Joule
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      • v1.2.0 Join Streams with stateful analytics
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  • Overview
  • Components
  • Deployment Architecture
  • Guardian
  • GuardianDB
  • Pod

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  1. Deployment strategies

Cluster

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Last updated 21 days ago

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Overview

Joule supports distributed execution using three key components: the Guardian, a configuration database, and Joule processes. This deployment model is designed for high-throughput workloads that can be efficiently distributed across multiple nodes, enabling scalable and resilient system performance.

This deployment model is ideal for various use cases such as:

  • Feed-forward compute pods for high-throughput compute loads

  • Distributable data and analytic processing

  • High event volume real-time processing

This feature is currently in beta version as of May 2025. Please contact for further information.

Components

Two key additional components are required for the Joule cluster deployment model.

  • Joulectl

  • Joule Runtime

  • Joule Guardian

  • GuardianDB

Deployment Architecture

Advance enterprise features provide the necessary fuctionality to process high volumes of event data in real-time

Guardian

The guardian process manages use case deployments and provides basic cluster information.

GuardianDB

This component serves as a centralised registry for all deployed artefacts and associated process metadata. When deployed, it enables Joule processes to be automatically initialised at startup by providing them with the necessary pod use cases and dependency information. This eliminates the need for manual configuration or intervention during system bootstrapping.

Pod

A pod is a logical grouping of Joule processes that execute the same use case. This structure is a critical feature that enables the formation of a feed-forward compute network. Through this mechanism, complex use cases can be deployed as independent units while still functioning cohesively as a unified system.

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