Fluentd and Google Cloud Monitoring Integration

Input and output integration overview

<p>The Fluentd Input Plugin gathers metrics from Fluentd’s in_monitor plugin endpoint. It provides insights into various plugin metrics while allowing for custom configurations to reduce series cardinality.</p>

<p>The Stackdriver plugin allows users to send metrics directly to a specified project in Google Cloud Monitoring, facilitating robust monitoring capabilities across their cloud resources.</p>

Integration details

Fluentd

<p>This plugin gathers metrics from the Fluentd plugin endpoint provided by the in_monitor plugin. It reads data from the /api/plugin.json resource and allows exclusion of specific plugins based on their type.</p>

Google Cloud Monitoring

<p>This plugin writes metrics to a project in Google Cloud Monitoring, which used to be known as Stackdriver. Authentication is a prerequisite and can be achieved via service accounts or user credentials. The plugin is designed to group metrics by a <code>namespace</code> variable and metric key, facilitating organized data management. However, users are encouraged to use the <code>official</code> naming format for enhanced query efficiency. The plugin supports additional configurations for managing metric representation and allows tags to be treated as resource labels. Notably, it imposes certain restrictions on the data it can accept, such as not allowing string values or points that are out of chronological order.</p>

Configuration

Fluentd

Google Cloud Monitoring

Input and output integration examples

Fluentd

<ol> <li><strong>Basic Configuration</strong>: Set up the Fluentd Input Plugin to gather metrics from your Fluentd instance’s monitoring endpoint, ensuring you are able to track performance and usage statistics.</li> <li><strong>Excluding Plugins</strong>: Use the <code>exclude</code> option to ignore specific plugins’ metrics that are not necessary for your monitoring needs, streamlining data collection and focusing on what matters.</li> <li><strong>Custom Plugin ID</strong>: Implement the <code>@id</code> parameter in your Fluentd configuration to maintain a consistent <code>plugin_id</code>, which helps avoid issues with high series cardinality during frequent restarts.</li> </ol>

Google Cloud Monitoring

<ol> <li> <p><strong>Multi-Project Metric Aggregation</strong>: Use this plugin to send aggregated metrics from various applications across different projects into a single Google Cloud Monitoring project. This use case helps centralize metrics for teams managing multiple applications, providing a unified view for performance monitoring and enhancing decision-making. By configuring different quota projects for billing, organizations can ensure proper cost management while benefiting from a consolidated monitoring strategy.</p> </li> <li> <p><strong>Anomaly Detection Setup</strong>: Integrate the plugin with a machine learning-based analytics tool that identifies anomalies in the collected metrics. Using the historical data provided by the plugin, the tool can learn normal baseline behavior and promptly alert the operations team when unusual patterns arise, enabling proactive troubleshooting and minimizing service disruptions.</p> </li> <li> <p><strong>Dynamic Resource Labeling</strong>: Implement dynamic tagging by utilizing the tags_as_resource_label option to adaptively attach resource labels based on runtime conditions. This setup allows metrics to provide context-sensitive information, such as varying environmental parameters or operational states, enhancing the granularity of monitoring and reporting without changing the fundamental metric structure.</p> </li> <li> <p><strong>Custom Metric Visualization Dashboards</strong>: Leverage the data collected by the Google Cloud Monitoring output plugin to feed a custom metrics visualization dashboard using a third-party framework. By visualizing metrics in real-time, teams can achieve better situational awareness, notably by correlating different metrics, improving operational decision-making, and streamlining performance management workflows.</p> </li> </ol>

Feedback

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