OPC UA and Datadog Integration

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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 to the Datadog Metrics API and requires an apikey which can be obtained for the account. This plugin supports the v1 API.

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.

Datadog

Datadog metric names are formed by joining the Telegraf metric name and the field key with a . character.

Field values are converted to floating point numbers. Strings and floats that cannot be sent over JSON, namely NaN and Inf, are ignored.

Setting rate_interval to non-zero will convert count metrics to rate and divide its value by this interval before submitting to Datadog. This allows Telegraf to submit metrics alongside Datadog agents when their rate intervals are the same (Datadog defaults to 10s). Note that this only supports metrics ingested via inputs.statsd given the dependency on the metric_type tag it creates. There is only support for counter metrics, and count values from timing and histogram metrics.

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

Datadog

[[outputs.datadog]]
  ## Datadog API key
  apikey = "my-secret-key"

  ## Connection timeout.
  # timeout = "5s"

  ## Write URL override; useful for debugging.
  ## This plugin only supports the v1 API currently due to the authentication
  ## method used.
  # url = "https://app.datadoghq.com/api/v1/series"

  ## Set http_proxy
  # use_system_proxy = false
  # http_proxy_url = "http://localhost:8888"

  ## Override the default (none) compression used to send data.
  ## Supports: "zlib", "none"
  # compression = "none"

  ## When non-zero, converts count metrics submitted by inputs.statsd
  ## into rate, while dividing the metric value by this number.
  ## Note that in order for metrics to be submitted simultaenously alongside
  ## a Datadog agent, rate_interval has to match the interval used by the
  ## agent - which defaults to 10s
  # rate_interval = 0s

Input and output integration examples

OPC UA

  1. 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.

  2. 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=Temperature to gather temperature data directly.

  3. 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.

Datadog

  1. Basic Metric Submission: Utilize the Datadog Output Plugin to transmit metrics from your Telegraf instance to Datadog. By configuring the apikey and enabling necessary metrics, you can easily monitor application performance over time.
  2. Debugging Write URL: In cases where you need to troubleshoot your metric submissions, you can override the default write URL with a custom endpoint to debug the metrics being sent, ensuring that they are reaching the correct destination.
  3. Proxy Configuration: If your network setup requires routing through a proxy for outgoing requests, use the http_proxy_url option to set the appropriate proxy. This allows for seamless integration in restrictive network environments.

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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