Supervisor 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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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider Supervisor and InfluxDB.

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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

This plugin gathers information about processes running under Supervisor using the XML-RPC API.

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.

Integration details

Supervisor

The Supervisor plugin for Telegraf is designed to collect metrics about processes managed by the Supervisor process control system using its XML-RPC API. The plugin is able to track various metrics, including process states and uptime, and provides options for configuring which metrics to collect through include or exclude lists. This integration is particularly useful for monitoring applications running under Supervisor, providing insights into their operational status and performance metrics. A minimum tested Supervisor version is 3.3.2, and it is recommended to secure the HTTP server with basic authentication for better security.

AWS Redshift

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.

Configuration

Supervisor

[[inputs.supervisor]]
  ## Url of supervisor's XML-RPC endpoint if basic auth enabled in supervisor http server,
  ## than you have to add credentials to url (ex. http://login:pass@localhost:9001/RPC2)
  # url="http://localhost:9001/RPC2"
  ## With settings below you can manage gathering additional information about processes
  ## If both of them empty, then all additional information will be collected.
  ## Currently supported supported additional metrics are: pid, rc
  # metrics_include = []
  # metrics_exclude = ["pid", "rc"]

AWS Redshift

[[outputs.postgresql]]
  ## Redshift connection settings
  host = "redshift-cluster.example.us-west-2.redshift.amazonaws.com"
  port = 5439
  user = "telegraf"
  password = "YourRedshiftPassword"
  database = "metrics"
  sslmode = "require"

  ## Optional: specify a dynamic table template for inserting metrics
  table_template = "telegraf_metrics"

  ## Note: Redshift does not support all PostgreSQL features; ensure your table exists and is compatible

Input and output integration examples

Supervisor

  1. Centralized Monitoring Dashboard: Implement this plugin to feed Supervisor metrics directly into a centralized monitoring dashboard, allowing teams to visualize the health and performance of their applications in real-time. This integration enables quick identification of issues, helps track service performance over time, and aids in capacity planning based on observed trends.

  2. Alerting for Process Failures: Utilize the metrics gathered by the Supervisor plugin to create an alerting mechanism that notifies engineers when critical processes go down or enter a fatal state. By setting thresholds in your monitoring system, teams can respond proactively to potential problems, minimizing downtime and ensuring system reliability.

  3. Historical Analysis of Process States: Store the metrics collected over time to analyze process state changes and patterns. By examining historical data, teams can identify recurring issues, track the impact of deployment changes, and optimize resource allocation based on process trends, leading to improved overall system performance.

  4. Integration with Incident Management Systems: Configure the Supervisor plugin to automatically send alerts to incident management systems like PagerDuty or OpsGenie when a process reaches a critical state. This integration streamlines the incident response process, ensuring that the right team members are notified promptly and can take action without delay.

AWS Redshift

  1. Business-Aware Infrastructure Monitoring: 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.

  2. Historical Trend Analysis for Cloud Resources: 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.

  3. Security Auditing of System Behavior: 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.

  4. Cross-Environment SLA Reporting: 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.

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.

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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