OPC UA and MongoDB Integration

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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.

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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.

The MongoDB Plugin allows you to send metrics to a MongoDB instance.

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.

MongoDB

This plugin sends metrics to MongoDB, automatically creating time series collections where they don’t already exist. Time series collections require MongoDB 5.0+.

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

MongoDB

[[outputs.mongodb]]
              # connection string examples for mongodb
              dsn = "mongodb://localhost:27017"
              # dsn = "mongodb://mongod1:27017,mongod2:27017,mongod3:27017/admin&replicaSet=myReplSet&w=1"

              # overrides serverSelectionTimeoutMS in dsn if set
              # timeout = "30s"

              # default authentication, optional
              # authentication = "NONE"

              # for SCRAM-SHA-256 authentication
              # authentication = "SCRAM"
              # username = "root"
              # password = "***"

              # for x509 certificate authentication
              # authentication = "X509"
              # tls_ca = "ca.pem"
              # tls_key = "client.pem"
              # # tls_key_pwd = "changeme" # required for encrypted tls_key
              # insecure_skip_verify = false

              # database to store measurements and time series collections
              # database = "telegraf"

              # granularity can be seconds, minutes, or hours.
              # configuring this value will be based on your input collection frequency.
              # see https://docs.mongodb.com/manual/core/timeseries-collections/#create-a-time-series-collection
              # granularity = "seconds"

              # optionally set a TTL to automatically expire documents from the measurement collections.
              # ttl = "360h"

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.

MongoDB

  1. Log Management: Integrate this plugin to send application logs directly to MongoDB for structured storage and flexible querying. You can analyze logs as time series data, aggregating logs by hour, day, or month.

  2. Metric Capture: Use the plugin to capture system metrics (CPU, memory usage) in real-time and store them in MongoDB. The time-series collections will allow for efficient queries over time ranges.

  3. Monitoring Solutions: Combine this output plugin with inputs from various sources, such as disk usage metrics, network statistics, or application performance data. It allows for consolidated monitoring dashboards with historical trends saved in MongoDB.

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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