使用Prometheus监控docker compose方式部署的ES
需求收集 ES 的指标, 并进行展示和告警;现状ES 通过 docker compose 安装所在环境的 K8S 集群有 Prometheus 和AlertManager 及 Grafana方案复用现有的监控体系, 通过: Prometheus 监控 ES.具体实现为:采集端 elasticsearch_exporter可以监控的指标为:NameTypeCardinalityHelpelastic
需求
收集 ES 的指标, 并进行展示和告警;
现状
- ES 通过 docker compose 安装
- 所在环境的 K8S 集群有 Prometheus 和 AlertManager 及 Grafana
方案
复用现有的监控体系, 通过: Prometheus 监控 ES.
具体实现为:
采集端 elasticsearch_exporter
可以监控的指标为:
Name | Type | Cardinality | Help |
---|---|---|---|
elasticsearch_breakers_estimated_size_bytes | gauge | 4 | Estimated size in bytes of breaker |
elasticsearch_breakers_limit_size_bytes | gauge | 4 | Limit size in bytes for breaker |
elasticsearch_breakers_tripped | counter | 4 | tripped for breaker |
elasticsearch_cluster_health_active_primary_shards | gauge | 1 | The number of primary shards in your cluster. This is an aggregate total across all indices. |
elasticsearch_cluster_health_active_shards | gauge | 1 | Aggregate total of all shards across all indices, which includes replica shards. |
elasticsearch_cluster_health_delayed_unassigned_shards | gauge | 1 | Shards delayed to reduce reallocation overhead |
elasticsearch_cluster_health_initializing_shards | gauge | 1 | Count of shards that are being freshly created. |
elasticsearch_cluster_health_number_of_data_nodes | gauge | 1 | Number of data nodes in the cluster. |
elasticsearch_cluster_health_number_of_in_flight_fetch | gauge | 1 | The number of ongoing shard info requests. |
elasticsearch_cluster_health_number_of_nodes | gauge | 1 | Number of nodes in the cluster. |
elasticsearch_cluster_health_number_of_pending_tasks | gauge | 1 | Cluster level changes which have not yet been executed |
elasticsearch_cluster_health_task_max_waiting_in_queue_millis | gauge | 1 | Max time in millis that a task is waiting in queue. |
elasticsearch_cluster_health_relocating_shards | gauge | 1 | The number of shards that are currently moving from one node to another node. |
elasticsearch_cluster_health_status | gauge | 3 | Whether all primary and replica shards are allocated. |
elasticsearch_cluster_health_timed_out | gauge | 1 | Number of cluster health checks timed out |
elasticsearch_cluster_health_unassigned_shards | gauge | 1 | The number of shards that exist in the cluster state, but cannot be found in the cluster itself. |
elasticsearch_clustersettings_stats_max_shards_per_node | gauge | 0 | Current maximum number of shards per node setting. |
elasticsearch_filesystem_data_available_bytes | gauge | 1 | Available space on block device in bytes |
elasticsearch_filesystem_data_free_bytes | gauge | 1 | Free space on block device in bytes |
elasticsearch_filesystem_data_size_bytes | gauge | 1 | Size of block device in bytes |
elasticsearch_filesystem_io_stats_device_operations_count | gauge | 1 | Count of disk operations |
elasticsearch_filesystem_io_stats_device_read_operations_count | gauge | 1 | Count of disk read operations |
elasticsearch_filesystem_io_stats_device_write_operations_count | gauge | 1 | Count of disk write operations |
elasticsearch_filesystem_io_stats_device_read_size_kilobytes_sum | gauge | 1 | Total kilobytes read from disk |
elasticsearch_filesystem_io_stats_device_write_size_kilobytes_sum | gauge | 1 | Total kilobytes written to disk |
elasticsearch_indices_active_queries | gauge | 1 | The number of currently active queries |
elasticsearch_indices_docs | gauge | 1 | Count of documents on this node |
elasticsearch_indices_docs_deleted | gauge | 1 | Count of deleted documents on this node |
elasticsearch_indices_docs_primary | gauge | Count of documents with only primary shards on all nodes | |
elasticsearch_indices_fielddata_evictions | counter | 1 | Evictions from field data |
elasticsearch_indices_fielddata_memory_size_bytes | gauge | 1 | Field data cache memory usage in bytes |
elasticsearch_indices_filter_cache_evictions | counter | 1 | Evictions from filter cache |
elasticsearch_indices_filter_cache_memory_size_bytes | gauge | 1 | Filter cache memory usage in bytes |
elasticsearch_indices_flush_time_seconds | counter | 1 | Cumulative flush time in seconds |
elasticsearch_indices_flush_total | counter | 1 | Total flushes |
elasticsearch_indices_get_exists_time_seconds | counter | 1 | Total time get exists in seconds |
elasticsearch_indices_get_exists_total | counter | 1 | Total get exists operations |
elasticsearch_indices_get_missing_time_seconds | counter | 1 | Total time of get missing in seconds |
elasticsearch_indices_get_missing_total | counter | 1 | Total get missing |
elasticsearch_indices_get_time_seconds | counter | 1 | Total get time in seconds |
...
展示端 基于Grafana
📚️ Reference:
告警指标 基于prometheus alertmanager
📚️ Reference:
ElasticSearch:https://awesome-prometheus-alerts.grep.to/rules.html#elasticsearch-1
实施步骤
以下为手动实施步骤
Docker Compose
docker pull quay.io/prometheuscommunity/elasticsearch-exporter:v1.3.0
docker-compose.yml
示例:
🐾 Warning:
exporter 在每次刮削时都会从 ElasticSearch 集群中获取信息,因此过短的刮削间隔会给 ES 主节点带来负载,特别是当你使用
--es.all
和--es.indices
运行时。我们建议你测量获取/_nodes/stats
和/_all/_stats
对你的ES集群来说需要多长时间,以确定你的刮削间隔是否太短。
原 ES 的 docker-copmose.yml
示例如下:
version: '3'
services:
elasticsearch:
image: elasticsearch-plugins:6.8.18
...
ports:
- 9200:9200
- 9300:9300
restart: always
增加了 elasticsearch_exporter
的yaml如下:
version: '3'
services:
elasticsearch:
image: elasticsearch-plugins:6.8.18
...
ports:
- 9200:9200
- 9300:9300
restart: always
elasticsearch_exporter:
image: quay.io/prometheuscommunity/elasticsearch-exporter:v1.3.0
command:
- '--es.uri=http://elasticsearch:9200'
- '--es.all'
- '--es.indices'
- '--es.indices_settings'
- '--es.indices_mappings'
- '--es.shards'
- '--es.snapshots'
- '--es.timeout=30s'
restart: always
ports:
- "9114:9114"
Prometheus 配置调整
prometheus 配置
Prometheus 增加静态抓取配置:
scrape_configs:
- job_name: "es"
static_configs:
- targets: ["x.x.x.x:9114"]
说明:
x.x.x.x 为 ES Exporter IP, 因为 ES Exporter 通过 docker compose 和 ES部署在同一台机器, 所以这个 IP 也是 ES 的IP.
Prometheus Rules
增加 ES 相关的 Prometheus Rules:
groups:
- name: elasticsearch
rules:
- record: elasticsearch_filesystem_data_used_percent
expr: 100 * (elasticsearch_filesystem_data_size_bytes - elasticsearch_filesystem_data_free_bytes)
/ elasticsearch_filesystem_data_size_bytes
- record: elasticsearch_filesystem_data_free_percent
expr: 100 - elasticsearch_filesystem_data_used_percent
- alert: ElasticsearchTooFewNodesRunning
expr: elasticsearch_cluster_health_number_of_nodes < 3
for: 0m
labels:
severity: critical
annotations:
description: "Missing node in Elasticsearch cluster\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
summary: ElasticSearch running on less than 3 nodes(instance {{ $labels.instance }}, node {{$labels.node}})
- alert: ElasticsearchDiskSpaceLow
expr: elasticsearch_filesystem_data_free_percent < 20
for: 2m
labels:
severity: warning
annotations:
summary: Elasticsearch disk space low (instance {{ $labels.instance }}, node {{$labels.node}})
description: "The disk usage is over 80%\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchDiskOutOfSpace
expr: elasticsearch_filesystem_data_free_percent < 10
for: 0m
labels:
severity: critical
annotations:
summary: Elasticsearch disk out of space (instance {{ $labels.instance }}, node {{$labels.node}})
description: "The disk usage is over 90%\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchHeapUsageWarning
expr: (elasticsearch_jvm_memory_used_bytes{area="heap"} / elasticsearch_jvm_memory_max_bytes{area="heap"}) * 100 > 80
for: 2m
labels:
severity: warning
annotations:
summary: Elasticsearch Heap Usage warning (instance {{ $labels.instance }}, node {{$labels.node}})
description: "The heap usage is over 80%\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchHeapUsageTooHigh
expr: (elasticsearch_jvm_memory_used_bytes{area="heap"} / elasticsearch_jvm_memory_max_bytes{area="heap"}) * 100 > 90
for: 2m
labels:
severity: critical
annotations:
summary: Elasticsearch Heap Usage Too High (instance {{ $labels.instance }}, node {{$labels.node}})
description: "The heap usage is over 90%\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchClusterRed
expr: elasticsearch_cluster_health_status{color="red"} == 1
for: 0m
labels:
severity: critical
annotations:
summary: Elasticsearch Cluster Red (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elastic Cluster Red status\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchClusterYellow
expr: elasticsearch_cluster_health_status{color="yellow"} == 1
for: 0m
labels:
severity: warning
annotations:
summary: Elasticsearch Cluster Yellow (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elastic Cluster Yellow status\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchHealthyDataNodes
expr: elasticsearch_cluster_health_number_of_data_nodes < 3
for: 0m
labels:
severity: critical
annotations:
summary: Elasticsearch Healthy Data Nodes (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Missing data node in Elasticsearch cluster\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchRelocatingShards
expr: elasticsearch_cluster_health_relocating_shards > 0
for: 0m
labels:
severity: info
annotations:
summary: Elasticsearch relocating shards (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elasticsearch is relocating shards\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchRelocatingShardsTooLong
expr: elasticsearch_cluster_health_relocating_shards > 0
for: 15m
labels:
severity: warning
annotations:
summary: Elasticsearch relocating shards too long (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elasticsearch has been relocating shards for 15min\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchInitializingShards
expr: elasticsearch_cluster_health_initializing_shards > 0
for: 0m
labels:
severity: info
annotations:
summary: Elasticsearch initializing shards (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elasticsearch is initializing shards\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchInitializingShardsTooLong
expr: elasticsearch_cluster_health_initializing_shards > 0
for: 15m
labels:
severity: warning
annotations:
summary: Elasticsearch initializing shards too long (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elasticsearch has been initializing shards for 15 min\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchUnassignedShards
expr: elasticsearch_cluster_health_unassigned_shards > 0
for: 0m
labels:
severity: critical
annotations:
summary: Elasticsearch unassigned shards (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elasticsearch has unassigned shards\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchPendingTasks
expr: elasticsearch_cluster_health_number_of_pending_tasks > 0
for: 15m
labels:
severity: warning
annotations:
summary: Elasticsearch pending tasks (instance {{ $labels.instance }}, node {{$labels.node}})
description: "Elasticsearch has pending tasks. Cluster works slowly.\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
- alert: ElasticsearchNoNewDocuments
expr: increase(elasticsearch_indices_docs{es_data_node="true"}[10m]) < 1
for: 0m
labels:
severity: warning
annotations:
summary: Elasticsearch no new documents (instance {{ $labels.instance }}, node {{$labels.node}})
description: "No new documents for 10 min!\n VALUE = {{ $value }}\n LABELS = {{ $labels }}"
并重启生效.
🐾Warning:
ElasticsearchTooFewNodesRunning
告警的条件是 es 集群的node 少于 3个, 对于单节点 ES 会误报, 所以按需开启rule或按需屏蔽(slience).ElasticsearchHealthyDataNodes
告警同上.
AlertManager 告警规则及收件人配置
按需调整, 示例如下:
'global':
'smtp_smarthost': ''
'smtp_from': ''
'smtp_require_tls': false
'resolve_timeout': '5m'
'receivers':
- 'name': 'es-email'
'email_configs':
- 'to': 'sfw@example.com,sdfwef@example.com'
'send_resolved': true
'route':
'group_by':
- 'job'
'group_interval': '5m'
'group_wait': '30s'
'routes':
- 'receiver': 'es-email'
'match':
'job': 'es'
并重启生效.
Grafana 配置
导入 json 格式的 Grafana Dashboard: (完整Dashboard可以直接通过 Grafana 搜索获取)
{
"__inputs": [],
"__requires": [
{
"type": "grafana",
"id": "grafana",
"name": "Grafana",
"version": "5.4.0"
},
{
"type": "panel",
"id": "graph",
"name": "Graph",
"version": "5.0.0"
},
{
"type": "datasource",
"id": "prometheus",
"name": "Prometheus",
"version": "5.0.0"
},
{
"type": "panel",
"id": "singlestat",
"name": "Singlestat",
"version": "5.0.0"
}
],
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": "-- Grafana --",
"enable": true,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"type": "dashboard"
}
]
},
"editable": true,
"gnetId": null,
"graphTooltip": 1,
"id": null,
"iteration": 1549021227642,
"links": [],
"panels": [
{
"gridPos": {
"h": 1,
"w": 24,
"x": 0,
"y": 0
},
"id": 90,
"title": "Cluster",
"type": "row"
},
{
"cacheTimeout": null,
"colorBackground": true,
"colorPostfix": false,
"colorPrefix": false,
"colorValue": false,
"colors": [
"#299c46",
"rgba(237, 129, 40, 0.89)",
"#d44a3a"
],
"format": "none",
"gauge": {
"maxValue": 100,
"minValue": 0,
"show": false,
"thresholdLabels": false,
"thresholdMarkers": true
},
"gridPos": {
"h": 3,
"w": 12,
"x": 0,
"y": 1
},
"id": 92,
"interval": null,
"links": [],
"mappingType": 1,
"mappingTypes": [
{
"name": "value to text",
"value": 1
},
{
"name": "range to text",
"value": 2
}
],
"maxDataPoints": 100,
"nullPointMode": "connected",
"nullText": null,
"postfix": "",
"postfixFontSize": "50%",
"prefix": "",
"prefixFontSize": "50%",
"rangeMaps": [
{
"from": "null",
"text": "N/A",
"to": "null"
}
],
"sparkline": {
"fillColor": "rgba(31, 118, 189, 0.18)",
"full": false,
"lineColor": "rgb(31, 120, 193)",
"show": false
},
"tableColumn": "Value",
"targets": [
{
"expr": "scalar(elasticsearch_cluster_health_status{color=\"green\",cluster=~\"$cluster\"}) + scalar(elasticsearch_cluster_health_status{color=\"yellow\",cluster=~\"$cluster\"}) * 2 + scalar(elasticsearch_cluster_health_status{color=\"red\",cluster=~\"$cluster\"}) * 3",
"format": "time_series",
"instant": false,
"intervalFactor": 1,
"legendFormat": "",
"refId": "A"
}
],
...
📚️ 参考文档
- prometheus-community/elasticsearch_exporter: Elasticsearch stats exporter for Prometheus (github.com)
- ElasticSearch dashboard for Grafana | Grafana Labs
- Awesome Prometheus alerts | Collection of alerting rules (grep.to)
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