MavLink and Sensu Integration

Input and output integration overview

This plugin collects metrics from MavLink-compatible flight controllers like ArduPilot and PX4, enabling live data ingestion from unmanned systems such as drones and boats.

This plugin writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.

Integration details

MavLink

The MavLink plugin is designed to gather metrics from MavLink-compatible flight controllers such as ArduPilot and PX4. It provides a mechanism to live ingest flight metrics from various unmanned systems, including drones, planes, and boats. By utilizing the ArduPilot-specific MavLink dialect, the plugin parses a wide range of messages as documented in the MavLink documentation. It enables seamless integration of telemetry data, allowing for detailed monitoring and analysis of flight operations. Users must be cautious, as this plugin may generate a substantial volume of data; thus, filters are available to limit the metrics collected and transmitted to output plugins. Additionally, configuration options allow customization of which messages to receive and how to connect to the flight controller.

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

MavLink

[[inputs.mavlink]]
  ## Flight controller URL supporting serial port, UDP and TCP connections.
  ## Options are documented at
  ##   https://mavsdk.mavlink.io/v1.4/en/cpp/guide/connections.html.
  ##
  ## Examples:
  ## - Serial port: serial:///dev/ttyACM0:57600
  ## - TCP client:  tcp://192.168.1.12:5760
  ## - UDP client:  udp://192.168.1.12:14550
  ## - TCP server:  tcpserver://:5760
  ## - UDP server:  udpserver://:14550
  # url = "tcp://127.0.0.1:5760"

  ## Filter to specific messages. Only the messages in this list will be parsed.
  ## If blank or unset, all messages will be accepted. Glob syntax is accepted.
  ## Each message in this list should be lowercase camel_case, with "message_"
  ## prefix removed, eg: "global_position_int", "attitude"
  # filter = []

  ## Mavlink system ID for Telegraf. Only used if the mavlink plugin is sending 
  ## messages, eg. when `stream_request_frequency` is 0 (see below.)
  # system_id = 254

  ## Determines whether the plugin sends requests to subscribe to data.
  ## In mavlink, stream rates must be configured before data is received.
  ## This config item sets the rate in Hz, with 0 disabling the request.
  ## 
  ## This frequency should be set to 0 if your software already controls the 
  ## rates using REQUEST_DATA_STREAM or MAV_CMD_SET_MESSAGE_INTERVAL
  ## (See https://mavlink.io/en/mavgen_python/howto_requestmessages.html)
  # stream_request_frequency = 4

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

MavLink

1. Real-Time Fleet Monitoring: Utilize the MavLink plugin to create a centralized dashboard for monitoring multiple drones in real-time. By ingesting metrics from various flight controllers, operators can oversee the status, health, and location of all drones, allowing for quick decision-making and enhanced situational awareness. This integration could significantly improve coordination during large-scale operations, like aerial surveys or search and rescue missions.

2. Automated Anomaly Detection: Leverage MavLink in conjunction with machine learning algorithms to detect anomalies in flight data. By continuously monitoring metrics such as altitude, speed, and battery status, the system can alert operators to deviations from normal behavior, potentially indicating technical malfunctions or safety issues. This proactive approach can enhance safety and reduce the risk of in-flight failures.

3. Data-Driven Maintenance Scheduling: Integrate the data collected through the MavLink plugin with maintenance management systems to optimize maintenance schedules based on actual flight metrics. Analyzing the collected data can highlight patterns indicating when specific components are likely to fail, thereby enabling predictive maintenance strategies that minimize downtime and repair costs.

4. Enhanced Research Analytics: For academic and commercial UAV research, MavLink can be used to gather extensive flight data for analysis. By compiling metrics over numerous flights, researchers can uncover insights related to flight patterns, environmental interactions, and the efficiency of different drone models. This can foster advancements in UAV technology and broader applications in autonomous systems.

Sensu

1. 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.

2. 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.

3. 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.

4. 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.

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