Platform Architecture Overview

High-level map of SrotaX modules, runtimes, and extension points. Use this to select the right entry point and understand how pieces compose.

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1. Layered architecture

Connect  →  Streaming Engine  →  Rule Engine
                  │                │
          └──────►│                │
                  ▼                │
              SrotaX Core  ◄──────┘
                    │
        Enrichment operators (Connect)

Layer	Purpose
SrotaX Core	Deterministic aggregation engine (stages/operators), expression evaluator, metrics, registries.
SrotaX Connect	Source/sink connectors (Kafka, HTTP sink, custom SPI) plus enrichment operators.
Streaming Engine	Always-on pipelines (fetch → transform → deliver → checkpoint).
Rule Engine	JSON/DSL-defined rule sets for decisioning and governance workflows.

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2. Module checklist

Feature	Module	Reference
Aggregation runtime	fluxion-core	Core Overview
Connectors	fluxion-connect	Connect Overview
Enrichment operators	fluxion-connect	Enrich Overview
Rule engine	fluxion-rules	Rule Engine Overview
Streaming engine	(contained in fluxion-core module today)	Streaming Overview

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3. Selecting an entry point

Need	Start here
Run aggregation pipelines in-process	fluxion-core (see Usage Guide)
Ingest from Kafka/HTTP	fluxion-connect + Streaming Engine
Enrich with HTTP/SQL lookups	Enrichment operators in fluxion-connect
Declarative rule authoring/governance	fluxion-rules (Rule Engine)
Long-running stream processing	Streaming Engine (with Connect)

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4. Extending SrotaX

1. Add capabilities at the lowest layer.
2. New operator/stage → contribute to SrotaX Core.
3. New connector → implement SPI in SrotaX Connect.
4. New enrichment behaviour → extend the operators in SrotaX Connect.
5. Expose through runtimes. Surface new operators/connectors to rule/streaming engines so users can adopt them immediately.
6. Document + test. Update docs/tests alongside the new contribution to keep assistants and developers aligned.

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5. Integration patterns

Scenario	Modules involved	Notes
Request/response service with pipeline execution	Core	Cache parsed stages, use PipelineExecutor.
Manual approval workflow (Temporal)	Core + Rules + Workflow integration	See Temporal Bridge.
Real-time enrichment from Kafka to HTTP	Core + Connect + Streaming	Use streaming pipeline with Kafka source and HTTP sink/operators.
Analytics batch job with JDBC source	Core + custom source	Extend streaming SPI or use executor in batch mode.

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6. References & next steps

• Core Overview – runtime APIs and extension points.
• Connect Overview – built-in connectors and SPI.
• Enrich Overview – HTTP/SQL operators.
• Streaming Overview – pipeline lifecycle, error policies.
• Rule Engine Overview – declarative rule runtime.
• Usage Guide – end-to-end pipeline execution tutorial.
• Examples Gallery – ready-made pipelines to copy.

This overview keeps the module map clear; dive into the linked guides for deeper, LLM-ready documentation.