目录
输入和输出集成概述
Telegraf 的 Ceph 插件有助于从 Ceph 存储集群中的 MON 和 OSD 节点收集性能指标,以实现有效的监控和管理。
InfluxDB 插件将指标写入 InfluxDB HTTP 服务,从而可以高效地存储和检索时序数据。
集成详情
Ceph
Ceph Storage Telegraf 插件旨在从 Ceph 存储集群中的 Monitor (MON) 和 Object Storage Daemon (OSD) 节点收集性能指标。Ceph 是一种高度可扩展的存储系统,通过此插件集成其指标收集,从而方便监控其组件。随着 13.x Mimic 版本中此插件的引入,用户可以有效地收集有关其 Ceph 基础设施的性能和运行状况的详细见解。它的工作原理是扫描配置的套接字目录以查找特定的 Ceph 服务套接字文件,通过 Ceph 管理界面执行命令,并解析返回的 JSON 数据以获取指标。这些指标基于顶级键进行组织,从而可以有效地监控和分析集群性能。此插件通过允许管理员了解系统行为并主动识别潜在问题,为管理和维护 Ceph 集群的性能提供了有价值的功能。
InfluxDB
InfluxDB Telegraf 插件用于将指标发送到 InfluxDB HTTP API,从而以结构化方式方便时序数据的存储和查询。此插件与 InfluxDB 无缝集成,提供诸如基于令牌的身份验证和对多个 InfluxDB 集群节点的支持等基本功能,确保了可靠且可扩展的数据摄取。通过其可配置性,用户可以指定诸如组织、目标存储桶和 HTTP 特定设置等选项,从而灵活地定制数据的发送和存储方式。该插件还支持敏感数据的密钥管理,从而增强了生产环境中的安全性。此插件在现代可观测性堆栈中尤其有益,在这些堆栈中,实时分析和时序数据的存储至关重要。
配置
Ceph
[[inputs.ceph]]
## This is the recommended interval to poll. Too frequent and you
## will lose data points due to timeouts during rebalancing and recovery
interval = '1m'
## All configuration values are optional, defaults are shown below
## location of ceph binary
ceph_binary = "/usr/bin/ceph"
## directory in which to look for socket files
socket_dir = "/var/run/ceph"
## prefix of MON and OSD socket files, used to determine socket type
mon_prefix = "ceph-mon"
osd_prefix = "ceph-osd"
mds_prefix = "ceph-mds"
rgw_prefix = "ceph-client"
## suffix used to identify socket files
socket_suffix = "asok"
## Ceph user to authenticate as, ceph will search for the corresponding
## keyring e.g. client.admin.keyring in /etc/ceph, or the explicit path
## defined in the client section of ceph.conf for example:
##
## [client.telegraf]
## keyring = /etc/ceph/client.telegraf.keyring
##
## Consult the ceph documentation for more detail on keyring generation.
ceph_user = "client.admin"
## Ceph configuration to use to locate the cluster
ceph_config = "/etc/ceph/ceph.conf"
## Whether to gather statistics via the admin socket
gather_admin_socket_stats = true
## Whether to gather statistics via ceph commands, requires ceph_user
## and ceph_config to be specified
gather_cluster_stats = false
InfluxDB
[[outputs.influxdb]]
## The full HTTP or UDP URL for your InfluxDB instance.
##
## Multiple URLs can be specified for a single cluster, only ONE of the
## urls will be written to each interval.
# urls = ["unix:///var/run/influxdb.sock"]
# urls = ["udp://127.0.0.1:8089"]
# urls = ["http://127.0.0.1:8086"]
## Local address to bind when connecting to the server
## If empty or not set, the local address is automatically chosen.
# local_address = ""
## The target database for metrics; will be created as needed.
## For UDP url endpoint database needs to be configured on server side.
# database = "telegraf"
## The value of this tag will be used to determine the database. If this
## tag is not set the 'database' option is used as the default.
# database_tag = ""
## If true, the 'database_tag' will not be included in the written metric.
# exclude_database_tag = false
## If true, no CREATE DATABASE queries will be sent. Set to true when using
## Telegraf with a user without permissions to create databases or when the
## database already exists.
# skip_database_creation = false
## Name of existing retention policy to write to. Empty string writes to
## the default retention policy. Only takes effect when using HTTP.
# retention_policy = ""
## The value of this tag will be used to determine the retention policy. If this
## tag is not set the 'retention_policy' option is used as the default.
# retention_policy_tag = ""
## If true, the 'retention_policy_tag' will not be included in the written metric.
# exclude_retention_policy_tag = false
## Write consistency (clusters only), can be: "any", "one", "quorum", "all".
## Only takes effect when using HTTP.
# write_consistency = "any"
## Timeout for HTTP messages.
# timeout = "5s"
## HTTP Basic Auth
# username = "telegraf"
# password = "metricsmetricsmetricsmetrics"
## HTTP User-Agent
# user_agent = "telegraf"
## UDP payload size is the maximum packet size to send.
# udp_payload = "512B"
## Optional TLS Config for use on HTTP connections.
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## HTTP Proxy override, if unset values the standard proxy environment
## variables are consulted to determine which proxy, if any, should be used.
# http_proxy = "http://corporate.proxy:3128"
## Additional HTTP headers
# http_headers = {"X-Special-Header" = "Special-Value"}
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "gzip"
## When true, Telegraf will output unsigned integers as unsigned values,
## i.e.: "42u". You will need a version of InfluxDB supporting unsigned
## integer values. Enabling this option will result in field type errors if
## existing data has been written.
# influx_uint_support = false
## When true, Telegraf will omit the timestamp on data to allow InfluxDB
## to set the timestamp of the data during ingestion. This is generally NOT
## what you want as it can lead to data points captured at different times
## getting omitted due to similar data.
# influx_omit_timestamp = false
输入和输出集成示例
Ceph
-
动态监控仪表板:利用 Ceph 插件创建一个实时监控仪表板,以可视化方式表示 Ceph 集群的性能指标。通过将这些指标集成到集中式仪表板中,系统管理员可以立即深入了解存储基础设施的运行状况,这有助于快速识别和解决潜在问题,防止问题升级。
-
自动化警报系统:将 Ceph 插件与警报解决方案结合使用,以自动通知管理员 Ceph 集群内的性能下降或操作问题。通过为关键指标定义阈值,组织可以确保快速响应措施,从而提高整体系统可靠性和性能。
-
性能基准测试:使用此插件收集的指标,对 Ceph 存储集群的不同配置或硬件设置进行性能基准测试。此过程可以帮助组织识别可增强性能和资源利用率的最佳配置,从而促进更高效的存储环境。
-
容量规划和预测:将从 Ceph 存储插件收集的指标集成到更广泛的数据分析和报告工具中,以方便容量规划。通过分析历史指标,组织可以预测未来的利用率趋势,从而就有效扩展存储资源做出明智的决策。
InfluxDB
-
实时系统监控:利用 InfluxDB 插件捕获和存储来自各种系统组件(如 CPU 使用率、内存消耗和磁盘 I/O)的指标。通过将这些指标推送到 InfluxDB,您可以创建一个实时仪表板,以可视化方式实时显示系统性能。这种设置不仅有助于识别性能瓶颈,还可以通过分析随时间变化的趋势来协助主动容量规划。
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Web 应用程序的性能跟踪:自动收集与 Web 应用程序性能相关的指标(如请求持续时间、错误率和用户交互),并将它们推送到 InfluxDB。通过在您的监控堆栈中使用此插件,您可以使用存储的指标生成报告和分析,以帮助了解用户行为和应用程序效率,从而指导开发和优化工作。
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物联网数据聚合:利用 InfluxDB Telegraf 插件从各种物联网设备收集传感器数据,并将其存储在集中的 InfluxDB 实例中。此用例使您能够分析随时间变化的环境或机器数据的趋势和模式,从而促进更智能的决策和预测性维护策略。通过将物联网数据集成到 InfluxDB 中,组织可以利用历史数据分析的力量来推动创新和运营效率。
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分析历史指标以进行预测:设置 InfluxDB 插件以将历史指标数据发送到 InfluxDB,并使用它来驱动预测模型。通过分析过去的性能指标,您可以创建预测未来趋势和需求的预测模型。此应用程序对于商业智能目的尤其有用,有助于组织根据历史使用模式为资源需求的波动做好准备。
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