只有图文的网站如何做,铁岭做网站包括哪些,宜宾做网站,做迅雷下载电影类网站会侵权么背景本文简单介绍下#xff0c;Prometheus如何通过exporters监控Oracle数据库#xff0c;以及应该注意哪些指标。oracledb_exporteroracledb_exporter是一个连接到Oracle数据库并生成Prometheus metrics的应用程序#xff0c;设置展示下如何安装和设置oracledb_exporterPrometheus如何通过exporters监控Oracle数据库以及应该注意哪些指标。oracledb_exporteroracledb_exporter是一个连接到Oracle数据库并生成Prometheus metrics的应用程序设置展示下如何安装和设置oracledb_exporter以使用Prometheus来监控Oracle数据库。oracledb_exporter部署在k8s集群中在k8s使用Deployment部署oracledb_exporter并添加注解以实现Prometheus自动发现oracledb_exporter断点并收集指标spec:template:metadata:annotations:prometheus.io/scrape: trueprometheus.io/port: 9161prometheus.io/path: /metricsoracledb_exporter需要Oracle的连接信息才能访问和生成指标此参数作为环境变量传递到exporter。由于连接信息包含用于访问数据库的用户和密码因此我们将使用Kubernetes Secret来存储它。要创建到Oracle数据库的连接字符串的密码可以使用以下命令kubectl create secret generic oracledb-exporter-secret \--from-literaldatasourceYOUR_CONNECTION_STRING在deployment中这样配置环境变量env:- name: DATA_SOURCE_NAMEvalueFrom:secretKeyRef:name: oracledb-exporter-secretkey: datasource要确保连接信息是否正确system/password//database_url:1521/database_name.your.domain.com可以使用 sqlplus docker镜像进行检测docker run --nethost --rm --interactive guywithnose/sqlplus sqlplus system/password//database_url:1521/database_name.my.domain.com下面添加一些自定义指标包括慢查询(slow queries)错误查询(bug queries)为了使用自定义指标在deployment中我们将添加另一个环境变量该变量具有到新指标的文件的路由。从ConfigMap将此新文件挂载为volume完整配置如下apiVersion: apps/v1kind: Deploymentmetadata:name: oracledb-exporternamespace: database-namespacespec:selector:matchLabels:app: oracledb-exporterreplicas: 1template:metadata:labels:app: oracledb-exporterannotations:prometheus.io/scrape: trueprometheus.io/port: 9161prometheus.io/path: /metricsspec:containers:- name: oracledb-exporterports:- containerPort: 9161image: iamseth/oracledb_exporterenv:- name: DATA_SOURCE_NAMEvalueFrom:secretKeyRef:name: oracledb-exporter-secretkey: datasource- name: CUSTOM_METRICSvalue: /tmp/custom-metrics.tomlvolumeMounts:- name: custom-metricsmountPath: /tmp/custom-metrics.tomlsubPath: custom-metrics.tomlvolumes:- name: custom-metricsconfigMap:defaultMode: 420name: custom-metricsConfigMap:apiVersion: v1kind: ConfigMapmetadata:name: custom-metricsnamespace: database-namespacedata:custom-metrics.toml: |[[metric]]context slow_queriesmetricsdesc { p95_time_usecs Gauge metric with percentile 95 of elapsed time., p99_time_usecs Gauge metric with percentile 99 of elapsed time. }request select percentile_disc(0.95) within group (order by elapsed_time) as p95_time_usecs, percentile_disc(0.99) within group (order by elapsed_time) as p99_time_usecs from v$sql where last_active_time sysdate - 5/(24*60)[[metric]]context big_queriesmetricsdesc { p95_rows Gauge metric with percentile 95 of returned rows., p99_rows Gauge metric with percentile 99 of returned rows. }request select percentile_disc(0.95) within group (order by rownum) as p95_rows, percentile_disc(0.99) within group (order by rownum) as p99_rows from v$sql where last_active_time sysdate - 5/(24*60)[[metric]]context size_user_segments_top100metricsdesc {table_bytesGauge metric with the size of the tables in user segments.}labels [segment_name]request select * from (select segment_name,sum(bytes) as table_bytes from user_segments where segment_typeTABLE group by segment_name) order by table_bytes DESC FETCH NEXT 100 ROWS ONLY[[metric]]context size_user_segments_top100metricsdesc {table_partition_bytesGauge metric with the size of the table partition in user segments.}labels [segment_name]request select * from (select segment_name,sum(bytes) as table_partition_bytes from user_segments where segment_typeTABLE PARTITION group by segment_name) order by table_partition_bytes DESC FETCH NEXT 100 ROWS ONLY[[metric]]context size_user_segments_top100metricsdesc {cluster_bytesGauge metric with the size of the cluster in user segments.}labels [segment_name]request select * from (select segment_name,sum(bytes) as cluster_bytes from user_segments where segment_typeCLUSTER group by segment_name) order by cluster_bytes DESC FETCH NEXT 100 ROWS ONLY[[metric]]context size_dba_segments_top100metricsdesc {table_bytesGauge metric with the size of the tables in user segments.}labels [segment_name]request select * from (select segment_name,sum(bytes) as table_bytes from dba_segments where segment_typeTABLE group by segment_name) order by table_bytes DESC FETCH NEXT 100 ROWS ONLY[[metric]]context size_dba_segments_top100metricsdesc {table_partition_bytesGauge metric with the size of the table partition in user segments.}labels [segment_name]request select * from (select segment_name,sum(bytes) as table_partition_bytes from dba_segments where segment_typeTABLE PARTITION group by segment_name) order by table_partition_bytes DESC FETCH NEXT 100 ROWS ONLY[[metric]]context size_dba_segments_top100metricsdesc {cluster_bytesGauge metric with the size of the cluster in user segments.}labels [segment_name]request select * from (select segment_name,sum(bytes) as cluster_bytes from dba_segments where segment_typeCLUSTER group by segment_name) order by cluster_bytes DESC FETCH NEXT 100 ROWS ONLY创建Secret和ConfigMap之后就可以应用Deployment并检查它是否正在从Oracle数据库的端口9161中获取指标。如果一切正常Prometheus将自动发现exporter带注释的pod并在几分钟内开始抓取指标。可以在Prometheus Web界面的target部分中对其进行检查以查找以oracledb_开头的任何指标。监控什么性能指标等待时间: exporter在Oracle数据库的不同活动中提供一系列等待时间的指标。它们都以oracledb_wait_time_前缀开头它们有助于评估数据库在哪里花费了更多时间。它可以存在于I/O网络提交并发等中。通过这种方式我们可以确定系统中可能影响Oracle数据库整体性能的瓶颈。慢查询某些查询返回结果所花的时间可能比其他查询长。如果此时间高于应用程序中配置的接收响应的超时时间它将认为这是来自数据库的超时错误然后重试查询。这种行为可能会使系统超负荷工作并影响整体性能。在上面显示的配置中有两个自定义指标可提供最近5分钟内执行查询的响应时间的百分比95和99的信息。这些指标是oracledb_slow_queries_p95_time_usecsoracledb_slow_queries_p99_time_usecs活动会话监视Oracle数据库中活动会话很重要。如果超过配置的限制则数据库将拒绝新连接从而导致应用程序错误。提供此信息的指标是oracledb_sessions_value标签status可以提供更多信息。活动监视数据库执行的操作也很重要。为此我们可以依靠以下指标oracledb_activity_execute_countoracledb_activity_parse_count_totaloracledb_activity_user_commitsoracledb_activity_user_rollbacks
