SpecsModelExplore
Overview
Actors
External Systems
Data Platform
Ingestion
CDC Connectors
Batch Loader
Stream Router
Storage
Processing
Serving
Analytics UI
Governance
SpecsModelExplore
Ingestion
OverviewGuideLinks and Communications
IDproduct.ingestion
DescriptionCollects data from operational sources via CDC, batch APIs and event streams.
Keyingestion
Typesystem
TeamData Ingestion
Owneringestion@dataplatform.example
Statusactive
TechnologiesJava, Kafka Connect, Debezium
Attributeslatency: near-real-time, paths: cdc,batch,stream
Tags
Table of contents
Guide
Ingestion
System at a glance
Containers
Three ingress paths
Responsibilities
Key flows

Guide

Ingestion

Ingestion is the front door of the data platform. Every row change in a production database, every SaaS API export and every domain event on the bus passes through here before it can be stored, transformed or queried. If data enters the lakehouse at all, it enters through Ingestion first.

Responsibility in one sentence

Capture operational data from databases, APIs and event streams — with resumable offsets, schema awareness and deduplication — and land it in the bronze layer of the lakehouse.

System at a glance

Could not build diagram for model "example-data-processing".

Containers

CDC Connectors

Debezium readers that tail WAL/binlog and emit change events with schema evolution.

Batch Loader

Scheduled pulls from SaaS REST APIs, SFTP drops and manifest-validated files.

Stream Router

Consumes the platform bus, deduplicates and routes events to processing topics.

Three ingress paths

Responsibilities

  • Change-data-capture with resumable log positions.
  • Upstream schema change detection and registry notification.
  • SaaS API polling with rate-limit handling and retry backoff.
  • Event deduplication, partitioning and dead-letter routing.

Key flows

Operational DB changes replicate to the lake in near real time:

Domain events from microservices enter the same path through the stream router:

Schema changes

When upstream DDL arrives, the Schema Evolver classifies the change — see the schema-change scenario in specs.

Links and Communications

4 outgoing links

Outgoing Links(4)

Target objectLabelLink typeRelationRaw idRequiredDescription
Production Databases

example-data-processing.external_systems.production_dbs

external
reads CDC from—linksexternal_systems.production_dbs——
SaaS APIs

example-data-processing.external_systems.saas_apis

external
polls—linksexternal_systems.saas_apis——
Event Bus

example-data-processing.external_systems.event_bus

external:broker
subscribes to—linksexternal_systems.event_bus——
Storage

example-data-processing.product.storage

system
lands data in—linksproduct.storage——