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Spark Platform Overview

Spark is an engineering platform for enterprise application delivery and runtime operations. It covers the full lifecycle from application registration, low-code design, release pipelines, runtime workbenches, and plugin-based extension.

Spark is not meant to be a single-purpose tool. Its purpose is to turn repeated engineering and business-operation work into platform capabilities: applications can be registered consistently, configuration can be managed per environment, releases can be orchestrated by pipelines, tasks can move from design-time configuration into runtime execution, and product capabilities can grow through the Lattice extension model.

Core Capabilities​

Spark Console​

  • Manages applications, clusters, environments, secrets, deployment templates, and runtime configuration
  • Supports K8S cluster onboarding, Harbor, Maven, certificates, bastion hosts, and infrastructure settings
  • Provides the shared entry point for Spark Flow, Spark Runtime, and low-code applications

Spark Build​

  • Focuses on application creation and low-code construction
  • Supports business model design for forms, pages, APIs, task types, and related configuration
  • Gradually carries AI-assisted application and business-configuration generation

Spark Flow​

  • Provides pipelines, release branches, image builds, and deployment execution
  • Supports native K8S Job builds, Kaniko image builds, and environment-level deployment configuration
  • Turns manual release operations into traceable and reusable delivery flows

Spark Runtime​

  • Hosts runtime workbenches, task processing, application runtime state, and runtime interactions
  • Supports separated runtime entries for development, testing, and production environments
  • Gives business users a compact and direct runtime experience

Spark Tasks​

  • Migrates and modernizes the ERA task system, including task types, fields, forms, workflows, and permission schemas
  • Supports task creation, pending work, transitions, attachments, activity history, progress, and query filters
  • Connects design-time workflow configuration to a real task workbench

Spark Plugin System​

  • Uses Lattice to define stable extension points and business identities
  • Allows Console menus, build executors, deployment capabilities, Dashboard Gadgets, and more to be extended by plugins
  • Keeps the platform core stable while leaving differentiated capabilities to governed extensions

Our Direction​

Spark aims to become an extensible engineering foundation for enterprise applications.

It should help teams create applications faster, deliver them more safely, observe runtime state more clearly, and move business workflows naturally from designers into runtime workbenches.

We believe a strong platform should not hard-code every difference into the main process. Stable capabilities belong in the core, while industry-specific, deployment-specific, and business-specific differences should be handled through a governed extension model.

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