目录
输入和输出集成概述
Modbus 插件允许您使用各种通信方法从 Modbus 设备收集数据,从而增强您监控和控制工业流程的能力。
OpenSearch 输出插件允许用户使用 HTTP 将指标直接发送到 OpenSearch 实例,从而促进 OpenSearch 生态系统内有效的数据管理和分析。
集成详情
Modbus
Modbus 插件通过 Modbus TCP 或 Modbus RTU/ASCII 收集离散输入、线圈、输入寄存器和保持寄存器。
OpenSearch
OpenSearch Telegraf 插件通过 HTTP 与 OpenSearch 数据库集成,从而实现指标的简化收集和存储。作为一个专为 2.x 及更高版本的 OpenSearch 版本设计的强大工具,该插件在提供强大功能的同时,还通过原始 Elasticsearch 插件提供与 1.x 的兼容性。此插件有助于在 OpenSearch 中创建和管理索引,自动管理模板并确保数据结构化以进行高效分析。该插件支持各种配置选项,例如索引名称、身份验证、运行状况检查和值处理,使其可以根据不同的操作要求进行定制。其功能使其对于希望利用 OpenSearch 的强大功能进行指标存储和查询的组织至关重要。
配置
Modbus
[[inputs.modbus]]
name = "Device"
slave_id = 1
timeout = "1s"
configuration_type = "register"
discrete_inputs = [
{ name = "start", address = [0]},
{ name = "stop", address = [1]},
{ name = "reset", address = [2]},
{ name = "emergency_stop", address = [3]},
]
coils = [
{ name = "motor1_run", address = [0]},
{ name = "motor1_jog", address = [1]},
{ name = "motor1_stop", address = [2]},
]
holding_registers = [
{ name = "power_factor", byte_order = "AB", data_type = "FIXED", scale=0.01, address = [8]},
{ name = "voltage", byte_order = "AB", data_type = "FIXED", scale=0.1, address = [0]},
{ name = "energy", byte_order = "ABCD", data_type = "FIXED", scale=0.001, address = [5,6]},
{ name = "current", byte_order = "ABCD", data_type = "FIXED", scale=0.001, address = [1,2]},
{ name = "frequency", byte_order = "AB", data_type = "UFIXED", scale=0.1, address = [7]},
{ name = "power", byte_order = "ABCD", data_type = "UFIXED", scale=0.1, address = [3,4]},
{ name = "firmware", byte_order = "AB", data_type = "STRING", address = [5, 6, 7, 8, 9, 10, 11, 12]},
]
input_registers = [
{ name = "tank_level", byte_order = "AB", data_type = "INT16", scale=1.0, address = [0]},
{ name = "tank_ph", byte_order = "AB", data_type = "INT16", scale=1.0, address = [1]},
{ name = "pump1_speed", byte_order = "ABCD", data_type = "INT32", scale=1.0, address = [3,4]},
]
OpenSearch
[[outputs.opensearch]]
## URLs
## The full HTTP endpoint URL for your OpenSearch instance. Multiple URLs can
## be specified as part of the same cluster, but only one URLs is used to
## write during each interval.
urls = ["http://node1.os.example.com:9200"]
## Index Name
## Target index name for metrics (OpenSearch will create if it not exists).
## This is a Golang template (see https://pkg.go.dev/text/template)
## You can also specify
## metric name (`{{.Name}}`), tag value (`{{.Tag "tag_name"}}`), field value (`{{.Field "field_name"}}`)
## If the tag does not exist, the default tag value will be empty string "".
## the timestamp (`{{.Time.Format "xxxxxxxxx"}}`).
## For example: "telegraf-{{.Time.Format \"2006-01-02\"}}-{{.Tag \"host\"}}" would set it to telegraf-2023-07-27-HostName
index_name = ""
## Timeout
## OpenSearch client timeout
# timeout = "5s"
## Sniffer
## Set to true to ask OpenSearch a list of all cluster nodes,
## thus it is not necessary to list all nodes in the urls config option
# enable_sniffer = false
## GZIP Compression
## Set to true to enable gzip compression
# enable_gzip = false
## Health Check Interval
## Set the interval to check if the OpenSearch nodes are available
## Setting to "0s" will disable the health check (not recommended in production)
# health_check_interval = "10s"
## Set the timeout for periodic health checks.
# health_check_timeout = "1s"
## HTTP basic authentication details.
# username = ""
# password = ""
## HTTP bearer token authentication details
# auth_bearer_token = ""
## Optional TLS Config
## Set to true/false to enforce TLS being enabled/disabled. If not set,
## enable TLS only if any of the other options are specified.
# tls_enable =
## Trusted root certificates for server
# tls_ca = "/path/to/cafile"
## Used for TLS client certificate authentication
# tls_cert = "/path/to/certfile"
## Used for TLS client certificate authentication
# tls_key = "/path/to/keyfile"
## Send the specified TLS server name via SNI
# tls_server_name = "kubernetes.example.com"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Template Config
## Manage templates
## Set to true if you want telegraf to manage its index template.
## If enabled it will create a recommended index template for telegraf indexes
# manage_template = true
## Template Name
## The template name used for telegraf indexes
# template_name = "telegraf"
## Overwrite Templates
## Set to true if you want telegraf to overwrite an existing template
# overwrite_template = false
## Document ID
## If set to true a unique ID hash will be sent as
## sha256(concat(timestamp,measurement,series-hash)) string. It will enable
## data resend and update metric points avoiding duplicated metrics with
## different id's
# force_document_id = false
## Value Handling
## Specifies the handling of NaN and Inf values.
## This option can have the following values:
## none -- do not modify field-values (default); will produce an error
## if NaNs or infs are encountered
## drop -- drop fields containing NaNs or infs
## replace -- replace with the value in "float_replacement_value" (default: 0.0)
## NaNs and inf will be replaced with the given number, -inf with the negative of that number
# float_handling = "none"
# float_replacement_value = 0.0
## Pipeline Config
## To use a ingest pipeline, set this to the name of the pipeline you want to use.
# use_pipeline = "my_pipeline"
## Pipeline Name
## Additionally, you can specify a tag name using the notation (`{{.Tag "tag_name"}}`)
## which will be used as the pipeline name (e.g. "{{.Tag \"os_pipeline\"}}").
## If the tag does not exist, the default pipeline will be used as the pipeline.
## If no default pipeline is set, no pipeline is used for the metric.
# default_pipeline = ""
输入和输出集成示例
Modbus
- 基本用法:要从单个设备读取数据,请使用设备名称和 IP 地址配置它,并指定从站 ID 和感兴趣的寄存器。
- 多个请求:您可以通过指定多个
[[inputs.modbus.request]]
部分,在单个配置中定义多个请求以从不同的 Modbus 从站设备获取数据。 - 数据处理:利用缩放功能将原始 Modbus 读数转换为有用的指标,并根据需要调整单位换算。
OpenSearch
-
时间序列数据的动态索引:利用 OpenSearch Telegraf 插件为时间序列指标动态创建索引,确保数据以有组织的方式存储,从而有利于基于时间的查询。通过使用 Go 模板定义索引模式,用户可以利用该插件创建每日或每月索引,这可以大大简化数据管理和长期检索,从而提高分析性能。
-
多租户应用程序的集中日志记录:在多租户应用程序中实施 OpenSearch 插件,其中每个租户的日志都发送到单独的索引。这使得能够对每个租户进行有针对性的分析和监控,同时保持数据隔离。通过利用索引名称模板功能,用户可以自动创建租户特定的索引,这不仅简化了流程,而且增强了租户数据的安全性和可访问性。
-
与机器学习集成以进行异常检测:将 OpenSearch 插件与机器学习工具结合使用,以自动检测指标数据中的异常。通过配置插件以将实时指标发送到 OpenSearch,用户可以将机器学习模型应用于传入的数据流,以识别异常值或异常模式,从而促进主动监控和快速补救措施。
-
使用 OpenSearch 增强监控仪表板:使用从 OpenSearch 收集的指标创建实时仪表板,以深入了解系统性能。通过将指标馈送到 OpenSearch,组织可以利用 OpenSearch Dashboards 可视化关键绩效指标,使运营团队能够快速评估健康状况和性能,并做出数据驱动的决策。
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