AMQP and Cortex Integration

Input and output integration overview

<p>The AMQP Consumer Input Plugin allows you to ingest data from an AMQP 0-9-1 compliant message broker, such as RabbitMQ, enabling seamless data collection for monitoring and analytics purposes.</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

AMQP

<p>This plugin provides a consumer for use with AMQP 0-9-1, a prominent implementation of which is RabbitMQ. AMQP, or Advanced Message Queuing Protocol, was originally developed to enable reliable, interoperable messaging between diverse systems in a network. The plugin reads metrics from a topic exchange using a configured queue and binding key, delivering a flexible and efficient means of collecting data from AMQP-compliant messaging systems. This enables users to leverage existing RabbitMQ implementations to monitor their applications effectively by capturing detailed metrics for analysis and alerting.</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

AMQP

Cortex

Input and output integration examples

AMQP

<ol> <li> <p><strong>Integrating Application Metrics with AMQP</strong>: Use the AMQP Consumer plugin to gather application metrics that are published to a RabbitMQ exchange. By configuring the plugin to listen to specific queues, teams can gain insights into application performance, track request rates, error counts, and latency metrics, all in real-time. This setup not only aids in anomaly detection but also provides valuable data for capacity planning and system optimization.</p> </li> <li> <p><strong>Event-Driven Monitoring</strong>: Configure the AMQP Consumer to trigger specific monitoring events whenever certain conditions are met within an application. For instance, if a message indicating a high error rate is received, the plugin can feed this data into monitoring tools, generating alerts or scaling events. This integration can improve responsiveness to issues and automate parts of the operations workflow.</p> </li> <li> <p><strong>Cross-Platform Data Aggregation</strong>: Leverage the AMQP Consumer plugin to consolidate metrics from various applications distributed across different platforms. By utilizing RabbitMQ as a centralized message broker, organizations can unify their monitoring data, allowing for comprehensive analysis and dashboarding through Telegraf, thus maintaining visibility across heterogeneous environments.</p> </li> <li> <p><strong>Real-Time Log Processing</strong>: Extend the use of the AMQP Consumer to capture log data sent to a RabbitMQ exchange, processing logs in real time for monitoring and alerting purposes. This application ensures that operational issues are detected and addressed swiftly by analyzing log patterns, trends, and anomalies as they occur.</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>

Feedback

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