GIP
Ginesys Integration Platform — apps, connectors, task pipelines, ingress APIs, and operations
Introduction
GIP (Ginesys Integration Platform) is the backend and data model behind the G1 DIP (Data Integration Platform) admin console. If you are searching for "DIP" in internal docs or repos, this section is the same product: configuration happens in the G1 DIP admin UI (g1-dip-frontend), while inbound traffic and job execution run through ingress and egress services in Zwing Connect.
This documentation describes features end-to-end: provisioning from public templates, connector–event mappings, task trees, event logs and jobs, async and sync ingress, and the App Connector Service (ACS) HTTP API.
Configuration and execution span the zwing-connect repo (ACS, ingress, egress, libs/dip-v2) and the g1-dip-frontend console. For deployment and secrets, see Platform and Local development.
Glossary
| Term | Meaning |
|---|---|
| App | A tenant-scoped integration application with inbound/outbound flags, access type, and optional link to a public app (refPublicAppId). |
| Event | A named occurrence (eventCode) bound to an app, either inbound or outbound, with optional publish/listener config. |
| Connector | Links an outbound app to an inbound app for a given enterprise (ssoEnterpriseId). |
| Connector–event mapping | For one connector, maps an outbound event to an inbound event and holds filters, templates, retry behaviour, ordering flags, and references to the event task tree. |
| Event task | A node in the configurable pipeline (HTTP, mapping, transform, etc.) stored per mapping; tasks form a tree via parentId. |
| Event log | Record of an accepted inbound payload (blob path, status pipeline) for tracing. |
| Job | Work unit created from an event log for a specific mapping; tracks status, blob paths, and retry. |
| Job task | Runtime execution row for each step of the tree for a given job. |
Explore
Public apps and default connectors
Creating apps from public templates and preconfigured connectors, events, and mappings
Event log and jobs
Event log lifecycle, jobs, job tasks, and observability filters
Task tree
Parent/child structure, validation, UI graph, import/export
Task types reference
enrich, transform, filter, mapping, dispatch, extract, http — config and execution
Data model reference
Fields on app, event, connector, and connector–event mapping
Ingress: async and sync
POST /ingress vs POST /ingress/sync, queues, and sync execution
Egress runtime and retry
Kafka consumers, sync execute, job statuses, retry API
ACS API overview
App Connector Service REST surface (/acs) aligned with the DIP UI
Template Master
Templates and how they relate to connector–event mappings
Seeding and sync public events
storage/seeders JSON, POST /acs/common/seed, sync-public-events for tenants
GIP blackout window (sequential)
isSequential, blackout_date, ingress block, egress remove/save, retry scheduler, and env
GIP Debezium — MySQL and Mongo
debezium-connector run-command, GIP MySQL bootstrap, GIP Mongo source, shared dip-v2 config
Related platform docs
- Kafka — topic naming and environments when debugging queue-backed processing.
- Local development — prerequisites for kubectl and service access.
- Setting environment variables — secrets and Key Vault patterns for deployed services.