Arista LANZ and Zabbix Integration

Input and output integration overview

The Arista LANZ plugin is designed for reading latency and congestion metrics from Arista LANZ, helping users monitor their network performance effectively.

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

Arista LANZ

This plugin provides a consumer for use with Arista Networks’ Latency Analyzer (LANZ). Metrics are read from a stream of data via TCP through port 50001 on the switches management IP. The data is in Protobuffers format, allowing for efficient transportation and parsing of data. LANZ is utilized to monitor network latency and congestion in real-time, which is vital for maintaining optimal performance in networking environments. The underlying technology, Arista’s latency analysis, provides insights into various network operations and infrastructure behaviors, making it a crucial tool for network engineering and management.

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

Arista LANZ

[[inputs.lanz]]
  ## URL to Arista LANZ endpoint
  servers = [
    "tcp://switch1.int.example.com:50001",
    "tcp://switch2.int.example.com:50001",
  ]

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

Arista LANZ

1. Real-Time Latency Monitoring: This plugin can be used to set up a monitoring dashboard that tracks real-time latency metrics across multiple interfaces. By gathering and visualizing this data, network admins can swiftly identify and rectify latency issues before they impact service quality. The challenge lies in efficiently handling the influx of metrics from various sources without overwhelming the infrastructure or incurring excessive processing delays.

2. Congestion Analysis for Traffic Engineering: Users can leverage the LANZ plugin to analyze congestion records, enabling the optimization of network traffic flows. By applying historical pattern recognition to the metrics collected, IT teams can make informed decisions on traffic management strategies, thus improving overall network efficiency. This requires implementing robust data storage and analysis capabilities to derive actionable insights from the raw metrics.

3. Integration with Alerting Systems: Integrate the metrics from this plugin with alerting systems to automatically notify network engineers of any significant changes in latency or congestion. By setting thresholds based on historical data trends, this use case enhances proactive incident management, allowing teams to address potential issues proactively. The technical challenge here is establishing the right balance in threshold settings to minimize false positives while ensuring genuine issues are flagged promptly.

4. Network Optimization Reports: Utilize the metrics gathered through the LANZ plugin to generate periodic reports that detail network performance, latency trends, and congestion events. These reports can help stakeholders understand network health over time and guide infrastructure investments. The challenge involves structuring and formatting the output data to make it comprehensible and actionable for various audiences.

Zabbix

1. 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.

2. 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.

3. 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.

4. 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.

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