Google Cloud Stackdriver and Cortex Integration

Input and output integration overview

<p>This plugin enables the collection of monitoring data from Google Cloud services through the Stackdriver Monitoring API. It is designed to help users monitor their cloud infrastructure’s performance and health by gathering relevant metrics.</p>

<p>This plugin enables Telegraf to send metrics to Cortex using the Prometheus remote write protocol, allowing seamless ingestion into Cortex’s scalable, multi-tenant time series storage.</p>

Integration details

Google Cloud Stackdriver

<p>The Stackdriver Telegraf plugin allows users to query timeseries data from Google Cloud Monitoring using the Cloud Monitoring API v3. With this plugin, users can easily integrate Google Cloud monitoring metrics into their monitoring stacks. This API provides a wealth of insights about resources and applications running in Google Cloud, including performance, uptime, and operational metrics. The plugin supports various configuration options to filter and refine the data retrieved, enabling users to customize their monitoring setup according to their specific needs. This integration facilitates a smoother experience in maintaining the health and performance of cloud resources and assists teams in making data-driven decisions based on historical and current performance statistics.</p>

Cortex

<p>With Telegraf’s HTTP output plugin and the <code>prometheusremotewrite</code> data format you can send metrics directly to Cortex, a horizontally scalable, long-term storage backend for Prometheus. Cortex supports multi-tenancy and accepts remote write requests using the Prometheus protobuf format. By using Telegraf as the collection agent and Remote Write as the transport mechanism, organizations can extend observability into sources not natively supported by Prometheus—such as Windows hosts, SNMP-enabled devices, or custom application metrics—while leveraging Cortex’s high-availability and long-retention capabilities.</p>

Configuration

Google Cloud Stackdriver

Cortex

Input and output integration examples

Google Cloud Stackdriver

<ol> <li> <p><strong>Integrating Cloud Metrics into Custom Dashboards</strong>: With this plugin, teams can funnel metrics from Google Cloud into personalized dashboards, allowing for real-time monitoring of application performance and resource utilization. By customizing the visual representation of cloud metrics, operations teams can easily identify trends and anomalies, enabling proactive management before issues escalate.</p> </li> <li> <p><strong>Automated Alerts and Analysis</strong>: Users can set up automated alerting mechanisms leveraging the plugin’s metrics to track resource thresholds. This capability allows teams to act swiftly in response to performance degradation or outages by providing immediate notifications, thus reducing the mean time to recovery and ensuring continued operational efficiency.</p> </li> <li> <p><strong>Cross-Platform Resource Comparison</strong>: The plugin can be used to draw metrics from various Google Cloud services and compare them with on-premise resources. This cross-platform visibility helps organizations make informed decisions about resource allocation and scaling strategies, as well as optimize cloud spending versus on-premise infrastructure.</p> </li> <li> <p><strong>Historical Data Analysis for Capacity Planning</strong>: By collecting historical metrics over time, the plugin empowers teams to conduct thorough capacity planning. Understanding past performance trends facilitates accurate forecasting for resource needs, leading to better budgeting and investment strategies.</p> </li> </ol>

Cortex

<ol> <li> <p><strong>Unified Multi-Tenant Monitoring</strong>: Use Telegraf to collect metrics from different teams or environments and push them to Cortex with separate <code>X-Scope-OrgID</code> headers. This enables isolated data ingestion and querying per tenant, ideal for managed services and platform teams.</p> </li> <li> <p><strong>Extending Prometheus Coverage to Edge Devices</strong>: Deploy Telegraf on edge or IoT devices to collect system metrics and send them to a centralized Cortex cluster. This approach ensures consistent observability even for environments without local Prometheus scrapers.</p> </li> <li> <p><strong>Global Service Observability with Federated Tenants</strong>: Aggregate metrics from global infrastructure by configuring Telegraf agents to push data into regional Cortex clusters, each tagged with tenant identifiers. Cortex handles deduplication and centralized access across regions.</p> </li> <li> <p><strong>Custom App Telemetry Pipeline</strong>: Collect app-specific telemetry via Telegraf’s <code>exec</code> or <code>http</code> input plugins and forward it to Cortex. This allows DevOps teams to monitor app-specific KPIs in a scalable, query-efficient format while keeping metrics logically grouped by tenant or service.</p> </li> </ol>

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