未恢复事件列出¶
POST /api/v1/events/abnormal/list
概述¶
获取指定时间范围内的未恢复事件(相同df_monitor_checker_event_ref的最近一条事件状态不为ok)列表，一般查询最近6小时的数据;
Body 请求参数¶
| 参数名 | 类型 | 必选 | 说明 |
|---|---|---|---|
| search | string | 搜索事件标题 允许为空: False |
|
| lastStatus | string | 最后状态 允许为空: False 例子: critical 可选值: ['critical', 'error', 'warning', 'nodata'] |
|
| timeRange | array | Y | 时间范围, 默认取最近6小时，时差不超过6小时 允许为空: False $minLength: 2 最大长度: 2 例子: [1642563283250, 1642563304850] |
| timeRange[*] | integer | Y | 毫秒级整数时间戳 允许为空: False |
| filters | array | 过滤条件列表 允许为空: False |
|
| offset | integer | 偏移量 允许为空: False 例子: 10 $minValue: 0 |
|
| limit | integer | 每页返回数量 允许为空: False 例子: 10 $minValue: 1 $maxValue: 100 |
参数补充说明¶
参数说明:
模板的基础结构组成包含: 视图结构(含图表结构, 视图变量结构，图表分组结构)
filters的主体结构说明
| 参数名 | type | 必选 | 说明 |
|---|---|---|---|
| condition | string | 与前一个过滤条件的关系，可选值:and, or; 默认值: and |
|
| filters | array | 子过滤条件，相当于是加了一层括号, 存在当前参数时，仅有condition生效, 其他参数将失效 |
|
| name | string | 待过滤的字段名 | |
| operation | string | 运算符, 可选值: >, >=, <, <=, =, !=, in, wildcard, query_string, exists |
|
| value | array | 值列表 | |
| value[#] | string/int/boolean | 可为字符串/数值/布尔类型, 在比较数据时将根据operation的特性从value中取特定元素比较，例如，operation为=时，仅 value[0]参与运算 |
** filters 举例
[
{
"name": "A",
"condition": "and",
"operation": "between",
"value": [1577410594000, 1577410494000]
},
{
"condition": "and",
"filters": [
{
"name": "tagA",
"condition": "and",
"operation": ">",
"value": 12,
},
{
"name": "tagB",
"condition": "and",
"operation": "=",
"value": ["fff"]
}
],
},
{
"name": "tagC",
"condition": "and",
"operation": "=",
"value": ["ok"]
}
]
请求例子¶
curl 'https://openapi.guance.com/api/v1/events/abnormal/list' \
-H 'DF-API-KEY: <DF-API-KEY>' \
-H 'Content-Type: application/json;charset=UTF-8' \
--data-raw '{"offset": 0, "limit": 10, "timeRange": [1642563283250, 1642563304850]}' \
--compressed
响应¶
{
"code": 200,
"content": {
"data": [
{
"__docid": "E_c7jodqs24loo3v53qc50",
"alert_time_ranges": [
[
1642541760000,
null
]
],
"date": 1642563300000,
"df_dimension_tags": "{\"host\":\"10-23-190-37\"}",
"df_event_id": "event-6ea0350eda12405dad9c1cba4b28cdc3",
"df_message": "critical\ncpu\n0.010000123409284342",
"df_meta": "{\"alerts_sent\":[],\"check_targets\":[{\"alias\":\"Result\",\"dql\":\"M::`cpu`:(NON_NEGATIVE_DERIVATIVE(`usage_user`) AS `DingTalk`) { `host` = '10-23-190-37' } BY `host`\",\"range\":3600}],\"checker_opt\":{\"id\":\"rul_xxxx32\",\"interval\":60,\"message\":\"{{ df_status }}\\n{{ df_monitor_checker_name }}\\n{{ Result }}\",\"name\":\"cpu\",\"noDataInterval\":0,\"recoverInterval\":0,\"rules\":[{\"conditionLogic\":\"and\",\"conditions\":[{\"alias\":\"Result\",\"operands\":[\"0.01\"],\"operator\":\">=\"}],\"status\":\"critical\"}],\"title\":\"title1\"},\"dimension_tags\":{\"host\":\"10-23-190-37\"},\"extra_data\":{\"type\":\"simpleCheck\"},\"monitor_opt\":{\"id\":\"monitor_xxxx32\",\"name\":\"Default Group\",\"type\":\"default\"}}",
"df_monitor_checker_event_ref": "320fed7a6dd82a0bcb2a539248e6bedc",
"df_status": "critical",
"df_title": "title1"
},
{
"__docid": "E_c7jodqs24loo3v53qc4g",
"alert_time_ranges": [
[
1642541760000,
null
]
],
"date": 1642563300000,
"df_dimension_tags": "{\"host\":\"10-23-190-37\"}",
"df_event_id": "event-d2366597f7244ae099d3fbda07d8ec5f",
"df_message": "critical\ncpu\n0.010000123409284342",
"df_meta": "{\"alerts_sent\":[],\"check_targets\":[{\"alias\":\"Result\",\"dql\":\"M::`cpu`:(NON_NEGATIVE_DERIVATIVE(`usage_user`) AS `DingTalk`) { `host` = '10-23-190-37' } BY `host`\",\"range\":3600}],\"checker_opt\":{\"id\":\"rul_xxxx32\",\"interval\":60,\"message\":\"{{ df_status }}\\n{{ df_monitor_checker_name }}\\n{{ Result }}\",\"name\":\"cpu\",\"noDataInterval\":0,\"recoverInterval\":0,\"rules\":[{\"conditionLogic\":\"and\",\"conditions\":[{\"alias\":\"Result\",\"operands\":[\"0.01\"],\"operator\":\">=\"}],\"status\":\"critical\"}],\"title\":\"title1\"},\"dimension_tags\":{\"host\":\"10-23-190-37\"},\"extra_data\":{\"type\":\"simpleCheck\"},\"monitor_opt\":{\"id\":\"monitor_xxxx32\",\"name\":\"Default Group\",\"type\":\"default\"}}",
"df_monitor_checker_event_ref": "899faaa6f042871f32fc58fe53b16e46",
"df_status": "critical",
"df_title": "title1"
}
],
"limit": 20,
"offset": 0,
"total_count": 2
},
"errorCode": "",
"message": "",
"success": true,
"traceId": "TRACE-4D5773BE-88B1-4167-A2F4-603A58404184"
}