IPMI Sensor and Graphite 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.
See Ways to Get Started
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.
The Graphite plugin enables users to send metrics collected by Telegraf into Graphite via TCP. This integration allows for efficient storage and visualization of time-series data using Graphite’s powerful capabilities.
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.
Graphite
This plugin writes metrics to Graphite via raw TCP, allowing for seamless integration of Telegraf collected metrics into the Graphite ecosystem. With this plugin, users can configure multiple TCP endpoints for load balancing, ensuring high availability and reliability in metric transmission. The ability to customize metric naming with prefixes and utilize various templating options enhances flexibility in how data is represented within Graphite. Additionally, support for Graphite tags and options for strict sanitization of metric names allow for robust data management, catering to the varying needs of users. This capability is essential for organizations looking to leverage Graphite’s powerful metrics storage and visualization while maintaining control over data representation.
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 = ""
Graphite
# Configuration for Graphite server to send metrics to
[[outputs.graphite]]
## TCP endpoint for your graphite instance.
## If multiple endpoints are configured, the output will be load balanced.
## Only one of the endpoints will be written to with each iteration.
servers = ["localhost:2003"]
## Local address to bind when connecting to the server
## If empty or not set, the local address is automatically chosen.
# local_address = ""
## Prefix metrics name
prefix = ""
## Graphite output template
## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
template = "host.tags.measurement.field"
## Strict sanitization regex
## This is the default sanitization regex that is used on data passed to the
## graphite serializer. Users can add additional characters here if required.
## Be aware that the characters, '/' '@' '*' are always replaced with '_',
## '..' is replaced with '.', and '\' is removed even if added to the
## following regex.
# graphite_strict_sanitize_regex = '[^a-zA-Z0-9-:._=\p{L}]'
## Enable Graphite tags support
# graphite_tag_support = false
## Applied sanitization mode when graphite tag support is enabled.
## * strict - uses the regex specified above
## * compatible - allows for greater number of characters
# graphite_tag_sanitize_mode = "strict"
## Character for separating metric name and field for Graphite tags
# graphite_separator = "."
## Graphite templates patterns
## 1. Template for cpu
## 2. Template for disk*
## 3. Default template
# templates = [
# "cpu tags.measurement.host.field",
# "disk* measurement.field",
# "host.measurement.tags.field"
#]
## timeout in seconds for the write connection to graphite
# timeout = "2s"
## 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
Input and output integration examples
IPMI Sensor
-
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.
-
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.
-
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.
-
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.
Graphite
-
Dynamic Metric Visualization: The Graphite plugin can be utilized to feed real-time metrics from various sources, such as application performance data or server health metrics, into Graphite. This dynamic integration allows teams to create interactive dashboards that visualize key performance indicators, track trends over time, and make data-driven decisions to enhance system performance.
-
Load Balanced Metrics Collection: By configuring multiple TCP endpoints within the plugin, organizations can implement load balancing for metric transmission. This use case ensures that metric delivery is both resilient and efficient, reducing the risk of data loss during high-traffic periods and maintaining a reliable flow of information to Graphite.
-
Customized Metrics Tagging: With support for Graphite tags, users can employ the Graphite plugin to enhance the granularity of their metrics. Tagging metrics with relevant information, such as application environment or service type, allows for more refined queries and analytics, enabling teams to drill down into specific areas of interest for better operational insights.
-
Enhanced Data Sanitization: Leveraging the plugin’s strict sanitization options, users can ensure that their metric names comply with Graphite’s requirements. This proactive measure eliminates potential issues arising from invalid characters in metric names, allowing for cleaner data management and more accurate visualizations.
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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