JTI OpenConfig Telemetry and Clickhouse 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>Telegraf’s SQL plugin sends collected metrics to an SQL database using a straightforward table schema and dynamic column generation. When configured for ClickHouse, it adjusts DSN formatting and type conversion settings to ensure seamless data integration.</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>

Clickhouse

<p>Telegraf’s SQL plugin is engineered to write metric data into an SQL database by dynamically creating tables and columns based on incoming metrics. When configured for ClickHouse, it utilizes the clickhouse-go v1.5.4 driver, which employs a unique DSN format and a set of specialized type conversion rules to map Telegraf’s data types directly to ClickHouse’s native types. This approach ensures optimal storage and retrieval performance in high-throughput environments, making it well-suited for real-time analytics and large-scale data warehousing. The dynamic schema creation and precise type mapping enable detailed time-series data logging, crucial for monitoring modern, distributed systems.</p>

Configuration

JTI OpenConfig Telemetry

Clickhouse

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>

Clickhouse

<ol> <li> <p><strong>Real-Time Analytics for High-Volume Data</strong>: Use the plugin to feed streaming metrics from large-scale systems into ClickHouse. This setup supports ultra-fast query performance and near real-time analytics, ideal for monitoring high-traffic applications.</p> </li> <li> <p><strong>Time-Series Data Warehousing</strong>: Integrate the plugin with ClickHouse to create a robust time-series data warehouse. This use case allows organizations to store detailed historical metrics and perform complex queries for trend analysis and capacity planning.</p> </li> <li> <p><strong>Scalable Monitoring in Distributed Environments</strong>: Leverage the plugin to dynamically create tables per metric type in ClickHouse, making it easier to manage and query data from a multitude of distributed systems without prior schema definitions.</p> </li> <li> <p><strong>Optimized Storage for IoT Deployments</strong>: Deploy the plugin to ingest data from IoT sensors into ClickHouse. Its efficient schema creation and native type mapping facilitate the handling of massive volumes of data, enabling real-time monitoring and predictive maintenance.</p> </li> </ol>

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.