Supervisor and CrateDB 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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Time series database
Source: DB Engines

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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

Input and output integration overview

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

The CrateDB plugin facilitates the writing of metrics to a CrateDB database, leveraging its PostgreSQL-compatible protocol to ensure a seamless experience for users.

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.

CrateDB

This plugin writes to CrateDB via its PostgreSQL protocol, allowing for metrics to be efficiently stored in a scalable database. CrateDB is designed for high-speed analytics, supporting time-series data and complicated queries, making it ideal for applications that require fast ingestion and analysis of large datasets. By utilizing the PostgreSQL protocol, the CrateDB output plugin ensures compatibility with existing PostgreSQL client libraries and tools, enabling a smooth integration for users who are already familiar with PostgreSQL’s ecosystem. The plugin provides options such as automatic table creation, connection parameters, and query timeouts, offering flexibility in how metrics are handled and stored within the database.

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"]

CrateDB

[[outputs.cratedb]]
  ## Connection parameters for accessing the database see
  ##   https://pkg.go.dev/github.com/jackc/pgx/v4#ParseConfig
  ## for available options
  url = "postgres://user:password@localhost/schema?sslmode=disable"

  ## Timeout for all CrateDB queries.
  # timeout = "5s"

  ## Name of the table to store metrics in.
  # table = "metrics"

  ## If true, and the metrics table does not exist, create it automatically.
  # table_create = false

  ## The character(s) to replace any '.' in an object key with
  # key_separator = "_"

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.

CrateDB

  1. Real-Time Analytics for IoT Devices: Collect and store metrics from thousands of IoT devices. By setting up a dynamic metrics table for each device, users can perform real-time analytics on the collected data, enabling quick insights into device performance, patterns, and potential failures. This setup benefits from CrateDB’s ability to handle high-throughput data ingestion while providing the necessary analytics capabilities to derive actionable insights.

  2. Website Performance Monitoring: Track key performance metrics from web applications, such as request latency and user activity. By storing metrics in CrateDB, teams can leverage the power of SQL-like queries to analyze traffic patterns, user engagement, and server performance over time, leading to optimized application performance and enhanced user experiences.

  3. Financial Transaction Analysis: Manage large volumes of financial transaction data for real-time fraud detection and analysis. With CrateDB’s scalable infrastructure, users can store, query, and analyze transaction metrics efficiently, allowing for the detection of anomalies and illicit activities based on transaction patterns and trends.

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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