Data Ingestion
Making the path from source to useful data understandable.
Make the data journey understandable before designing each screen.
Data passes through collection, preparation and routing before anyone can use it. This project note explains the relationships in the original Splunk ingestion architecture.
Many sources feed several kinds of work.
The source architecture includes edge, on-premises and cloud environments, with destinations for search, security and observability. It also includes cloud storage, federated search and external destinations.
An upload is only one step in the system.
A single upload model leaves out parsing, processing, routing and the monitoring of the pipeline itself. Those dependencies are visible in the source map; no user-friction study is available for this case.
Trace the paths before separating them into screens.
The surviving work is an architecture map. This case makes its collection, preparation, routing and management paths easier to inspect; it does not claim a documented comparison of competing concepts.
Connect each source to its intended use.
The diagrams below are simplified readings of the original architecture. Monitoring and management span the journey rather than appearing only at its end.
- Edge
- On-premises
- Cloud
- 01Parse
- 02Process
- 03Route logs / metrics / traces
- Search + reporting
- Security
- Observability
Monitoring and management span the path; external destinations remain part of the wider model.
Start with where the data lives.
The source map includes edge, on-premises, and cloud environments, with AWS S3, Google Cloud, and Azure represented in the wider system.
Make transformation visible.
Parsing and processing sit between collection and downstream use. They explain why data arriving at a destination may differ from its source.
Give different data different paths.
Logs, metrics, and traces have distinct routing paths. External destinations and federated search also appear in the broader model.
Connect infrastructure to its purpose.
The destinations include observability, search and reporting, and security. Monitoring and management span the journey, making the pipeline itself something people can inspect.
A simplified, interactive reading of the presentation’s architecture diagram. It shows system relationships, not a live data pipeline.
The wider system also connects external destinations, cloud storage, and federated search.
Translate the system into places someone could inspect.
These are new concept wireframes derived from the architecture, not recovered product screens. They show how source setup, routing and pipeline health could relate.
Start with the source and its path
Expose the transformation boundary
Connect data types to useful destinations
Concept wireframes derived from the documented architecture; the source is a system map, not these product screens.
The architecture is the surviving design artifact.
The original presentation image follows. It records the system relationships behind the explanation; a shipped ingestion interface is not established by this material.
The map supports a design discussion, not a usability result.
No study method or findings accompany this artifact. A useful next check would ask people to trace a source, explain its transformations and identify where they would investigate a failure.
A documented system model with delivery evidence still missing.
The available evidence establishes the architecture work. It does not establish a delivery date, operational improvement or measured outcome.