IPMI Sensor and Nebius Cloud Monitoring Integration

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 allows users to effortlessly send aggregated metrics to Nebius Cloud Monitoring, leveraging the cloud’s monitoring solutions.

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.

Nebius Cloud Monitoring

The Nebius Cloud Monitoring plugin serves as an intermediary to send custom metrics to the Nebius Cloud Monitoring service. It is designed specifically to facilitate the monitoring of applications and services running within the Nebius ecosystem. This plugin is especially useful for users of the Nebius Cloud Platform who need to leverage cloud-based monitoring capabilities without significant configuration overhead. The plugin’s integration relies on Google Cloud metadata, allowing it to automatically fetch the necessary authentication credentials from the Compute instance it operates within. Key technical considerations include the management of reserved labels to ensure metrics are recorded correctly without conflicts.

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 = ""

Nebius Cloud Monitoring

[[outputs.nebius_cloud_monitoring]]
  ## Timeout for HTTP writes.
  # timeout = "20s"

  ## Nebius.Cloud monitoring API endpoint. Normally should not be changed
  # endpoint = "https://monitoring.api.il.nebius.cloud/monitoring/v2/data/write"

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.

Nebius Cloud Monitoring

1. Dynamic Application Monitoring: Integrate this plugin with your application to continuously send metrics related to resource usage, such as CPU and memory utilization, to Nebius Cloud Monitoring. By doing so, you can gain insights into the performance of your application, allowing for adjustments in real-time based on the metrics received.

2. Incident Response Automation: Use the Nebius Cloud Monitoring plugin to automatically send alerts and metrics when certain thresholds are reached. For instance, if a particular service’s uptime drops below a certain percentage, the plugin can be configured to report this directly to the monitoring service, enabling quicker incident response and resolution.

3. Comparative Service Analysis: Set up the plugin to send metrics from multiple cloud instances running different versions of the same application to Nebius Cloud Monitoring. This approach allows for a comparative analysis of resource usage and performance, helping teams determine which version performs best under similar workloads.

4. Aggregated Metrics Dashboard: Use this plugin to create a centralized dashboard displaying metrics from various services across your cloud instances. By aggregating different application metrics into one interface, stakeholders can assess the overall health and performance of their cloud environment easily.

Feedback

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