MavLink and Zabbix 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
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 sends metrics to Zabbix via traps, allowing for efficient monitoring of systems and applications. It supports automated configuration and data sending based on dynamic metrics collected by Telegraf.
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.
Zabbix
The Telegraf Zabbix plugin is designed to send metrics to Zabbix, an open-source monitoring solution, using the trap protocol. It supports various versions from 3.0 to 6.0, ensuring compatibility with recent updates. The plugin facilitates easy integration with the Zabbix ecosystem, allowing users to send collected metrics and monitor system performance seamlessly. Key functionalities include the ability to define the address and port of the Zabbix server, options for prefixing keys, determining the type of data sent (active vs. trapper), and features for low-level discovery (LLD) enabling dynamic item creation based on the metrics observed. Configuration options also allow for autoregistration and resending intervals for LLD data, ensuring that the metrics are up-to-date and relevant. Additionally, the trap format used for sending metrics is structured to facilitate efficient data transfer and processing in Zabbix.
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
Zabbix
[[outputs.zabbix]]
## Address and (optional) port of the Zabbix server
address = "zabbix.example.com:10051"
## Send metrics as type "Zabbix agent (active)"
# agent_active = false
## Add prefix to all keys sent to Zabbix.
# key_prefix = "telegraf."
## Name of the tag that contains the host name. Used to set the host in Zabbix.
## If the tag is not found, use the hostname of the system running Telegraf.
# host_tag = "host"
## Skip measurement prefix to all keys sent to Zabbix.
# skip_measurement_prefix = false
## This field will be sent as HostMetadata to Zabbix Server to autoregister the host.
## To enable this feature, this option must be set to a value other than "".
# autoregister = ""
## Interval to resend auto-registration data to Zabbix.
## Only applies if autoregister feature is enabled.
## This value is a lower limit, the actual resend should be triggered by the next flush interval.
# autoregister_resend_interval = "30m"
## Interval to send LLD data to Zabbix.
## This value is a lower limit, the actual resend should be triggered by the next flush interval.
# lld_send_interval = "10m"
## Interval to delete stored LLD known data and start capturing it again.
## This value is a lower limit, the actual resend should be triggered by the next flush interval.
# lld_clear_interval = "1h"
Input and output integration examples
MavLink
-
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.
-
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.
-
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.
-
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.
Zabbix
-
Dynamic Monitoring of Containerized Applications: Integration of the Zabbix plugin can be leveraged to monitor Docker containers dynamically. As containers are created and removed, the plugin can automatically update Zabbix with the appropriate metrics, ensuring that monitoring stays current without manual configuration. This enhances visibility into resource usage and performance metrics for microservices orchestrated with Kubernetes or Docker Swarm.
-
Real-Time Performance Monitoring with Auto-registration: By enabling the autoregister feature, the plugin can automatically register hosts in Zabbix based on the metrics received. This scenario provides a streamlined approach to add new hosts to monitoring without manual setup, which is particularly useful in environments where hosts may frequently spin up and down, such as serverless architectures or cloud-based deployments.
-
Leveraging Low-level Discovery for Flexible Metric Capture: Using low-level discovery, this plugin allows Zabbix to adaptively create items for metrics that are not predefined. In a scenario involving multiple network devices reporting different performance metrics, the plugin can dynamically inform Zabbix about new metrics as they appear, thus ensuring comprehensive monitoring capabilities that evolve with the monitored systems.
-
Centralized Monitoring of Distributed Systems: The Zabbix plugin can be utilized in a centralized monitoring setup for distributed systems where multiple Telegraf instances are running across different geographical locations. By sending all metrics to a central Zabbix server, organizations can achieve a holistic view of their infrastructure’s performance and make informed operational decisions.
Feedback
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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.
See Ways to Get Started
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