IPMI Sensor and Thanos Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider IPMI and InfluxDB.

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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 IPMI Sensor Plugin facilitates the collection of server health metrics directly from hardware via the IPMI protocol, querying sensor data from either local or remote systems.

This plugin sends metrics from Telegraf to Thanos using the Prometheus remote write protocol over HTTP, allowing efficient and scalable ingestion into Thanos Receive components.

Integration details

IPMI Sensor

The IPMI Sensor plugin is designed to gather bare metal metrics via the command line utility ipmitool, which interfaces with the Intelligent Platform Management Interface (IPMI). This protocol provides management and monitoring capabilities for hardware components in server systems, allowing for the retrieval of critical system health metrics such as temperature, fan speeds, and power supply status from both local and remote servers. When configured without specified servers, the plugin defaults to querying the local machine’s sensor statistics using the ipmitool sdr command. In scenarios covering remote hosts, authentication is supported through username and password using the command format ipmitool -I lan -H SERVER -U USERID -P PASSW0RD sdr. This flexibility allows users to monitor systems effectively across various environments. The plugin also supports multiple sensor types, including chassis power status and DCMI power readings, catering to administrators needing real-time insight into server operations.

Thanos

Telegraf’s HTTP plugin can send metrics directly to Thanos via its Remote Write-compatible Receive component. By setting the data format to prometheusremotewrite, Telegraf can serialize metrics into the same protobuf-based format used by native Prometheus clients. This setup enables high-throughput, low-latency metric ingestion into Thanos, facilitating centralized observability at scale. It is particularly useful in hybrid environments where Telegraf is collecting metrics from systems outside Prometheus’ native reach, such as SNMP devices, Windows hosts, or custom apps, and streams them directly to Thanos for long-term storage and global querying.

Configuration

IPMI Sensor

[[inputs.ipmi_sensor]]
  ## Specify the path to the ipmitool executable
  # path = "/usr/bin/ipmitool"

  ## Use sudo
  ## Setting 'use_sudo' to true will make use of sudo to run ipmitool.
  ## Sudo must be configured to allow the telegraf user to run ipmitool
  ## without a password.
  # use_sudo = false

  ## Servers
  ## Specify one or more servers via a url. If no servers are specified, local
  ## machine sensor stats will be queried. Uses the format:
  ##  [username[:password]@][protocol[(address)]]
  ##  e.g. root:passwd@lan(127.0.0.1)
  # servers = ["USERID:PASSW0RD@lan(192.168.1.1)"]

  ## Session privilege level
  ## Choose from: CALLBACK, USER, OPERATOR, ADMINISTRATOR
  # privilege = "ADMINISTRATOR"

  ## Timeout
  ## Timeout for the ipmitool command to complete.
  # timeout = "20s"

  ## Metric schema version
  ## See the plugin readme for more information on schema versioning.
  # metric_version = 1

  ## Sensors to collect
  ## Choose from:
  ##   * sdr: default, collects sensor data records
  ##   * chassis_power_status: collects the power status of the chassis
  ##   * dcmi_power_reading: collects the power readings from the Data Center Management Interface
  # sensors = ["sdr"]

  ## Hex key
  ## Optionally provide the hex key for the IMPI connection.
  # hex_key = ""

  ## Cache
  ## If ipmitool should use a cache
  ## Using a cache can speed up collection times depending on your device.
  # use_cache = false

  ## Path to the ipmitools cache file (defaults to OS temp dir)
  ## The provided path must exist and must be writable
  # cache_path = ""

Thanos

[[outputs.http]]
  ## Thanos Receive endpoint for remote write
  url = "http://thanos-receive.example.com/api/v1/receive"

  ## HTTP method
  method = "POST"

  ## Data format set to Prometheus remote write
  data_format = "prometheusremotewrite"

  ## Optional headers (authorization, etc.)
  # [outputs.http.headers]
  #   Authorization = "Bearer YOUR_TOKEN"

  ## Optional TLS configuration
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"
  # insecure_skip_verify = false

  ## Request timeout
  timeout = "10s"

Input and output integration examples

IPMI Sensor

  1. Centralized Monitoring Dashboard: Utilize the IPMI Sensor plugin to gather metrics from multiple servers and compile them into a centralized monitoring dashboard. This enables real-time visibility into server health across data centers. Administrators can track metrics like temperature and power usage, helping them make data-driven decisions about resource allocation, potential failures, and maintenance schedules.

  2. Automated Power Alerts: Incorporate the plugin into an alerting system that monitors chassis power status and triggers alerts when anomalies are detected. For instance, if the power status indicates a failure or if watt values exceed expected thresholds, automated notifications can be sent to operations teams, ensuring prompt attention to hardware issues.

  3. Energy Consumption Analysis: Leverage the DCMI power readings collected via the plugin to analyze energy consumption patterns of hardware over time. By integrating these readings with analytics platforms, organizations can identify opportunities to reduce power usage, optimize efficiency, and potentially decrease operational costs in large server farms or cloud infrastructures.

  4. Health Check Automation: Schedule regular health checks by using the IPMI Sensor Plugin to collect data from a fleet of servers. This data can be logged and compared against historical performance metrics to identify trends, outliers, or signs of impending hardware failure, allowing IT teams to take proactive measures and reduce downtime.

Thanos

  1. Agentless Cloud Monitoring: Deploy Telegraf agents across cloud VMs to collect system and application metrics, then stream them directly into Thanos using Remote Write. This provides centralized observability without requiring Prometheus nodes at each location.

  2. Scalable Windows Host Monitoring: Use Telegraf on Windows machines to collect OS-level metrics and send them via Remote Write to Thanos Receive. This enables observability across heterogeneous environments with native Prometheus support only on Linux.

  3. Cross-Region Metrics Federation: Telegraf agents in multiple geographic regions can push data to region-local Thanos Receivers using this plugin. From there, Thanos can deduplicate and query metrics globally, reducing latency and network egress costs.

  4. Integrating Third-Party Data into Thanos: Collect metrics from custom telemetry sources such as REST APIs or proprietary logs using Telegraf inputs and forward them to Thanos via Remote Write. This brings non-native data into a Prometheus-compatible, long-term analytics pipeline.

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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