Foundation Demo DP reference

The Foundation Demo DP (dp:quickstart) is an integrated bundle of deployment packs and modules that stands up a complete, end-to-end CDF environment in a single deployment: source ingestion, an enterprise data model, entity matching, file annotation, contextualization quality monitoring, and synthetic test data. It is the fastest way to get a fully functional CDF project running with real workflows — from raw source data through contextualized assets — without assembling individual packs manually.

The Foundation Demo DP is a fixed bundle (canCherryPick = false) — modifying or cherry-picking individual modules within the pack is not supported. In the Toolkit menu it appears as Foundation Deployment Pack Demo. If you need a customized setup, add the constituent modules individually with cdf modules add. For a production baseline rather than a demo, use the Foundation deployment pack.

Who it’s for

Target personas:

Data engineers — deploy and configure the demo bundle end-to-end.
Solution architects — evaluate CDF capabilities before committing to a project-specific model.
Field engineers — showcase CDF capabilities in a matter of minutes with the Open Industrial Data.

Use this pack when:

You are starting a new CDF project and want a complete, integrated pipeline — ingestion, data model, contextualization, and monitoring — deployed in one step.
You want to evaluate or demonstrate CDF’s full stack (entity matching, P&ID annotation, search, quality reporting) using included synthetic data without live integrations.
You need a standardized baseline that your team can then customize module by module.
You want to validate CDF capabilities before committing to a project-specific data model.

When not to use this pack:

If you only need one specific capability (for example, entity matching or P&ID annotation) — use the individual deployment packs instead to avoid deploying unused modules.
If you are building a governed production environment rather than a demo — use the Foundation deployment pack.

What’s included

The bundle deploys 13 modules across four layers.

Foundation and data model

Module	Description	Optional?
`cdf_common`	Shared spaces, datasets, RAW databases, and relation-writer runtime resources used by all downstream modules.	No
`cdf_ingestion`	Orchestration workflow that runs staged pipelines — data population first, then contextualization.	No
`cdf_search`	Location and search structures for Industrial Tools experiences.	No
`qs_enterprise_dm`	The Quickstart enterprise data model — containers, views, and spaces.	No

Source systems and synthetic data

Module	Description	Optional?
`cdf_sap_assets`	Ingests and transforms SAP functional locations and equipment. Includes synthetic SAP asset data.	No
`cdf_sap_events`	Ingests maintenance notifications, orders, and operations. Includes synthetic SAP events data.	No
`cdf_pi`	Creates time series entities and metadata from PI inputs. Includes synthetic PI time series data.	No
`cdf_sharepoint`	Loads files for annotation, including the P&IDs used in testing. Includes synthetic SharePoint file data.	No
`cdf_oid_sync`	Replays time-shifted Open Industrial Data to simulate continuous updates.	No

Contextualization

Module	Description	Optional?
`cdf_connection_sql`	Links entities using deterministic SQL and tag-based mapping logic.	No
`cdf_entity_matching`	Matches time series and assets using rule-based and ML-assisted methods. See CDF Entity Matching.	No
`cdf_file_annotation`	Runs prepare, launch, finalize, and promote steps for P&ID file annotations. See P&ID Annotation.	No

Monitoring

Module	Description	Optional?
`report_quality`	Computes contextualization KPIs and stores rates for monitoring trends.	No

Prerequisites

Verify all of the following before you start:

Cognite Toolkit version 0.8 or later is installed. See Setting up.
A cdf.toml file exists in your project root. If it is missing, run cdf modules init . and select Create toml file (required).
The data plugin is enabled in cdf.toml — required for the cdf data upload steps:
[plugins] data = true
Authentication is configured and verified — run cdf auth init and cdf auth verify. See Authentication and authorization.
The following values are available for your .env file:
- GROUP_SOURCE_ID — the Object ID of your IdP group.
- OPEN_ID_CLIENT_SECRET — generated from the Open Industrial Data Hub page with Create client secret.

Install and deploy

Because the Foundation Demo DP is a fixed bundle, deploying into a clean project is recommended.

Start a new project (recommended)
Add to an existing project

In a clean directory, initialize and select the bundle:
cdf modules init . --clean
--clean overwrites existing module folders in the current directory. Use a fresh directory or commit your changes first.
From the interactive module list, use Space to select Foundation Deployment Pack Demo, then press Enter to confirm.

Run cdf modules add and select Foundation Deployment Pack Demo from the interactive list.

The Foundation Demo DP is a fixed bundle and may conflict with modules you have already deployed. Review your existing module structure and commit local changes before proceeding.

Then configure the project before building:

Set your CDF project name in config.<env>.yaml, and add GROUP_SOURCE_ID and OPEN_ID_CLIENT_SECRET to your .env file (do not hardcode secrets in config files).

Under cdf_entity_matching, update the view configuration to match the Quickstart data model:

Variable	Change from	Change to
`targetViewFilterValues`	`root:WMT`	`root:ast_VAL`
`targetViewSearchProperty`	`name`	`aliases`
`AssetViewExternalId` / `targetViewExternalId`	`YourOrgAsset`	`Asset`
`TimeSeriesViewExternalId` / `entityViewExternalId`	`YourOrgTimeSeries`	`Enterprise_TimeSeries`

Under cdf_file_annotation, set ApplicationOwner to the owner email address(es).
Review all cron expressions — placeholder values may be set to February 29 and must be changed to valid recurring dates.
Enable FILE_ANNOTATION mode in the SAP asset transformation. In modules/sourcesystem/cdf_sap_assets/transformations/population/asset.Transformation.sql, comment out the COMMON MODE block and uncomment the FILE_ANNOTATION MODE block. This sets asset external IDs as ast_<id>, creates the ast_VAL root node, and populates the aliases and tags that diagram detection needs.

Then build and deploy:

Build deployment artifacts

cdf build

The Toolkit substitutes template variables and writes artifacts to the build/ directory. If you need to change the project name or any variables marked <change_me>, edit config.<env>.yaml first — see Configure, build, and deploy modules.

Dry-run the deployment

cdf deploy --dry-run

Inspect the output and confirm that configurations look correct before deploying.

Deploy to CDF

cdf deploy

The Toolkit deploys only configurations that have changed since the last run.

Set up CI/CD (optional)

For governed production deployments, automate build, dry-run, and deploy in a pipeline. See Set up CI/CD pipelines.

A warning about non-resource directories such as upload_data in cdf_pi is expected and can be ignored.

After deployment, upload the synthetic test data for the source and contextualization modules:

cdf data upload dir modules/sourcesystem/cdf_pi/upload_data
cdf data upload dir modules/sourcesystem/cdf_sap_assets/upload_data
cdf data upload dir modules/sourcesystem/cdf_sap_events/upload_data
cdf data upload dir modules/sourcesystem/cdf_sharepoint/upload_data
cdf data upload dir modules/contextualization/cdf_entity_matching/upload_data
cdf data upload dir modules/contextualization/cdf_file_annotation/upload_data

If your modules directory is under an organization directory, prepend that directory name to each path. To skip project-name verification in test environments, add --skip-verify-cdf-project to each upload command.

Finally, in the CDF Data Workflows UI, trigger the workflows in order — wait for each to finish before starting the next:

ingestion — populates the data model and creates baseline relationships.
cdf_file_annotation — annotates the uploaded P&ID files and links them to assets.
EntityMatching — runs metadata enrichment and entity matching.

Verify the deployment

After deployment and workflow execution, confirm success with these checks:

The cdf deploy command finishes without errors and all modules deploy successfully.
All cdf data upload commands finish without errors — in Integrate > Staging (RAW), confirm the tables from each module’s upload_data/ are present.
In Integrate > Data Workflows, confirm the three workflows (ingestion, cdf_file_annotation, EntityMatching) completed without errors.
Open Industrial Tools > Search > Files and confirm that uploaded P&IDs have linked assets — annotations are applied.
In Build Solutions > Functions, review the logs for the entity matching function and confirm time series were processed without errors.
In Data Modeling > Data Models, confirm the Quickstart enterprise data model is deployed with its spaces, containers, and views.
Run the quality report workflow, then confirm the contextualization-rate report table is populated in the quality reports RAW database.

The deployment is successful when all three workflows complete, annotations and matches appear, and the quality report produces KPI output.

Configuration reference

All parameters are set in config.<env>.yaml at the project root. Sensitive values (GROUP_SOURCE_ID, client IDs and secrets) must be set in your .env file, not hardcoded. Because this is a fixed demo bundle, all of the following must be set or updated before deploying:

Parameter	Module	Description
CDF project name	All	Your CDF project external ID for the target environment.
`GROUP_SOURCE_ID`	All	Object ID of your IdP group (`.env`). Used for data model updates and transformation runs.
`OPEN_ID_CLIENT_SECRET`	`cdf_oid_sync`	Client secret for the Open Industrial Data application (`.env`).
`targetViewFilterValues`	`cdf_entity_matching`	Filter value for the target asset view. Update `root:WMT` → `root:ast_VAL`.
`targetViewSearchProperty`	`cdf_entity_matching`	Search property on the target view. Update `name` → `aliases`.
`AssetViewExternalId` / `targetViewExternalId`	`cdf_entity_matching`	External ID of the asset view. Update `YourOrgAsset` → `Asset`.
`TimeSeriesViewExternalId` / `entityViewExternalId`	`cdf_entity_matching`	External ID of the time series view. Update `YourOrgTimeSeries` → `Enterprise_TimeSeries`.
`ApplicationOwner`	`cdf_file_annotation`	Email address(es) of the application owner for the file annotation pipeline.
Cron expressions	All scheduled modules	Placeholder cron values may be set to February 29 — update to valid recurring dates before deploying.

Architecture

The Foundation Demo DP is a fixed bundle of Cognite Toolkit modules across four layers. The cdf_ingestion workflow enforces execution order — data population runs before contextualization — so each layer has the data it needs when it runs.

modules/
├── common/
│   ├── cdf_common/        ← shared spaces, datasets, RAW
│   ├── cdf_ingestion/     ← staged orchestration workflow
│   └── cdf_search/        ← search + location structures
├── sourcesystem/
│   ├── cdf_pi/            ← PI time series + synthetic data
│   ├── cdf_sap_assets/    ← SAP assets + synthetic data
│   ├── cdf_sap_events/    ← SAP events + synthetic data
│   ├── cdf_sharepoint/    ← files + synthetic P&IDs
│   └── cdf_oid_sync/      ← Open Industrial Data sync
├── contextualization/
│   ├── cdf_connection_sql/  ← deterministic SQL linking
│   ├── cdf_entity_matching/ ← rule-based + ML matching
│   └── cdf_file_annotation/ ← P&ID annotation pipeline
├── dashboards/
│   └── report_quality/   ← contextualization KPI monitoring
└── datamodels/
    └── qs_enterprise_dm/ ← Quickstart enterprise data model

Pipeline execution order

FILE_ANNOTATION mode

For P&ID annotation to work, the SAP asset transformation must use FILE_ANNOTATION mode rather than COMMON mode. This mode sets asset external IDs as ast_<id>, creates the ast_VAL root node, and populates the aliases and tags the file annotation pipeline uses for diagram detection. It is a manual SQL edit in asset.Transformation.sql before deployment.

Troubleshooting

Symptom	Likely cause	Resolution
Module files overwritten unexpectedly	Ran `cdf modules init . --clean` in a directory with existing work.	Use a clean directory, or commit existing work first. Use `cdf modules add` to add modules to an existing project without overwriting.
`cdf data upload` fails with “data plugin not enabled”	`[plugins] data = true` is missing from `cdf.toml`.	Add `data = true` under `[plugins]` in `cdf.toml` and retry.
`cdf data upload` fails with a project verification error	The project name in the upload manifest does not match the configured CDF project.	Add `--skip-verify-cdf-project` for test environments, or align the project name in `Manifest.yaml` with your CDF project.
File annotation finds no matches	FILE_ANNOTATION mode was not enabled, so the `ast_VAL` root and aliases are missing.	Enable FILE_ANNOTATION mode in `asset.Transformation.sql`, redeploy, and re-run the ingestion and annotation workflows.
Entity matching returns no results	View external IDs in `cdf_entity_matching` still use placeholder values (`YourOrgAsset`, `YourOrgTimeSeries`).	Update all entity matching view configuration values as listed in Configuration reference.
Workflow fails on the first run after deploy	Synthetic data was not uploaded before triggering workflows, or an upload failed.	Verify all `cdf data upload` commands completed and the expected tables are visible in Integrate > Staging (RAW) before triggering workflows.
Scheduled workflows fail to trigger	Cron expressions are set to an invalid date (for example, February 29 in a non-leap year).	Update all cron expressions in the config to valid recurring dates before deploying.
`cdf deploy` fails with “Insufficient permissions”	Toolkit service account is missing capabilities required by one or more modules.	Add capabilities for Functions, Workflows, Transformations, RAW, Data Sets, Data Modeling, and Extraction Pipelines to the CDF group used by the Toolkit.

For issues not covered here, contact Cognite support.

Support

Field	Details
Team	Cognite Value Delivery Team
Documentation	Cognite product documentation
Questions and feedback	Deployment Packs group on Cognite Hub
Version	1.0.0
Last updated	2026

​Who it’s for

​What’s included

​Foundation and data model

​Source systems and synthetic data

​Contextualization

​Monitoring

​Prerequisites

​Install and deploy

​Verify the deployment

​Configuration reference

​Architecture

​Pipeline execution order

​FILE_ANNOTATION mode

​Troubleshooting

​Support

Who it’s for

What’s included

Foundation and data model

Source systems and synthetic data

Contextualization

Monitoring

Prerequisites

Install and deploy

Verify the deployment

Configuration reference

Architecture

Pipeline execution order

FILE_ANNOTATION mode

Troubleshooting

Support