日志之Loki详细讲解
1 Loki
1.1 引言
Loki
是一个轻量级的日志收集、分析的应用,采用的是promtail
的方式来获取日志内容并送到loki里面进行存储,最终在grafana
的datasource
里面添加数据源进行日志的展示、查询。
官方文档:https://kubernetes.io/docs/concepts/security/pod-security-policy
loki
的持久化存储支持azure、gcs、s3、swift、local
这5中类型,其中常用的是s3、local
。另外,它还支持很多种日志搜集类型,像最常用的logstash、fluentbit
也在官方支持的列表中。
优点:
- 支持的客户端,如
Promtail,Fluentbit,Fluentd,Vector,Logstash和Grafana Agent
- 首选代理
Promtail
,可以多来源提取日志,包括本地日志文件,systemd,Windows
事件日志,Docker
日志记录驱动程序等 - 没有日志格式要求,包括
JSON,XML,CSV,logfmt
,非结构化文本 - 使用与查询指标相同的语法查询日志
- 日志查询时允许动态筛选和转换日志行
- 可以轻松地计算日志中的需要的指标
- 引入时的最小索引意味着您可以在查询时动态地对日志进行切片和切块,以便在出现新问题时回答它们
- 云原生支持,使用
Prometheus
形式抓取数据
各日志收集组件简单对比
名称 | 安装的组件 | 优点 |
---|---|---|
ELK/EFK | elasticsearch、logstash, kibana、filebeat、kafka/redis | 支持自定义grok正则解析复杂日志内容;dashboard支持主富的可视化展示 |
Loki | grafana、loki、promtail | 占用资源小;grafana原生支持;查询速度快 |
1.2 Loki工作方式
1.2.1 日志解析格式
从上面的图中我们可以看到,它在解析日志的时候是以index
为主的,index
包括时间戳和pod
的部分label
(其他label
为filename
、containers
等),其余的是日志内容。具体查询效果如下:
{app="loki",namespace="kube-public"}
为索引
1.2.2 日志搜集架构模式
在使用过程中,官方推荐使用promtail
做为agent
以DaemonSet
方式部署在kubernetes
的worker
节点上搜集日志。另外也可以用上面提到的其他日志收集工具来收取,这篇文章在结尾处会附上其他工具的配置方式。
1.2.3 Loki部署模式
Loki
由许多组件微服务构建而成,微服务组件有5个。在这5个里面添加缓存用来把数据放起来加快查询。数据放在共享存储里面配置memberlist_config
部分并在实例之间共享状态,将Loki
进行无限横向扩展。
在配置完memberlist_config
部分后采用轮询的方式查找数据。为了使用方便官方把所有的微服务编译成一个二进制,可以通过命令行参数-target
控制,支持all、read、write
,我们在部署时根据日志量的大小可以指定不同模式
all
(读写模式)
服务启动后,我们做的数据查询、数据写入都是来自这一个节点
read/write
(读写分离模式)
在读写分离模式下运行时fronted-query
查询会将流量转发到read
节点上。读节点上保留了querier、ruler、fronted
,写节点上保留了distributor、ingester
- 微服务模式运行
微服务模式运行下,通过不同的配置参数启动为不同的角色,每一个进程都引用它的目标角色服务。
组件名称 | 功能 |
---|---|
分发器/调度器(distributor) | 验证数据合规:数据排序; hash一致性, QPS限制, 转发,数据副本保证不丢失 |
收集器(ingester) | 时间戳排序: 文件系统支持: WAL预写 |
查询前端 (query frontend) | 提供页面操作,向后端存储发出数据查询;查询队列 (query-queueing) 能够防止大数据量查询时触发0OM;查询分割 (query-split) 可以分割大批量查询最后进行数据聚台 |
查询器Querier | 使用loggl语言在后端存储中查询日志 |
缓存 | 将查询到的日志缓存起来共后续使用,如果数据不完整重新查询缺失的数据 |
1.3 服务端部署
在部署之前需要准备好一个k8s集群才行哦
应用 | 镜像 |
---|---|
loki | grafana/loki:2.5.0 |
promtail | grafana/promtail:2.5.0 |
1.3.1 AllInOne部署模式
1.3.1.1 k8s部署
我们从github上下载的程序是没有配置文件的,需要提前将文件准备一份。这里提供了一份完整的allInOne
配置文件,部分内容进行了优化。
配置文件内容如下所示
auth_enabled: false
target: all
ballast_bytes: 20480
server:
grpc_listen_port: 9095
http_listen_port: 3100
graceful_shutdown_timeout: 20s
grpc_listen_address: "0.0.0.0"
grpc_listen_network: "tcp"
grpc_server_max_concurrent_streams: 100
grpc_server_max_recv_msg_size: 4194304
grpc_server_max_send_msg_size: 4194304
http_server_idle_timeout: 2m
http_listen_address: "0.0.0.0"
http_listen_network: "tcp"
http_server_read_timeout: 30s
http_server_write_timeout: 20s
log_source_ips_enabled: true
# http_path_prefix如果需要更改,在推送日志的时候前缀都需要加指定的内容
# http_path_prefix: "/"
register_instrumentation: true
log_format: json
log_level: info
distributor:
ring:
heartbeat_timeout: 3s
kvstore:
prefix: collectors/
store: memberlist
# 需要提前创建好consul集群
# consul:
# http_client_timeout: 20s
# consistent_reads: true
# host: 127.0.0.1:8500
# watch_burst_size: 2
# watch_rate_limit: 2
querier:
engine:
max_look_back_period: 20s
timeout: 3m0s
extra_query_delay: 100ms
max_concurrent: 10
multi_tenant_queries_enabled: true
query_ingester_only: false
query_ingesters_within: 3h0m0s
query_store_only: false
query_timeout: 5m0s
tail_max_duration: 1h0s
query_scheduler:
max_outstanding_requests_per_tenant: 2048
grpc_client_config:
max_recv_msg_size: 104857600
max_send_msg_size: 16777216
grpc_compression: gzip
rate_limit: 0
rate_limit_burst: 0
backoff_on_ratelimits: false
backoff_config:
min_period: 50ms
max_period: 15s
max_retries: 5
use_scheduler_ring: true
scheduler_ring:
kvstore:
store: memberlist
prefix: "collectors/"
heartbeat_period: 30s
heartbeat_timeout: 1m0s
# 默认第一个网卡的名称
# instance_interface_names
# instance_addr: 127.0.0.1
# 默认server.grpc-listen-port
instance_port: 9095
frontend:
max_outstanding_per_tenant: 4096
querier_forget_delay: 1h0s
compress_responses: true
log_queries_longer_than: 2m0s
max_body_size: 104857600
query_stats_enabled: true
scheduler_dns_lookup_period: 10s
scheduler_worker_concurrency: 15
query_range:
align_queries_with_step: true
cache_results: true
parallelise_shardable_queries: true
max_retries: 3
results_cache:
cache:
enable_fifocache: false
default_validity: 30s
background:
writeback_buffer: 10000
redis:
endpoint: 127.0.0.1:6379
timeout: 1s
expiration: 0s
db: 9
pool_size: 128
password: 1521Qyx6^
tls_enabled: false
tls_insecure_skip_verify: true
idle_timeout: 10s
max_connection_age: 8h
ruler:
enable_api: true
enable_sharding: true
alertmanager_refresh_interval: 1m
disable_rule_group_label: false
evaluation_interval: 1m0s
flush_period: 3m0s
for_grace_period: 20m0s
for_outage_tolerance: 1h0s
notification_queue_capacity: 10000
notification_timeout: 4s
poll_interval: 10m0s
query_stats_enabled: true
remote_write:
config_refresh_period: 10s
enabled: false
resend_delay: 2m0s
rule_path: /rulers
search_pending_for: 5m0s
storage:
local:
directory: /data/loki/rulers
type: configdb
sharding_strategy: default
wal_cleaner:
period: 240h
min_age: 12h0m0s
wal:
dir: /data/loki/ruler_wal
max_age: 4h0m0s
min_age: 5m0s
truncate_frequency: 1h0m0s
ring:
kvstore:
store: memberlist
prefix: "collectors/"
heartbeat_period: 5s
heartbeat_timeout: 1m0s
# instance_addr: "127.0.0.1"
# instance_id: "miyamoto.en0"
# instance_interface_names: ["en0","lo0"]
instance_port: 9500
num_tokens: 100
ingester_client:
pool_config:
health_check_ingesters: false
client_cleanup_period: 10s
remote_timeout: 3s
remote_timeout: 5s
ingester:
autoforget_unhealthy: true
chunk_encoding: gzip
chunk_target_size: 1572864
max_transfer_retries: 0
sync_min_utilization: 3.5
sync_period: 20s
flush_check_period: 30s
flush_op_timeout: 10m0s
chunk_retain_period: 1m30s
chunk_block_size: 262144
chunk_idle_period: 1h0s
max_returned_stream_errors: 20
concurrent_flushes: 3
index_shards: 32
max_chunk_age: 2h0m0s
query_store_max_look_back_period: 3h30m30s
wal:
enabled: true
dir: /data/loki/wal
flush_on_shutdown: true
checkpoint_duration: 15m
replay_memory_ceiling: 2GB
lifecycler:
ring:
kvstore:
store: memberlist
prefix: "collectors/"
heartbeat_timeout: 30s
replication_factor: 1
num_tokens: 128
heartbeat_period: 5s
join_after: 5s
observe_period: 1m0s
# interface_names: ["en0","lo0"]
final_sleep: 10s
min_ready_duration: 15s
storage_config:
boltdb:
directory: /data/loki/boltdb
boltdb_shipper:
active_index_directory: /data/loki/active_index
build_per_tenant_index: true
cache_location: /data/loki/cache
cache_ttl: 48h
resync_interval: 5m
query_ready_num_days: 5
index_gateway_client:
grpc_client_config:
filesystem:
directory: /data/loki/chunks
chunk_store_config:
chunk_cache_config:
enable_fifocache: true
default_validity: 30s
background:
writeback_buffer: 10000
redis:
endpoint: 192.168.3.56:6379
timeout: 1s
expiration: 0s
db: 8
pool_size: 128
password: 1521Qyx6^
tls_enabled: false
tls_insecure_skip_verify: true
idle_timeout: 10s
max_connection_age: 8h
fifocache:
ttl: 1h
validity: 30m0s
max_size_items: 2000
max_size_bytes: 500MB
write_dedupe_cache_config:
enable_fifocache: true
default_validity: 30s
background:
writeback_buffer: 10000
redis:
endpoint: 127.0.0.1:6379
timeout: 1s
expiration: 0s
db: 7
pool_size: 128
password: 1521Qyx6^
tls_enabled: false
tls_insecure_skip_verify: true
idle_timeout: 10s
max_connection_age: 8h
fifocache:
ttl: 1h
validity: 30m0s
max_size_items: 2000
max_size_bytes: 500MB
cache_lookups_older_than: 10s
# 压缩碎片索引
compactor:
shared_store: filesystem
shared_store_key_prefix: index/
working_directory: /data/loki/compactor
compaction_interval: 10m0s
retention_enabled: true
retention_delete_delay: 2h0m0s
retention_delete_worker_count: 150
delete_request_cancel_period: 24h0m0s
max_compaction_parallelism: 2
# compactor_ring:
frontend_worker:
match_max_concurrent: true
parallelism: 10
dns_lookup_duration: 5s
# runtime_config 这里没有配置任何信息
# runtime_config:
common:
storage:
filesystem:
chunks_directory: /data/loki/chunks
fules_directory: /data/loki/rulers
replication_factor: 3
persist_tokens: false
# instance_interface_names: ["en0","eth0","ens33"]
analytics:
reporting_enabled: false
limits_config:
ingestion_rate_strategy: global
ingestion_rate_mb: 100
ingestion_burst_size_mb: 18
max_label_name_length: 2096
max_label_value_length: 2048
max_label_names_per_series: 60
enforce_metric_name: true
max_entries_limit_per_query: 5000
reject_old_samples: true
reject_old_samples_max_age: 168h
creation_grace_period: 20m0s
max_global_streams_per_user: 5000
unordered_writes: true
max_chunks_per_query: 200000
max_query_length: 721h
max_query_parallelism: 64
max_query_series: 700
cardinality_limit: 100000
max_streams_matchers_per_query: 1000
max_concurrent_tail_requests: 10
ruler_evaluation_delay_duration: 3s
ruler_max_rules_per_rule_group: 0
ruler_max_rule_groups_per_tenant: 0
retention_period: 700h
per_tenant_override_period: 20s
max_cache_freshness_per_query: 2m0s
max_queriers_per_tenant: 0
per_stream_rate_limit: 6MB
per_stream_rate_limit_burst: 50MB
max_query_lookback: 0
ruler_remote_write_disabled: false
min_sharding_lookback: 0s
split_queries_by_interval: 10m0s
max_line_size: 30mb
max_line_size_truncate: false
max_streams_per_user: 0
# memberlist_conig模块配置gossip用于在分发服务器、摄取器和查询器之间发现和连接。
# 所有三个组件的配置都是唯一的,以确保单个共享环。
# 至少定义了1个join_members配置后,将自动为分发服务器、摄取器和ring 配置memberlist类型的kvstore
memberlist:
randomize_node_name: true
stream_timeout: 5s
retransmit_factor: 4
join_members:
- 'loki-memberlist'
abort_if_cluster_join_fails: true
advertise_addr: 0.0.0.0
advertise_port: 7946
bind_addr: ["0.0.0.0"]
bind_port: 7946
compression_enabled: true
dead_node_reclaim_time: 30s
gossip_interval: 100ms
gossip_nodes: 3
gossip_to_dead_nodes_time: 3
# join:
leave_timeout: 15s
left_ingesters_timeout: 3m0s
max_join_backoff: 1m0s
max_join_retries: 5
message_history_buffer_bytes: 4096
min_join_backoff: 2s
# node_name: miyamoto
packet_dial_timeout: 5s
packet_write_timeout: 5s
pull_push_interval: 100ms
rejoin_interval: 10s
tls_enabled: false
tls_insecure_skip_verify: true
schema_config:
configs:
- from: "2020-10-24"
index:
period: 24h
prefix: index_
object_store: filesystem
schema: v11
store: boltdb-shipper
chunks:
period: 168h
row_shards: 32
table_manager:
retention_deletes_enabled: false
retention_period: 0s
throughput_updates_disabled: false
poll_interval: 3m0s
creation_grace_period: 20m
index_tables_provisioning:
provisioned_write_throughput: 1000
provisioned_read_throughput: 500
inactive_write_throughput: 4
inactive_read_throughput: 300
inactive_write_scale_lastn: 50
enable_inactive_throughput_on_demand_mode: true
enable_ondemand_throughput_mode: true
inactive_read_scale_lastn: 10
write_scale:
enabled: true
target: 80
# role_arn:
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
inactive_write_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
read_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
inactive_read_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
chunk_tables_provisioning:
enable_inactive_throughput_on_demand_mode: true
enable_ondemand_throughput_mode: true
provisioned_write_throughput: 1000
provisioned_read_throughput: 300
inactive_write_throughput: 1
inactive_write_scale_lastn: 50
inactive_read_throughput: 300
inactive_read_scale_lastn: 10
write_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
inactive_write_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
read_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
inactive_read_scale:
enabled: true
target: 80
out_cooldown: 1800
min_capacity: 3000
max_capacity: 6000
in_cooldown: 1800
tracing:
enabled: true
注意
:
ingester.lifecycler.ring.replication_factor
的值在单实例的情况下为1ingester.lifecycler.min_ready_duration
的值为15s,在启动后默认会显示15秒将状态变为ready
memberlist.node_name
的值可以不用设置,默认是当前主机的名称memberlist.join_members
是一个列表,在有多个实例的情况下需要添加各个节点的主机名/IP地址
。在k8s
里面可以设置成一个service绑定到StatefulSets
query_range.results_cache.cache.enable_fifocache
建议设置为false,我这里设置成了trueinstance_interface_names
是一个列表,默认的为["en0","eth0"]
,可以根据需要设置对应的网卡名称,一般不需要进行特殊设置。
1.3.1.2 创建configmap
将上面的内容写入到一个文件——>loki-all.yaml
,把它作为一个configmap
写入k8s
集群。可以使用如下命令创建:
kubectl create configmap --from-file ./loki-all.yaml loki-all
可以通过命令查看到已经创建好的configmap
,具体操作详见下图
1.3.1.3 创建持久化存储
在k8s里面我们的数据是需要进行持久化的。Loki
收集起来的日志信息对于业务来说是至关重要的,因此需要在容器重启的时候日志能够保留下来。
那么就需要用到pv、pvc
,后端存储可以使用nfs、glusterfs、hostPath、azureDisk、cephfs
等20种支持类型,这里因为没有对应的环境就采用了hostPath
方式。
apiVersion: v1
kind: PersistentVolume
metadata:
name: loki
namespace: default
spec:
hostPath:
path: /glusterfs/loki
type: DirectoryOrCreate
capacity:
storage: 1Gi
accessModes:
- ReadWriteMany
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: loki
namespace: default
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: 1Gi
volumeName: loki
1.3.1.4 创建应用
准备好k8s的StatefulSet
部署文件后就可以直接在集群里面创建应用了。
apiVersion: apps/v1
kind: StatefulSet
metadata:
labels:
app: loki
name: loki
namespace: default
spec:
podManagementPolicy: OrderedReady
replicas: 1
selector:
matchLabels:
app: loki
template:
metadata:
annotations:
prometheus.io/port: http-metrics
prometheus.io/scrape: "true"
labels:
app: loki
spec:
containers:
- args:
- -config.file=/etc/loki/loki-all.yaml
image: grafana/loki:2.5.0
imagePullPolicy: IfNotPresent
livenessProbe:
failureThreshold: 3
httpGet:
path: /ready
port: http-metrics
scheme: HTTP
initialDelaySeconds: 45
periodSeconds: 10
successThreshold: 1
timeoutSeconds: 1
name: loki
ports:
- containerPort: 3100
name: http-metrics
protocol: TCP
- containerPort: 9095
name: grpc
protocol: TCP
- containerPort: 7946
name: memberlist-port
protocol: TCP
readinessProbe:
failureThreshold: 3
httpGet:
path: /ready
port: http-metrics
scheme: HTTP
initialDelaySeconds: 45
periodSeconds: 10
successThreshold: 1
timeoutSeconds: 1
resources:
requests:
cpu: 500m
memory: 500Mi
limits:
cpu: 500m
memory: 500Mi
securityContext:
readOnlyRootFilesystem: true
volumeMounts:
- mountPath: /etc/loki
name: config
- mountPath: /data
name: storage
restartPolicy: Always
securityContext:
fsGroup: 10001
runAsGroup: 10001
runAsNonRoot: true
runAsUser: 10001
serviceAccount: loki
serviceAccountName: loki
volumes:
- emptyDir: {}
name: tmp
- name: config
configMap:
name: loki
- persistentVolumeClaim:
claimName: loki
name: storage
---
kind: Service
apiVersion: v1
metadata:
name: loki-memberlist
namespace: default
spec:
ports:
- name: loki-memberlist
protocol: TCP
port: 7946
targetPort: 7946
selector:
kubepi.org/name: loki
---
kind: Service
apiVersion: v1
metadata:
name: loki
namespace: default
spec:
ports:
- name: loki
protocol: TCP
port: 3100
targetPort: 3100
selector:
kubepi.org/name: loki
在上面的配置文件中我添加了一些pod
级别的安全策略,这些安全策略还有集群级别的PodSecurityPolicy
,防止因为漏洞的原因造成集群的整个崩溃
1.3.1.5 验证部署结果
当看到上面的Running
状态时可以通过API的方式看一下分发器是不是正常工作,当显示Active
时正常才会正常分发日志流到收集器(ingester
)
1.3.2 裸机部署
将loki
放到系统的/bin/
目录下,准备grafana-loki.service
控制文件重载系统服务列表
[Unit]
Description=Grafana Loki Log Ingester
Documentation=https://grafana.com/logs/
After=network-online.target
[Service]
ExecStart=/bin/loki --config.file /etc/loki/loki-all.yaml
ExecReload=/bin/kill -s HUP $MAINPID
ExecStop=/bin/kill -s TERM $MAINPID
[Install]
WantedBy=multi-user.target
重载系统列表命令,可以直接系统自动管理服务:
systemctl daemon-reload
# 启动服务
systemctl start grafana-loki
# 停止服务
systemctl stop grafana-loki
# 重载应用
systemctl reload grafana-loki
1.4 Promtail部署
部署客户端收集日志时也需要创建一个配置文件,按照上面创建服务端的步骤创建。不同的是需要把日志内容push
到服务端
1.4.1 k8s部署
1.4.1.1 创建配置文件
server:
log_level: info
http_listen_port: 3101
clients:
- url: http://loki:3100/loki/api/v1/push
positions:
filename: /run/promtail/positions.yaml
scrape_configs:
- job_name: kubernetes-pods
pipeline_stages:
- cri: {}
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels:
- __meta_kubernetes_pod_controller_name
regex: ([0-9a-z-.]+?)(-[0-9a-f]{8,10})?
action: replace
target_label: __tmp_controller_name
- source_labels:
- __meta_kubernetes_pod_label_app_kubernetes_io_name
- __meta_kubernetes_pod_label_app
- __tmp_controller_name
- __meta_kubernetes_pod_name
regex: ^;*([^;]+)(;.*)?$
action: replace
target_label: app
- source_labels:
- __meta_kubernetes_pod_label_app_kubernetes_io_instance
- __meta_kubernetes_pod_label_release
regex: ^;*([^;]+)(;.*)?$
action: replace
target_label: instance
- source_labels:
- __meta_kubernetes_pod_label_app_kubernetes_io_component
- __meta_kubernetes_pod_label_component
regex: ^;*([^;]+)(;.*)?$
action: replace
target_label: component
- action: replace
source_labels:
- __meta_kubernetes_pod_node_name
target_label: node_name
- action: replace
source_labels:
- __meta_kubernetes_namespace
target_label: namespace
- action: replace
replacement: $1
separator: /
source_labels:
- namespace
- app
target_label: job
- action: replace
source_labels:
- __meta_kubernetes_pod_name
target_label: pod
- action: replace
source_labels:
- __meta_kubernetes_pod_container_name
target_label: container
- action: replace
replacement: /var/log/pods/*$1/*.log
separator: /
source_labels:
- __meta_kubernetes_pod_uid
- __meta_kubernetes_pod_container_name
target_label: __path__
- action: replace
regex: true/(.*)
replacement: /var/log/pods/*$1/*.log
separator: /
source_labels:
- __meta_kubernetes_pod_annotationpresent_kubernetes_io_config_hash
- __meta_kubernetes_pod_annotation_kubernetes_io_config_hash
- __meta_kubernetes_pod_container_name
target_label: __path__
用上面的内容创建一个configMap,方法同上
1.4.1.2 创建DaemonSet文件
Promtail
是一个无状态应用不需要进行持久化存储只需要部署到集群里面就可以了,还是同样的准备DaemonSets
创建文件。
kind: DaemonSet
apiVersion: apps/v1
metadata:
name: promtail
namespace: default
labels:
app.kubernetes.io/instance: promtail
app.kubernetes.io/name: promtail
app.kubernetes.io/version: 2.5.0
spec:
selector:
matchLabels:
app.kubernetes.io/instance: promtail
app.kubernetes.io/name: promtail
template:
metadata:
labels:
app.kubernetes.io/instance: promtail
app.kubernetes.io/name: promtail
spec:
volumes:
- name: config
configMap:
name: promtail
- name: run
hostPath:
path: /run/promtail
- name: containers
hostPath:
path: /var/lib/docker/containers
- name: pods
hostPath:
path: /var/log/pods
containers:
- name: promtail
image: docker.io/grafana/promtail:2.3.0
args:
- '-config.file=/etc/promtail/promtail.yaml'
ports:
- name: http-metrics
containerPort: 3101
protocol: TCP
env:
- name: HOSTNAME
valueFrom:
fieldRef:
apiVersion: v1
fieldPath: spec.nodeName
volumeMounts:
- name: config
mountPath: /etc/promtail
- name: run
mountPath: /run/promtail
- name: containers
readOnly: true
mountPath: /var/lib/docker/containers
- name: pods
readOnly: true
mountPath: /var/log/pods
readinessProbe:
httpGet:
path: /ready
port: http-metrics
scheme: HTTP
initialDelaySeconds: 10
timeoutSeconds: 1
periodSeconds: 10
successThreshold: 1
failureThreshold: 5
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
drop:
- ALL
readOnlyRootFilesystem: false
allowPrivilegeEscalation: false
restartPolicy: Always
serviceAccountName: promtail
serviceAccount: promtail
tolerations:
- key: node-role.kubernetes.io/master
operator: Exists
effect: NoSchedule
- key: node-role.kubernetes.io/control-plane
operator: Exists
effect: NoSchedule
1.4.1.3 创建promtail应用
kubectl apply -f promtail.yaml
使用上面这个命令创建后就可以看到服务已经创建好了。接下来就是在Grafana
里面添加DataSource
查看数据了。
1.4.2 裸机部署
如果是裸机部署的情况下,需要对上面的配置文件做一下稍微的改动,更改clients
的地址就可以,文件存放到/etc/loki/
下,例如改成:
clients:
- url: http://ipaddress:port/loki/api/v1/push
添加系统开机启动配置,service配置文件存放位置/usr/lib/systemd/system/loki-promtail.service
内容如下
[Unit]
Description=Grafana Loki Log Ingester
Documentation=https://grafana.com/logs/
After=network-online.target
[Service]
ExecStart=/bin/promtail --config.file /etc/loki/loki-promtail.yaml
ExecReload=/bin/kill -s HUP $MAINPID
ExecStop=/bin/kill -s TERM $MAINPID
[Install]
WantedBy=multi-user.target
启动方式同上面服务端部署内容
1.5 数据源
添加数据源,具体步骤: Grafana->Setting->DataSources->AddDataSource->Loki
注意
:http
的URL
地址,应用、服务部署在哪个namespace
下,就需要指定它的FQDN
地址,它的格式是ServiceName.namespace
。如果默认在default
下、创建的端口号是3100,就需要填写为http://loki:3100,这里为什么不写IP地址而写成服务的名字,是因为在k8s集群里面有个dns服务器会自动解析这个地址。
查找日志信息
1.6 其他客户端配置
1.6.1 Logstash作为日志收集客户端
在启动Logstash
后我们需要安装一个插件,可以通过这个命令安装loki
的输出插件,安装完成之后可以在logstash
的output
中添加信息。
bin/logstash-plugin install logstash-output-loki
添加配置进行测试
完整的logstash
配置信息,可以参考官网给出的内容LogstashConfigFile
output {
loki {
[url => "" | default = none | required=true]
[tenant_id => string | default = nil | required=false]
[message_field => string | default = "message" | required=false]
[include_fields => array | default = [] | required=false]
[batch_wait => number | default = 1(s) | required=false]
[batch_size => number | default = 102400(bytes) | required=false]
[min_delay => number | default = 1(s) | required=false]
[max_delay => number | default = 300(s) | required=false]
[retries => number | default = 10 | required=false]
[username => string | default = nil | required=false]
[password => secret | default = nil | required=false]
[cert => path | default = nil | required=false]
[key => path | default = nil| required=false]
[ca_cert => path | default = nil | required=false]
[insecure_skip_verify => boolean | default = false | required=false]
}
}
或者采用logstash
的http
输出模块,配置如下:
output {
http {
format => "json"
http_method => "post"
content_type => "application/json"
connect_timeout => 10
url => "http://loki:3100/loki/api/v1/push"
message => '"message":"%{message}"}'
}
}
1.7 Helm安装
如果想简便安装的话,可以采用helm
来安装。helm
将所有的安装步骤都进行了封装,简化了安装步骤。
对于想详细了解k8s的人来说,helm不太适合。因为它封装后自动执行,k8s
管理员不知道各组件之间是如何依赖的,可能会造成误区。
废话不多说,下面开始helm安装:
- 添加repo源
helm repo add grafana https://grafana.github.io/helm-charts
- 更新源
helm repo update
- 部署
默认配置
helm upgrade --install loki grafana/loki-simple-scalable
自定义namespace
helm upgrade --install loki --namespace=loki grafana/loki-simple-scalable
自定义配置信息
helm upgrade --install loki grafana/loki-simple-scalable --set "key1=val1,key2=val2,..."
1.8 故障解决方案
1.8.1 502 BadGateWay
loki的地址填写不正确
在k8s里面,地址填写错误造成了502。检查一下loki的地址是否是以下内容:
http://LokiServiceName
http://LokiServiceName.namespace
http://LokiServiceName.namespace:ServicePort
grafana和loki
在不同的节点上,检查一下节点间网络通信状态、防火墙策略
1.8.2 Ingester not ready: instance xx:9095 in state JOINING
耐心等待一会,因为是allInOne
模式程序启动需要一定的时间。
1.8.3 too many unhealthy instances in the ring
将ingester.lifecycler.replication_factor
改为1,是因为这个设置不正确造成的。这个在启动的时候会设置为多个复制源,但当前只部署了一个所以在查看label
的时候提示这个
1.8.4 Data source connected
Data source connected, but no labels received. Verify that Loki and Promtail is configured properly
promtail
无法将收集到的日志发送给loki,许可检查一下promtail
的输出是不是正常promtail
在loki还没有准备就绪的时候把日志发送过来了,但loki没有接收到。如果需要重新接收日志,需要删除positions.yaml文件,具体路径可以用find查找一下位置promtail
忽略了目标日志文件或者配置文件错误造成的无法正常启动promtail
无法在指定的位置发现日志文件