本篇給大家帶來一套輕量級的 kubernetes 日志收集方案的相關介紹。我自己也在生産環境中使用過這套方案,令我意想不到的時它占用的kubernetes的資源相比與ELK這套方案真的是小巫見大巫。那接下來就跟随這篇文章開始學習它吧……
為什麼要使用Loki
這篇文章着重介紹了grafana公司開發的loki日志收集應用。Loki是一個輕量級的日志收集、分析的應用,采用的是promtail的方式來擷取日志内容并送到loki裡面進行存儲,最終在grafana的datasource裡面添加資料源進行日志的展示、查詢。
loki的持久化存儲支援azure、gcs、s3、swift、local這5中類型,其中常用的是s3、local。另外,它還支援很多種日志搜集類型,像最常用的logstash、fluentbit也在官方支援的清單中。
那它有哪些優點呢?
- 支援的用戶端,如Promtail,Fluentbit,Fluentd,Vector,Logstash和Grafana Agent
- 首選代理Promtail,可以多來源提取日志,包括本地日志檔案,systemd,Windows事件日志,Docker日志記錄驅動程式等
- 沒有日志格式要求,包括JSON,XML,CSV,logfmt,非結構化文本
- 使用與查詢名額相同的文法查詢日志
- 日志查詢時允許動态篩選和轉換日志行
- 可以輕松地計算日志中的需要的名額
- 引入時的最小索引意味着您可以在查詢時動态地對日志進行切片和切塊,以便在出現新問題時回答它們
- 雲原生支援,使用Prometheus形式抓取資料
各日志收集元件簡單對比
Loki工作方式解惑日志解析格式
從上面的圖中我們可以看到,它在解析日志的時候是以index為主的,index包括時間戳和pod的部分label(其他label為filename、containers等),其餘的是日志内容。具體查詢效果如下:
{app="loki",namespace="kube-public"}為索引
日志搜集架構模式
在使用過程中,官方推薦使用promtail做為agent以DaemonSet方式部署在kubernetes的worker節點上搜集日志。另外也可以用上面提到的其他日志收集工具來收取,這篇文章在結尾處會附上其他工具的配置方式。
Loki部署模式都有哪些呢
Loki由許多元件微服務建構而成,微服務元件有5個。在這5個裡面添加緩存用來把資料放起來加快查詢。資料放在共享存儲裡面配置memberlist_config部分并在執行個體之間共享狀态,将Loki進行無限橫向擴充。
在配置完memberlist_config部分後采用輪詢的方式查找資料。為了使用友善官方把所有的微服務編譯成一個二進制,可以通過指令行參數-target控制,支援all、read、write,我們在部署時根據日志量的大小可以指定不同模式
all(讀寫模式)
服務啟動後,我們做的資料查詢、資料寫入都是來自這一個節點。請看下面的這個圖解:
read/write(讀寫分離模式)
在讀寫分離模式下運作時fronted-query查詢會将流量轉發到read節點上。讀節點上保留了querier、ruler、fronted,寫節點上保留了distributor、ingester
微服務模式運作
微服務模式運作下,通過不同的配置參數啟動為不同的角色,每一個程序都引用它的目标角色服務。
大顯身手之服務端部署
上面我們講了那麼多關于loki的介紹和它的工作模式,你也一定期待它是怎麼部署的吧?!該怎麼部署、部署在哪裡、部署後怎麼使用等等問題都會出現在你的腦海裡。
在部署之前你需要準備好一個k8s叢集才行哦。那好,接下來耐着性子往下看……
AllInOne部署模式
① k8s部署
我們從github上下載下傳的程式是沒有配置檔案的,需要提前将檔案準備一份。這裡提供了一份完整的allInOne配置檔案,部分内容進行了優化。
配置檔案内容如下所示
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,在推送日志的時候字首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
# 需要提前建立好consul叢集
# 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
# 預設第一個網卡的名稱
# instance_interface_names
# instance_addr: 127.0.0.1
# 預設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
# 壓縮碎片索引
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 這裡沒有配置任何資訊
# 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子產品配置gossip用于在分發伺服器、攝取器和查詢器之間發現和連接配接。
# 所有三個元件的配置都是唯一的,以確定單個共享環。
# 至少定義了1個join_members配置後,将自動為分發伺服器、攝取器和ring 配置memberlist類型的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的值在單執行個體的情況下為1
ingester.lifecycler.min_ready_duration的值為15s,在啟動後預設會顯示15秒将狀态變為ready
memberlist.node_name的值可以不用設定,預設是目前主機的名稱
memberlist.join_members是一個清單,在有多個執行個體的情況下需要添加各個節點的主機名/IP位址。在k8s裡面可以設定成一個service綁定到StatefulSets。
query_range.results_cache.cache.enable_fifocache建議設定為false,我這裡設定成了true
instance_interface_names是一個清單,預設的為["en0","eth0"],可以根據需要設定對應的網卡名稱,一般不需要進行特殊設定。
建立configmap
說明:将上面的内容寫入到一個檔案——>loki-all.yaml,把它作為一個configmap寫入k8s叢集。可以使用如下指令建立:
kubectl create configmap --from-file ./loki-all.yaml loki-all
可以通過指令檢視到已經建立好的configmap,具體操作詳見下圖
建立持久化存儲
在k8s裡面我們的資料是需要進行持久化的。Loki收集起來的日志資訊對于業務來說是至關重要的,是以需要在容器重新開機的時候日志能夠保留下來。
那麼就需要用到pv、pvc,後端存儲可以使用nfs、glusterfs、hostPath、azureDisk、cephfs等20種支援類型,這裡因為沒有對應的環境就采用了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
建立應用
準備好k8s的StatefulSet部署檔案後就可以直接在叢集裡面建立應用了。
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
在上面的配置檔案中我添加了一些pod級别的安全政策,這些安全政策還有叢集級别的PodSecurityPolicy,防止因為漏洞的原因造成叢集的整個崩潰,關于叢集級别的psp,可以詳見官方文檔
驗證部署結果
當看到上面的Running狀态時可以通過API的方式看一下分發器是不是正常工作,當顯示Active時正常才會正常分發日志流到收集器(ingester)
② 裸機部署
将loki放到系統的/bin/目錄下,準備grafana-loki.service控制檔案重載系統服務清單
[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 $MAINPID
[Install]
WantedBy=multi-user.target
重載系統清單指令,可以直接系統自動管理服務:
systemctl daemon-reload
# 啟動服務
systemctl start grafana-loki
# 停止服務
systemctl stop grafana-loki
# 重載應用
systemctl reload grafana-loki
大顯身手之Promtail部署
部署用戶端收集日志時也需要建立一個配置檔案,按照上面建立服務端的步驟建立。不同的是需要把日志内容push到服務端
① k8s部署
建立配置檔案
server:
log_level: info
http_listen_port: 3101
clients:
- url: http://loki:3100/loki/api/v1/push
positions:
filename: /run/promtail/positions.yaml
scrape_configs:
- job_name: kubernetes-pods
pipeline_stages:
- cri: {}
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels:
- __meta_kubernetes_pod_controller_name
regex: ([0-9a-z-.]+?)(-[0-9a-f]{8,10})?
action: replace
target_label: __tmp_controller_name
- source_labels:
- __meta_kubernetes_pod_label_app_kubernetes_io_name
- __meta_kubernetes_pod_label_app
- __tmp_controller_name
- __meta_kubernetes_pod_name
regex: ^;*([^;]+)(;.*)?$
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__
用上面的内容建立一個configMap,方法同上
建立DaemonSet檔案
Promtail是一個無狀态應用不需要進行持久化存儲隻需要部署到叢集裡面就可以了,還是同樣的準備DaemonSets建立檔案。
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
建立promtail應用
kubectl apply -f promtail.yaml
使用上面這個指令建立後就可以看到服務已經建立好了。接下來就是在Grafana裡面添加DataSource檢視資料了。
② 裸機部署
如果是裸機部署的情況下,需要對上面的配置檔案做一下稍微的改動,更改clients得位址就可以,檔案存放到/etc/loki/下,例如改成:
clients:
- url: http://ipaddress:port/loki/api/v1/push
添加系統開機啟動配置,service配置檔案存放位置/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
啟動方式同上面服務端部署内容
Loki in DataSource
添加資料源
具體步驟: Grafana->Setting->DataSources->AddDataSource->Loki
注意點:
http的URL位址,應用、服務部署在哪個namespace下,就需要指定它的FQDN位址,它的格式是ServiceName.namespace。如果預設在default下、建立的端口号是3100,就需要填寫為http://loki:3100,這裡為什麼不寫IP位址而寫成服務的名字,是因為在k8s叢集裡面有個dns伺服器會自動解析這個位址。
查找日志資訊
其他用戶端配置
Logstash作為日志收集用戶端
安裝插件
在啟動Logstash後我們需要安裝一個插件,可以通過這個指令安裝loki的輸出插件,安裝完成之後可以在logstash的output中添加資訊。
bin/logstash-plugin install logstash-output-loki
添加配置進行測試
完整的logstash配置資訊,可以參考官網給出的内容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輸出子產品,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}"}'
}
}
Helm安裝
如果你想簡便安裝的話,可以采用helm來安裝。helm将所有的安裝步驟都進行了封裝,簡化了安裝步驟。
對于想詳細了解k8s的人來說,helm不太适合。因為它封裝後自動執行,k8s管理者不知道各元件之間是如何依賴的,可能會造成誤區。
廢話不多說,下面開始helm安裝
添加repo源
helm repo add grafana https://grafana.github.io/helm-charts
更新源
helm repo update
部署
預設配置
helm upgrade --install loki grafana/loki-simple-scalable
自定義namespace
helm upgrade --install loki --namespace=loki grafana/loki-simple-scalable
自定義配置資訊
helm upgrade --install loki grafana/loki-simple-scalable --set "key1=val1,key2=val2,..."
8故障解決方案
1.502 BadGateWay
loki的位址填寫不正确
在k8s裡面,位址填寫錯誤造成了502。檢查一下loki的位址是否是以下内容:
http://LokiServiceName
http://LokiServiceName.namespace
http://LokiServiceName.namespace:ServicePort
grafana和loki在不同的節點上,檢查一下節點間網絡通信狀态、防火牆政策
2.Ingester not ready: instance xx:9095 in state JOINING
耐心等待一會,因為是allInOne模式程式啟動需要一定的時間。
3.too many unhealthy instances in the ring
将ingester.lifecycler.replication_factor改為1,是因為這個設定不正确造成的。這個在啟動的時候會設定為多個複制源,但目前隻部署了一個是以在檢視label的時候提示這個
4.Data source connected, but no labels received. Verify that Loki and Promtail is configured properly
- promtail無法将收集到的日志發送給loki,許可檢查一下promtail的輸出是不是正常
- promtail在loki還沒有準備就緒的時候把日志發送過來了,但loki沒有接收到。如果需要重新接收日志,需要删除positions.yaml檔案,具體路徑可以用find查找一下位置
- promtail忽略了目标日志檔案或者配置檔案錯誤造成的無法正常啟動
- promtail無法在指定的位置發現日志檔案
官方文檔:
- https://kubernetes.io/docs/concepts/security/pod-security-policy/
感謝閱讀,希望對你有所幫助 :) 來源:juejin.cn/post/7150469420605767717
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