IPVS and New Relic 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
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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.
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Input and output integration overview
The IPVS plugin is designed to collect metrics related to IPVS virtual and real servers on Linux systems.
This plugin allows the sending of metrics to New Relic Insights using the Metrics API, enabling effective monitoring and analysis of application performance.
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.
New Relic
This plugin writes metrics to New Relic Insights utilizing the Metrics API, which provides a robust mechanism for sending time series data to the New Relic platform. Users must first obtain an Insights API Key to authenticate and authorize their data submissions. The plugin is designed to facilitate easy integration with New Relic’s monitoring and analytics capabilities, supporting a variety of metric types and allowing for efficient data handling. Core features include the ability to add prefixes to metrics for better identification, customizable timeouts for API requests, and support for proxy settings to enhance connectivity. It is essential for users to configure these options according to their requirements, enabling seamless data flow into New Relic for comprehensive real-time analytics and insights.
Configuration
IPVS
[[inputs.ipvs]]
# no configuration
New Relic
[[outputs.newrelic]]
## The 'insights_key' parameter requires a NR license key.
## New Relic recommends you create one
## with a convenient name such as TELEGRAF_INSERT_KEY.
## reference: https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/#ingest-license-key
# insights_key = "New Relic License Key Here"
## Prefix to add to add to metric name for easy identification.
## This is very useful if your metric names are ambiguous.
# metric_prefix = ""
## Timeout for writes to the New Relic API.
# timeout = "15s"
## HTTP Proxy override. If unset use values from the standard
## proxy environment variables to determine proxy, if any.
# http_proxy = "http://corporate.proxy:3128"
## Metric URL override to enable geographic location endpoints.
# If not set use values from the standard
# metric_url = "https://metric-api.newrelic.com/metric/v1"
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.
New Relic
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Application Performance Monitoring: Use the New Relic Telegraf plugin to send application performance metrics from a web service to New Relic Insights. By integrating this plugin, developers can collect data such as response times, error rates, and throughput, enabling teams to monitor application health in real-time and resolve issues quickly before they impact users. This setup promotes proactive management of application performance and user experience.
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Infrastructure Metrics Aggregation: Leverage this plugin to aggregate and send system-level metrics (CPU usage, memory consumption, etc.) from various servers to New Relic. This helps system administrators maintain an comprehensive view of infrastructure performance, facilitating capacity planning and identifying potential bottlenecks. By centralizing metrics in New Relic, teams can visualize trends over time and make informed decisions regarding resource allocation.
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Dynamic Metric Naming for Multi-tenant Applications: Implement dynamic prefixing with the metric_prefix option to differentiate between different tenants in a multi-tenant application. By configuring the plugin to include a unique identifier per tenant in the metric names, teams can analyze usage patterns and performance metrics per tenant. This provides valuable insights into tenant behavior, supporting tailored optimizations and enhancing service quality across different customer segments.
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Real-time Anomaly Detection: Combine the New Relic plugin with alerting mechanisms to trigger notifications based on unusual metric patterns. By sending metrics such as request counts and response times, teams can set thresholds in New Relic that, when breached, will automatically alert responsible parties. This user-driven approach supports immediate responses to potential issues before they escalate into larger incidents.
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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