IPVS and OpenTSDB Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Time series database
Source: DB Engines
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Table of Contents
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 IPVS plugin is designed to collect metrics related to IPVS virtual and real servers on Linux systems.
The OpenTSDB plugin facilitates the integration of Telegraf with OpenTSDB, allowing users to push time-series metrics to an OpenTSDB backend seamlessly.
Integration details
IPVS
The IPVS plugin gathers metrics about IPVS virtual and real servers using the Linux kernel netlink socket interface. As a component specifically designed for Linux, it tracks performance related to IP virtual servers, allowing users to monitor various attributes such as active connections, packet statistics, and byte counts. Key metrics include those for both virtual and real servers, facilitating a comprehensive view of server performance. The plugin also requires the Telegraf process to run with appropriate permissions, typically as root or a user with specific capabilities for proper operation.
OpenTSDB
The OpenTSDB plugin is designed to send metrics to an OpenTSDB instance using either the telnet or HTTP mode. With the introduction of OpenTSDB 2.0, the recommended method for sending metrics is via the HTTP API, which allows for batch processing of metrics by configuring the ‘http_batch_size’. The plugin supports several configuration options including metrics prefixing, server host and port specification, URI path customization for reverse proxies, and debug options for diagnosing communication issues with OpenTSDB. This plugin is particularly useful in scenarios where time series data is generated and needs to be efficiently stored in a scalable time series database like OpenTSDB, making it suitable for a wide range of monitoring and analytics applications.
Configuration
IPVS
[[inputs.ipvs]]
# no configuration
OpenTSDB
[[outputs.opentsdb]]
## prefix for metrics keys
prefix = "my.specific.prefix."
## DNS name of the OpenTSDB server
## Using "opentsdb.example.com" or "tcp://opentsdb.example.com" will use the
## telnet API. "http://opentsdb.example.com" will use the Http API.
host = "opentsdb.example.com"
## Port of the OpenTSDB server
port = 4242
## Number of data points to send to OpenTSDB in Http requests.
## Not used with telnet API.
http_batch_size = 50
## URI Path for Http requests to OpenTSDB.
## Used in cases where OpenTSDB is located behind a reverse proxy.
http_path = "/api/put"
## Debug true - Prints OpenTSDB communication
debug = false
## Separator separates measurement name from field
separator = "_"
Input and output integration examples
IPVS
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Load Balancing Performance Monitoring: Use the IPVS plugin to monitor the performance of a load balancing setup in a Linux environment where IPVS is implemented. By collecting metrics such as byte counts, packet rates, and active connections, administrators can gain real-time insights into server performance, allowing for proactive adjustments to load distribution strategies and ensuring that no individual server becomes a bottleneck.
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Automated Alerting for Connection Thresholds: Integrate the metrics collected by the IPVS plugin with an alerting system to automatically notify administrators when active connections exceed or fall below specified thresholds. This use case enables dynamic scaling of backend resources, optimizing application performance and resource utilization, while minimizing the risk of sudden service disruptions.
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Historical Performance Trend Analysis: Store the metrics gathered by the IPVS plugin in a time-series database for historical analysis. By analyzing trends over time, organizations can identify patterns in server performance, correlate them with application usage spikes, and make informed decisions regarding infrastructure upgrades or maintenance schedules to better handle peak loads.
OpenTSDB
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Real-time Infrastructure Monitoring: Utilize the OpenTSDB plugin to collect and store metrics from various infrastructure components. By configuring the plugin to push metrics to OpenTSDB, organizations can have a centralized view of their infrastructure health and performance over time.
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Custom Application Metrics Tracking: Integrate the OpenTSDB plugin into custom applications to track key performance indicators (KPIs) such as response times, error rates, and user interactions. This setup allows developers and product teams to visualize application performance trends and make data-driven decisions.
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Automated Anomaly Detection: Leverage the plugin in conjunction with machine learning algorithms to automatically detect anomalies in time-series data sent to OpenTSDB. By continuously monitoring the incoming metrics, the system can train models that alert users to potential issues before they affect application performance.
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Historical Data Analysis: Use the OpenTSDB plugin to store and analyze historical performance data for capacity planning and trend analysis. This provides valuable insights into system behavior over time, helping teams to understand usage patterns and prepare for future growth.
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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