ES
1 数据源
1.1 ES 数据
"vm_doc": {
"env_type": "online", # sandbox/online
"pool": "xxx", # pool
"region": "xxx", # region
"zone": "AZONE-xxx", # 可用区
"deployset_name": "xxx", # 部署集
"host_ip": "xx.xx.xx.xx", # 机器 ip
"is_reserve": "no", # 是否为预留机器
"free_cpu_in_core": 5, # cpu 库存
"free_mem_size_in_mb": 42021, # mem 库存
"free_disk_size_in_gb": 330, # disk 库存
"allocated_cpu_in_core": 3, # cpu 已分配量
"allocated_mem_size_in_mb": 11979, # mem 已分配量
"allocated_disk_size_in_gb": 120, # disk 已分片量
"used_mem_size_in_mb": 2048, # mem 已使用量
"total_cpu_in_core", # cpu 逻辑总量
"total_mem_size_in_mb", # mem 逻辑总量
"total_disk_size_in_gb", # disk 逻辑总量
"physical_total_cpu_in_core", # cpu 物理总量
"physical_total_mem_size_in_mb", # mem 物理总量
"instance_count": 3, # 机器上容器个数
"day_time": "2022-08-20",
"timestamp": "2022-08-20T10:35:22.488559",
}1.2 配置(add data source)
索引格式: vm-unit_2022-08-20参数
值
Index name
[vm-unit_]YYYY-MM-DD
Pattern
Daily
Time field name
timestamp
ElasticSearch version
7.10+
Max concurrent Shard Requests
5
Min time interval
1d
2 仪表盘变量(dashboard/dashboard settings/Variables)
添加如下变量后，会在 dashboard 的上方出现下拉框
env_type {"find": "terms", "field": "env_type.keyword", "size": 100}
pool {"find": "terms", "field": "pool.keyword", "size": 100}
zone {"find": "terms", "field": "zone.keyword", "size": 100}
deployset_name {"find": "terms", "field": "deployset_name.keyword", "size": 100, "query": "zone:$zone"} 2.1 操作方法
General:
Name:pool
Type:Query
-------其他项为空
Query Options:
Data source: ${data_source}
Refresh: On dashboard load
Query: {"find": "terms", "field": "pool.keyword", "size": 100}
Regex: 空
Sort： Disable
Selection options：
Multi-value: true
Include All option: true
Custom all value: 空3 仪表盘(汇总图)
3.1 机器数量(折线图)
Query:
pool:$pool AND env_type:online AND is_reserve:no
Alias
无
Metric:
count
Group By
Terms, pool.keyword, Top 10, Min Doc Count: 1, Order by: Count
Then By
Date Histogram, timestamp, Interval: 1dTerms: 表示查询具体的值
Date Histogram：时间直方图
上面图会根据 pool 展示多条曲线，每条曲线代表一个 pool，横坐标是时间。
如果要对 pool 进行汇总，则可以点击 Transform，然后点击 Add field from calculation
Mode
Reduce row
Field name
pool1,pool2
Calculation
Total
Alias
Total
Replace all fields
false这样就会汇总 pool1 和 pool2 数据为 Total 了
3.2 内存
CPU 与内存指标类似
3.2.1 内存总分配量 or 物理总内存
Query
pool:$pool AND env_type:online AND is_reserve:no
Alias
无
Metric (1)
Sum，allocated_mem_size_in_mb
Group By
Terms, pool.keyword, Top 10, Min Doc Count: 1, Order by: Sum allocated_mem_size_in_mb
Then By
Date Histogram, timestamp, Interval: 1d再根据 3.1 生成下所有 pool 的总量曲线图。
3.2.2 内存分配率
内存分配率需要按照池单独生成图(如生成 pool1 的内存分配率)
Query
A----------------------------------------------
Query
pool:pool1 AND env_type:online AND is_reserve:no
Alias
allocated_mem
Metric (1)
Sum, allocated_mem_size_in_mb
Group By
Date Histogram, timestamp, Interval: 1d
B----------------------------------------------
Query
pool:scs AND env_type:online AND is_reserve:no
Alias
sum_mem
Metric (1)
Sum, physical_total_mem_size_in_mb
Group By
Date Histogram, timestamp, Interval: 1dTransform
Add field from calculation
Mode
Binary operation
Operation
allocated_mem/sum_mem
Alias
allocated_mem / sum_mem
Replace all fields
true(这里需要设置为 true，只显示比例图)4 仪表盘(按部署集区分)
4.1 机器数量(折线图)
每个部署集(deployset_name) 1 条曲线，横坐标是时间(每天一个点)
Query:
zone:$zone AND pool:$pool AND deployset_name:$deployset_name AND env_type:$env_type
Metric:
count
Group By:
Terms, zone.keyword, Top 10, Min Doc Count: 1, Order by: Count
Then By:
Date Histogram, timestamp, Interval: 1d4.2 库存(折线图)
每个部署集(deployset_name) 1 条曲线，横坐标是时间(每天一个点)
Query:
zone:$zone AND pool:$pool AND deployset_name:$deployset_name AND env_type:$env_type
Metric (1)
Sum, free_cpu_in_core
Group By:
Terms, deployset_name.keyword, Top 10, Min Doc Count: 1, Order by: Sum free_cpu_in_core
Then By
Date Histogram, timestamp, Interval: 1dLast updated