Apache and Librato Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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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
This plugin interfaces with the Apache HTTP Server’s mod_status to gather and report performance metrics from the server.
The Librato plugin for Telegraf is designed to facilitate seamless integration with the Librato Metrics API, allowing for efficient metric reporting and monitoring.
Integration details
Apache
The Apache plugin collects server performance information using the mod_status module of the Apache HTTP Server. It relies on the mod_status feature, which must be explicitly enabled in the Apache configuration to access a machine-readable status page. This plugin allows users to fetch several metrics related to Apache’s operational performance, including worker status, connection statistics, and server load, thereby facilitating effective monitoring and troubleshooting of web server performance in real-time.
Librato
The Librato plugin enables Telegraf to send metrics to the Librato Metrics API. To authenticate, users must provide an api_user
and api_token
, which can be acquired from the Librato account settings. This integration allows for efficient monitoring and reporting of custom metrics within the Librato platform. The plugin also utilizes a source_tag
option that can enrich the metrics with contextual information from Point Tags; however, it does not currently support sending associated Point Tags. It is essential to note that any point value sent that cannot be converted to a float64 type will be skipped, ensuring that only valid metrics are processed and sent to Librato. The plugin also supports secret-store options for managing sensitive authentication credentials securely, facilitating best practices in credential management.
Configuration
Apache
[[inputs.apache]]
## An array of URLs to gather from, must be directed at the machine
## readable version of the mod_status page including the auto query string.
## Default is "http://localhost/server-status?auto".
urls = ["http://localhost/server-status?auto"]
## Credentials for basic HTTP authentication.
# username = "myuser"
# password = "mypassword"
## Maximum time to receive response.
# response_timeout = "5s"
## 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
Librato
[[outputs.librato]]
## Librato API Docs
## http://dev.librato.com/v1/metrics-authentication
## Librato API user
api_user = "[email protected]" # required.
## Librato API token
api_token = "my-secret-token" # required.
## Debug
# debug = false
## Connection timeout.
# timeout = "5s"
## Output source Template (same as graphite buckets)
## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md#graphite
## This template is used in librato's source (not metric's name)
template = "host"
Input and output integration examples
Apache
-
Real-Time Performance Monitoring: Use the Apache input plugin to set up a real-time dashboard displaying critical performance metrics of your Apache server. By visualizing metrics such as BusyWorkers, and Load averages, you can quickly identify performance bottlenecks and server health issues, aiding in proactive management of web traffic loads.
-
Automated Alerting for Server Issues: Implement alerts based on metrics collected by this plugin to notify administrators in case of performance degradation. For instance, if the
BusyWorkers
metric exceeds a certain threshold, automatic alerts can be triggered, ensuring prompt incident response to maintain uptime and service reliability. -
Historical Performance Analysis: Combine data collected by the Apache plugin with long-term storage solutions to track performance trends over time. This accumulated data helps in understanding usage patterns, forecasting resource needs, and making informed decisions regarding server scaling or optimization.
-
Cross-System Monitoring: Integrate metrics gathered from Apache alongside metrics from other components of your web stack using Telegraf’s capabilities to send data to a centralized monitoring solution. This holistic view can simplify troubleshooting and coordination between different technologies, ensuring optimal system performance across the board.
Librato
-
Real-time Application Monitoring: Utilize Librato to collect performance metrics from a web application in real-time. This setup involves sending response times, error rates, and user interactions to Librato, allowing developers to monitor the application’s health and performance metrics closely. By analyzing these metrics, teams can quickly identify and address performance bottlenecks or application failures before they impact end users.
-
Infrastructure Metrics Aggregation: Leverage this plugin to gather and send metrics from various infrastructure components, such as servers or containers, to Librato for centralized monitoring. Configuring the plugin to send CPU, memory usage, and disk I/O metrics enables system administrators to have a comprehensive view of infrastructure performance, assisting in capacity planning and resource optimization strategies.
-
Custom Metrics for Business Operations: Feed business-specific metrics, such as sales transactions or user sign-ups, to the Librato service using this plugin. By tracking these custom metrics, businesses can gain insights into their operational performance and make data-driven decisions to enhance their strategies, marketing efforts, or product development initiatives.
-
Anomaly Detection in Metrics: Implement monitoring tools that utilize machine learning for anomaly detection. By continuously sending real-time metrics to Librato, teams can analyze trends and automatically flag unusual behavior, such as sudden spikes in latency or unusual traffic patterns, enabling timely intervention and troubleshooting.
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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