBouncer连接池
apiVersion: apps/v1
kind: Deployment
metadata:
name: pgbouncer
spec:
template:
spec:
containers:
- name: pgbouncer
image: pgbouncer/pgbouncer:latest
env:
- name: DATABASES_HOST
value: postgres
- name: DATABASES_PORT
value: "5432"
- name: DATABASES_DATABASE
value: "*"
- name: PGBOUNCER_POOL_MODE
value: transaction
- name: PGBOUNCER_MAX_CLIENT_CONN
value: "1000"
- name: PGBOUNCER_DEFAULT_POOL_SIZE
value: "20"
application_connection: |
# 应用程序连接配置
database_config:
pool_size: 20
max_overflow: 10
pool_timeout: 30
pool_recycle: 3600
echo: false
# 连接字符串
connection_url: "postgresql://user:pass@pgbouncer:6432/dbname"
caching_strategies:
redis_cache_layer: |
# Redis缓存层配置
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: redis-cache
spec:
serviceName: redis
replicas: 3
template:
spec:
containers:
- name: redis
image: redis:7-alpine
command:
- redis-server
- --appendonly
- "yes"
- --maxmemory
- "2gb"
- --maxmemory-policy
- "allkeys-lru"
resources:
requests:
memory: "2Gi"
cpu: "500m"
limits:
memory: "3Gi"
cpu: "1"
application_caching: |
# 应用层缓存策略
cache_patterns:
read_through:
description: "读穿透缓存"
implementation: "先查缓存，未命中则查数据库并写入缓存"
write_through:
description: "写穿透缓存"
implementation: "同时更新缓存和数据库"
cache_aside:
description: "旁路缓存"
implementation: "应用程序管理缓存逻辑"📋 云原生数据库面试重点
架构设计类
云原生数据库的核心特征？
- 存储计算分离
- 弹性伸缩能力
- 自动故障恢复
- 声明式API管理
如何选择合适的云原生数据库？
- 工作负载类型分析
- 一致性模型要求
- 扩展性需求评估
- 运维复杂度考虑
分布式数据库的CAP权衡？
- 一致性(Consistency)
- 可用性(Availability)
- 分区容错性(Partition Tolerance)
- 不同场景的选择策略
部署运维类
Kubernetes上部署数据库的最佳实践？
- StatefulSet vs Operator
- 持久化存储配置
- 网络策略设计
- 资源限制设置
如何实现数据库的高可用？
- 多副本配置
- 自动故障转移
- 跨可用区部署
- 备份恢复策略
数据库备份和恢复方案？
- 全量备份vs增量备份
- 连续归档策略
- 点时间恢复PITR
- 跨区域备份
性能优化类
云原生数据库性能优化方法？
- 查询优化技巧
- 索引设计策略
- 连接池配置
- 缓存层设计
如何监控数据库性能？
- 关键指标选择
- 监控工具集成
- 告警规则设计
- 性能基线建立
分布式数据库的一致性保证？
- Raft/Paxos协议
- MVCC机制
- 分布式事务
- 最终一致性
技术对比类
CockroachDB vs TiDB的选择？
- 架构设计差异
- 兼容性对比
- 性能特点
- 适用场景分析
关系型vs非关系型数据库？
- 数据模型差异
- 事务支持能力
- 扩展性对比
- 使用场景选择
Operator vs Helm部署数据库？
- 自动化程度对比
- 运维复杂度
- 功能丰富度
- 适用场景分析
🔗 相关内容
- 数据管理概述 - 云原生数据管理架构
- StatefulSet实践 - 有状态应用部署
- Kubernetes Operator - Operator模式详解
- 存储管理 - Kubernetes存储配置
云原生数据库代表了数据库技术的未来发展方向，将分布式架构、自动化运维和云原生理念深度融合。通过选择合适的云原生数据库解决方案并遵循最佳实践，可以构建高可用、高性能、易运维的现代数据平台。