JTI OpenConfig Telemetry and Cortex Integration

Input and output integration overview

<p>The JTI OpenConfig Telemetry plugin allows users to collect real-time telemetry data from devices running Juniper’s implementation of the OpenConfig model, leveraging the Junos Telemetry Interface for efficient data retrieval.</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

JTI OpenConfig Telemetry

<p>This plugin reads data from Juniper Networks’ OpenConfig telemetry implementation using the Junos Telemetry Interface (JTI). OpenConfig is an initiative aimed at enabling standardized and open network device telemetry through a common model for various devices and protocols. The JTI allows for the collection of this telemetry data in a real-time manner from various sensors defined within the configuration. Configurable parameters for this plugin include the ability to specify device addresses, authentication credentials, sampling frequency, and multiple sensors with potentially different reporting rates. The plugin uniquely handles time-stamping either through the collection time or the timestamp provided in the data, allowing for flexibility in how data is processed. Given its support for TLS for secure communication, the plugin is well-suited for integration into both traditional and modern network management systems, enhancing visibility into network performance and reliability.</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

JTI OpenConfig Telemetry

Cortex

Input and output integration examples

JTI OpenConfig Telemetry

<ol> <li> <p><strong>Network Performance Monitoring</strong>: Use the JTI OpenConfig Telemetry plugin to monitor network performance metrics from multiple Juniper devices in real-time. By configuring various sensors, operators can gain insights into interface performance, traffic patterns, and error rates, allowing for proactive troubleshooting and optimization of the network.</p> </li> <li> <p><strong>Automated Fault Detection</strong>: Integrate the telemetry data collected via this plugin with a fault detection system that triggers alerts based on predefined thresholds. For example, when a specific sensor indicates a fault or threshold breach, automated scripts can be initiated to remediate the situation, dramatically improving response times.</p> </li> <li> <p><strong>Historical Performance Analysis</strong>: By forwarding the collected telemetry data into a time-series database, organizations can perform historical analysis on network performance. This enables teams to identify trends over time, spot anomalies, and make more informed decisions regarding network capacity planning and resource allocation.</p> </li> <li> <p><strong>Real-Time Dashboards for Network Operations</strong>: Leverage the real-time data gathered through this plugin to power visualization dashboards that provide network operators with live insights into performance metrics. This facilitates better operational awareness and quicker decision-making during critical events.</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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