对于大规模实时查询，这不是推荐的配置。为了实现查询和压缩优化、高速摄取和高可用性，您可能需要考虑OPC UA 和 InfluxDB。
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时间序列数据库
来源：DB Engines
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贡献者
目录
强大的性能，无限的扩展能力
收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时，它都更有价值。InfluxDB 是排名第一的时间序列平台，旨在通过 Telegraf 进行扩展。
查看入门方法
输入和输出集成概述
OPC UA 插件提供了一个从 OPC UA 服务器设备检索数据的接口，从而促进有效的数据收集和监控。
Prometheus 输出插件使 Telegraf 能够在 HTTP 端点公开指标，以供 Prometheus 服务器抓取。此集成允许用户以 Prometheus 可以有效处理的格式从各种来源收集和聚合指标。
集成详情
OPC UA
OPC UA 插件从使用 OPC UA 协议通信的设备检索数据，使您可以收集和监控来自 OPC UA 服务器的数据。
Prometheus
此插件促进了与 Prometheus 的集成，Prometheus 是一种著名的开源监控和警报工具包，专为大规模环境中的可靠性和效率而设计。作为 Prometheus 客户端，它允许用户通过 HTTP 服务器公开一组定义的指标，Prometheus 可以按指定的间隔抓取这些指标。此插件在监控各种系统中起着至关重要的作用，它允许这些系统以标准化格式发布性能指标，从而全面了解系统健康状况和行为。主要功能包括支持配置各种端点、启用 TLS 以进行安全通信以及 HTTP 基本身份验证选项。该插件还与全局 Telegraf 配置设置无缝集成，支持广泛的自定义以适应特定的监控需求。这促进了不同系统必须有效通信性能数据的环境中的互操作性。通过利用 Prometheus 的指标格式，它可以通过指标过期和收集器控制等高级配置来灵活地管理指标，为监控和警报工作流程提供了完善的解决方案。
配置
OPC UA
[[inputs.opcua]]
## Metric name
# name = "opcua"
#
## OPC UA Endpoint URL
# endpoint = "opc.tcp://localhost:4840"
#
## Maximum time allowed to establish a connect to the endpoint.
# connect_timeout = "10s"
#
## Maximum time allowed for a request over the established connection.
# request_timeout = "5s"
# Maximum time that a session shall remain open without activity.
# session_timeout = "20m"
#
## Security policy, one of "None", "Basic128Rsa15", "Basic256",
## "Basic256Sha256", or "auto"
# security_policy = "auto"
#
## Security mode, one of "None", "Sign", "SignAndEncrypt", or "auto"
# security_mode = "auto"
#
## Path to cert.pem. Required when security mode or policy isn't "None".
## If cert path is not supplied, self-signed cert and key will be generated.
# certificate = "/etc/telegraf/cert.pem"
#
## Path to private key.pem. Required when security mode or policy isn't "None".
## If key path is not supplied, self-signed cert and key will be generated.
# private_key = "/etc/telegraf/key.pem"
#
## Authentication Method, one of "Certificate", "UserName", or "Anonymous". To
## authenticate using a specific ID, select 'Certificate' or 'UserName'
# auth_method = "Anonymous"
#
## Username. Required for auth_method = "UserName"
# username = ""
#
## Password. Required for auth_method = "UserName"
# password = ""
#
## Option to select the metric timestamp to use. Valid options are:
## "gather" -- uses the time of receiving the data in telegraf
## "server" -- uses the timestamp provided by the server
## "source" -- uses the timestamp provided by the source
# timestamp = "gather"
#
## Client trace messages
## When set to true, and debug mode enabled in the agent settings, the OPCUA
## client's messages are included in telegraf logs. These messages are very
## noisey, but essential for debugging issues.
# client_trace = false
#
## Include additional Fields in each metric
## Available options are:
## DataType -- OPC-UA Data Type (string)
# optional_fields = []
#
## Node ID configuration
## name - field name to use in the output
## namespace - OPC UA namespace of the node (integer value 0 thru 3)
## identifier_type - OPC UA ID type (s=string, i=numeric, g=guid, b=opaque)
## identifier - OPC UA ID (tag as shown in opcua browser)
## tags - extra tags to be added to the output metric (optional); deprecated in 1.25.0; use default_tags
## default_tags - extra tags to be added to the output metric (optional)
##
## Use either the inline notation or the bracketed notation, not both.
#
## Inline notation (default_tags not supported yet)
# nodes = [
# {name="", namespace="", identifier_type="", identifier="", tags=[["tag1", "value1"], ["tag2", "value2"]},
# {name="", namespace="", identifier_type="", identifier=""},
# ]
#
## Bracketed notation
# [[inputs.opcua.nodes]]
# name = "node1"
# namespace = ""
# identifier_type = ""
# identifier = ""
# default_tags = { tag1 = "value1", tag2 = "value2" }
#
# [[inputs.opcua.nodes]]
# name = "node2"
# namespace = ""
# identifier_type = ""
# identifier = ""
#
## Node Group
## Sets defaults so they aren't required in every node.
## Default values can be set for:
## * Metric name
## * OPC UA namespace
## * Identifier
## * Default tags
##
## Multiple node groups are allowed
#[[inputs.opcua.group]]
## Group Metric name. Overrides the top level name. If unset, the
## top level name is used.
# name =
#
## Group default namespace. If a node in the group doesn't set its
## namespace, this is used.
# namespace =
#
## Group default identifier type. If a node in the group doesn't set its
## namespace, this is used.
# identifier_type =
#
## Default tags that are applied to every node in this group. Can be
## overwritten in a node by setting a different value for the tag name.
## example: default_tags = { tag1 = "value1" }
# default_tags = {}
#
## Node ID Configuration. Array of nodes with the same settings as above.
## Use either the inline notation or the bracketed notation, not both.
#
## Inline notation (default_tags not supported yet)
# nodes = [
# {name="node1", namespace="", identifier_type="", identifier=""},
# {name="node2", namespace="", identifier_type="", identifier=""},
#]
#
## Bracketed notation
# [[inputs.opcua.group.nodes]]
# name = "node1"
# namespace = ""
# identifier_type = ""
# identifier = ""
# default_tags = { tag1 = "override1", tag2 = "value2" }
#
# [[inputs.opcua.group.nodes]]
# name = "node2"
# namespace = ""
# identifier_type = ""
# identifier = ""
## Enable workarounds required by some devices to work correctly
# [inputs.opcua.workarounds]
## Set additional valid status codes, StatusOK (0x0) is always considered valid
# additional_valid_status_codes = ["0xC0"]
# [inputs.opcua.request_workarounds]
## Use unregistered reads instead of registered reads
# use_unregistered_reads = false
Prometheus
[[outputs.prometheus_client]]
## Address to listen on.
## ex:
## listen = ":9273"
## listen = "vsock://:9273"
listen = ":9273"
## Maximum duration before timing out read of the request
# read_timeout = "10s"
## Maximum duration before timing out write of the response
# write_timeout = "10s"
## Metric version controls the mapping from Prometheus metrics into Telegraf metrics.
## See "Metric Format Configuration" in plugins/inputs/prometheus/README.md for details.
## Valid options: 1, 2
# metric_version = 1
## Use HTTP Basic Authentication.
# basic_username = "Foo"
# basic_password = "Bar"
## If set, the IP Ranges which are allowed to access metrics.
## ex: ip_range = ["192.168.0.0/24", "192.168.1.0/30"]
# ip_range = []
## Path to publish the metrics on.
# path = "/metrics"
## Expiration interval for each metric. 0 == no expiration
# expiration_interval = "60s"
## Collectors to enable, valid entries are "gocollector" and "process".
## If unset, both are enabled.
# collectors_exclude = ["gocollector", "process"]
## Send string metrics as Prometheus labels.
## Unless set to false all string metrics will be sent as labels.
# string_as_label = true
## If set, enable TLS with the given certificate.
# tls_cert = "/etc/ssl/telegraf.crt"
# tls_key = "/etc/ssl/telegraf.key"
## Set one or more allowed client CA certificate file names to
## enable mutually authenticated TLS connections
# tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
## Export metric collection time.
# export_timestamp = false
## Specify the metric type explicitly.
## This overrides the metric-type of the Telegraf metric. Globbing is allowed.
# [outputs.prometheus_client.metric_types]
# counter = []
# gauge = []
输入和输出集成示例
OPC UA
-
基本配置：使用 OPC UA 服务器端点和所需的指标设置插件。这允许 Telegraf 开始从配置的节点收集指标。
-
节点 ID 设置：使用配置指定特定节点，例如温度传感器，以实时监控其值。例如，配置节点
ns=3;s=Temperature以直接收集温度数据。 -
组配置：通过将多个节点分组在单个配置下，简化对多个节点的监控——这为该组中的所有节点设置默认值，从而减少设置中的冗余。
Prometheus
-
监控多云部署：利用 Prometheus 插件从跨多个云提供商运行的应用程序收集指标。这种情况允许团队通过单个 Prometheus 实例集中监控，该实例从不同环境抓取指标，从而提供跨混合基础设施的统一性能指标视图。它简化了报告和警报，提高了运营效率，而无需复杂的集成。
-
增强微服务可见性：实施该插件以公开 Kubernetes 集群中各种微服务的指标。使用 Prometheus，团队可以实时可视化服务指标、识别瓶颈并维护系统健康检查。此设置支持基于从收集的指标生成的见解进行自适应扩展和资源利用率优化。它增强了对服务交互进行故障排除的能力，从而显着提高了微服务架构的弹性。
-
电子商务中的实时异常检测：通过将此插件与 Prometheus 一起使用，电子商务平台可以监控关键绩效指标，例如响应时间和错误率。将异常检测算法与抓取的指标集成在一起，可以识别指示潜在问题的意外模式，例如突然的流量峰值或后端服务故障。这种主动监控增强了业务连续性和运营效率，最大限度地减少了潜在的停机时间，同时确保了服务的可靠性。
-
API 的性能指标报告：利用 Prometheus 输出插件收集和报告 API 性能指标，然后可以在 Grafana 仪表板中可视化这些指标。此用例支持对 API 响应时间、吞吐量和错误率进行详细分析，从而促进 API 服务的持续改进。通过密切监控这些指标，团队可以快速响应性能下降，确保最佳的 API 性能并保持高水平的服务可用性。
反馈
感谢您成为我们社区的一份子！如果您有任何一般性反馈或在这些页面上发现任何错误，我们欢迎并鼓励您提出意见。请在 InfluxDB 社区 Slack 中提交您的反馈。
强大的性能，无限的扩展能力
收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时，它都更有价值。InfluxDB 是排名第一的时间序列平台，旨在通过 Telegraf 进行扩展。
查看入门方法
