NATS and AWS Redshift Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
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Input and output integration overview
<p>The NATS Consumer Input Plugin enables real-time data consumption from NATS messaging subjects, integrating seamlessly into the Telegraf data pipeline for monitoring and metrics gathering.</p>
<p>This plugin enables Telegraf to send metrics to Amazon Redshift using the PostgreSQL plugin, allowing metrics to be stored in a scalable, SQL-compatible data warehouse.</p>
Integration details
NATS
<p>The NATS Consumer Plugin allows Telegraf to read metrics from specified NATS subjects and create metrics based on supported input data formats. Utilizing a Queue Group allows multiple instances of Telegraf to read from a NATS cluster in parallel, enhancing throughput and reliability. This plugin also supports various authentication methods, including username/password, NATS credentials files, and nkey seed files, ensuring secure communication with the NATS servers. It is particularly useful in environments where data persistence and message reliability are critical, thanks to features such as JetStream that facilitate the consumption of historical messages. Additionally, the ability to configure various operational parameters makes this plugin suitable for high-throughput scenarios while maintaining performance integrity.</p>
AWS Redshift
<p>This configuration uses the Telegraf PostgreSQL plugin to send metrics to Amazon Redshift, AWS’s fully managed cloud data warehouse that supports SQL-based analytics at scale. Although Redshift is based on PostgreSQL 8.0.2, it does not support all standard PostgreSQL features such as full JSONB, stored procedures, or upserts. Therefore, care must be taken to predefine compatible tables and schema when using Telegraf for Redshift integration. This setup is ideal for use cases that benefit from long-term, high-volume metric storage and integration with AWS analytics tools like QuickSight or Redshift Spectrum. Metrics stored in Redshift can be joined with business datasets for rich observability and BI analysis.</p>
Configuration
NATS
AWS Redshift
Input and output integration examples
NATS
<ol> <li> <p><strong>Real-Time Analytics Dashboard</strong>: Utilize the NATS plugin to gather metrics from various NATS subjects in real time and feed them into a centralized analytics dashboard. This setup allows for immediate visibility into live application performance, enabling teams to react swiftly to operational issues or performance degradation.</p> </li> <li> <p><strong>Distributed System Monitoring</strong>: Deploy multiple instances of Telegraf configured with the NATS plugin across a distributed architecture. This approach allows teams to aggregate metrics from various microservices efficiently, providing a holistic view of system health and performance while ensuring no messages are dropped during transmission.</p> </li> <li> <p><strong>Historical Message Recovery</strong>: Leverage the capabilities of NATS JetStream along with this plugin to recover and process historical messages after Telegraf has been restarted. This feature is particularly beneficial for applications that require high reliability, ensuring that no critical metrics are lost even in case of service disruptions.</p> </li> <li> <p><strong>Dynamic Load Balancing</strong>: Implement a dynamic load balancing scenario where Telegraf instances consume messages from a NATS cluster based on load. Adjust the queue group settings to control the number of active consumers, allowing for better resource utilization and performance scaling as demand fluctuations occur.</p> </li> </ol>
AWS Redshift
<ol> <li> <p><strong>Business-Aware Infrastructure Monitoring</strong>: Store infrastructure metrics from Telegraf in Redshift alongside sales, marketing, or customer engagement data. Analysts can correlate system performance with business KPIs using SQL joins and window functions.</p> </li> <li> <p><strong>Historical Trend Analysis for Cloud Resources</strong>: Use Telegraf to continuously log CPU, memory, and I/O metrics to Redshift. Combine with time-series SQL queries and visualization tools like Amazon QuickSight to spot trends and forecast resource demand.</p> </li> <li> <p><strong>Security Auditing of System Behavior</strong>: Send metrics related to system logins, file changes, or resource spikes into Redshift. Analysts can build dashboards or reports for compliance auditing using SQL queries across multi-year data sets.</p> </li> <li> <p><strong>Cross-Environment SLA Reporting</strong>: Aggregate SLA metrics from multiple cloud accounts and regions using Telegraf, and push them to a central Redshift warehouse. Enable unified SLA compliance dashboards and executive reporting via a single SQL interface.</p> </li> </ol>
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Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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