OPC UA and Sensu Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider OPC UA and InfluxDB.
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Table of Contents
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
Input and output integration overview
The OPC UA plugin provides an interface for retrieving data from OPC UA server devices, facilitating effective data collection and monitoring.
This plugin writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.
Integration details
OPC UA
The OPC UA Plugin retrieves data from devices that communicate using the OPC UA protocol, allowing you to collect and monitor data from your OPC UA servers.
Sensu
This plugin writes metrics events to Sensu via its HTTP events API. Sensu is a monitoring system that enables users to collect, analyze, and manage metrics from various components in their infrastructure. The plugin facilitates the integration of Telegraf, a server agent for collecting and reporting metrics, with the Sensu monitoring platform. Users can configure settings such as backend and agent API URLs, API keys for authentication, and optional TLS settings. The plugin’s core functionality is centered around sending metric events, including check and entity specifications, to Sensu, allowing for comprehensive monitoring and alerting. The API reference provides extensive details about the events and metrics structure, ensuring users can efficiently leverage Sensu’s capabilities for observability and incident response.
Configuration
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
Sensu
[[outputs.sensu]]
## BACKEND API URL is the Sensu Backend API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the corresponding backend API path
## /api/core/v2/namespaces/:entity_namespace/events/:entity_name/:check_name).
##
## Backend Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## AGENT API URL is the Sensu Agent API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the correspeonding agent API path (/events).
##
## Agent API Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## NOTE: if backend_api_url and agent_api_url and api_key are set, the output
## plugin will use backend_api_url. If backend_api_url and agent_api_url are
## not provided, the output plugin will default to use an agent_api_url of
## http://127.0.0.1:3031
##
# backend_api_url = "http://127.0.0.1:8080"
# agent_api_url = "http://127.0.0.1:3031"
## API KEY is the Sensu Backend API token
## Generate a new API token via:
##
## $ sensuctl cluster-role create telegraf --verb create --resource events,entities
## $ sensuctl cluster-role-binding create telegraf --cluster-role telegraf --group telegraf
## $ sensuctl user create telegraf --group telegraf --password REDACTED
## $ sensuctl api-key grant telegraf
##
## For more information on Sensu RBAC profiles & API tokens, please visit:
## - https://docs.sensu.io/sensu-go/latest/reference/rbac/
## - https://docs.sensu.io/sensu-go/latest/reference/apikeys/
##
# api_key = "${SENSU_API_KEY}"
## Optional TLS Config
# 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
## Timeout for HTTP message
# timeout = "5s"
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "identity"
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of
## the table
## Sensu Event details
##
## Below are the event details to be sent to Sensu. The main portions of the
## event are the check, entity, and metrics specifications. For more information
## on Sensu events and its components, please visit:
## - Events - https://docs.sensu.io/sensu-go/latest/reference/events
## - Checks - https://docs.sensu.io/sensu-go/latest/reference/checks
## - Entities - https://docs.sensu.io/sensu-go/latest/reference/entities
## - Metrics - https://docs.sensu.io/sensu-go/latest/reference/events#metrics
##
## Check specification
## The check name is the name to give the Sensu check associated with the event
## created. This maps to check.metadata.name in the event.
[outputs.sensu.check]
name = "telegraf"
## Entity specification
## Configure the entity name and namespace, if necessary. This will be part of
## the entity.metadata in the event.
##
## NOTE: if the output plugin is configured to send events to a
## backend_api_url and entity_name is not set, the value returned by
## os.Hostname() will be used; if the output plugin is configured to send
## events to an agent_api_url, entity_name and entity_namespace are not used.
# [outputs.sensu.entity]
# name = "server-01"
# namespace = "default"
## Metrics specification
## Configure the tags for the metrics that are sent as part of the Sensu event
# [outputs.sensu.tags]
# source = "telegraf"
## Configure the handler(s) for processing the provided metrics
# [outputs.sensu.metrics]
# handlers = ["influxdb","elasticsearch"]
Input and output integration examples
OPC UA
-
Basic Configuration: Set up the plugin with your OPC UA server endpoint and desired metrics. This allows Telegraf to start gathering metrics from the configured nodes.
-
Node ID Setup: Use the configuration to specify specific nodes, such as temperature sensors, to monitor their values in real-time. For example, configure node
ns=3;s=Temperatureto gather temperature data directly. -
Group Configuration: Simplify monitoring multiple nodes by grouping them under a single configuration—this sets defaults for all nodes in that group, thereby reducing redundancy in setup.
Sensu
-
Real-Time Infrastructure Monitoring: Utilize the Sensu plugin to send performance metrics from various servers and services directly to Sensu. This real-time data flow enables teams to visualize infrastructure health, track resource usage, and receive immediate alerts for any anomalies detected. By centralizing monitoring through Sensu, organizations can create a holistic view of their systems and respond swiftly to issues.
-
Automated Incident Response Workflows: Leverage the plugin to automatically trigger incident response workflows based on the metrics events sent to Sensu. For example, if CPU usage exceeds a defined threshold, the Sensu system can be configured to alert the operations team, which can then initiate automated remediation processes, reducing downtime and maintaining system reliability. This integration allows for proactive management of system resources.
-
Dynamic Scaling of Resources: Use the Sensu plugin to feed metrics into an auto-scaling system that adjusts resources based on demand. By tracking metrics like request load and resource utilization, organizations can automatically scale their infrastructure up or down, ensuring optimal performance and cost efficiency without manual intervention.
-
Centralized Logging and Monitoring: Combine the Sensu with logging tools to send logs and performance metrics to a centralized monitoring system. This comprehensive approach allows teams to correlate logs with metric events, providing deeper insights into system behavior and performance, which aids in troubleshooting and performance optimization over time.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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