Pipeline Migration
MicrosoftOfficialPublished by Microsoft
- Skill
- Workflow
- Cloud and DevOps
- MIT
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured, API-driven workflow for migrating Synapse Data Factory pipelines to Microsoft Fabric. It handles the transformation of pipeline JSON, including inlining datasets, converting linked services to Fabric connections, mapping SynapseNotebook activities to TridentNotebook, and migrating global parameters to Variable Libraries. The skill includes assessment, orchestration, and validation phases to ensure a smooth transition, while identifying unsupported activities that require manual intervention.
What it does
- Assesses Synapse pipeline complexity and migration scope.
- Automates the conversion of Synapse pipeline JSON to Fabric DataPipeline format.
- Inlines dataset definitions directly into pipeline activities.
- Maps Synapse linked services to Fabric connections.
- Converts global parameters into Fabric Variable Library items.
- Updates notebook activities to reference Fabric notebook GUIDs.
When to use it
- When migrating existing Synapse Data Factory pipelines to Microsoft Fabric.
- To assess the feasibility and blockers of a pipeline migration project.
- When you need to convert Synapse global parameters to Fabric Variable Libraries.
- When you need to update notebook activity references for the Fabric environment.
Advantages
- Reduces manual effort by automating JSON transformations and API calls.
- Provides a clear, phased approach to migration with built-in assessment.
- Ensures compatibility by mapping deprecated Synapse features to Fabric equivalents.
- Reduces errors by automating GUID lookups and connection references.
Usage examples
- “Assess my Synapse workspace 'FinancePipelineWS' for migration to Fabric.”
- The agent will query the Synapse workspace, analyze the pipelines, and generate a markdown report detailing the migration scope, potential blockers, and unsupported activities.
- “Migrate all pipelines from Synapse workspace 'FinancePipelineWS' to Fabric workspace 'FinanceFabricWS'.”
- The agent will orchestrate the migration, including creating connections, converting parameters, updating notebook references, and deploying the new pipelines to Fabric.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/pipeline-migration/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip pipeline-migration.zip -d .agents/skills
Documentation by Microsoft
Telemetry — MANDATORY. Every
api.fabric.microsoft.comcall must carryx-ms-fabric-skill: pipeline-migration(az rest:--headers "x-ms-fabric-skill=pipeline-migration"), including every LRO poll,fabric_lroand retry. Snippets omit it — add it anyway.
CRITICAL NOTES
To find workspace details (including its ID) from a workspace name: list all workspaces, then use JMESPath filtering
To find item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace, then use JMESPath filtering
Fabric does NOT have a "Dataset" item type — all dataset properties are inlined into activity
typePropertiesLinked Services map to Fabric Connections — in pipeline activity JSON,
referenceNameon the activity'slinkedServiceblock uses the Fabric connection display name (not the connection GUID); the connection GUID is used only on Fabric REST API callsNotebook activities change from
SynapseNotebooktoTridentNotebookand reference notebooks by GUID, not by nameSynapse global parameters become a Variable Library item in Fabric, referenced as
@pipeline().libraryVariables.<name>. Variable LibraryNumbertypes are not consumable in pipelines — SynapseFloat/Doubleare mapped toStringfor runtime compatibilityThe
Validationactivity type does not exist in Fabric — it must be rewritten asGetMetadata+IfConditionTriggers are intentionally excluded from this skill — recreate schedules manually in Fabric after migration
SSIS package execution, SHIR-exclusive connectors, and Databricks activities are parked — see pipeline-gotchas.md
Synapse Pipelines → Microsoft Fabric Data Factory Migration
Prerequisite Knowledge
These companion documents provide general Fabric REST patterns. Do NOT read them upfront — reference only when a specific phase requires a pattern not already covered in this skill's resource files:
COMMON-CORE.md — General Fabric REST API patterns, authentication & token audiences, item discovery via JMESPath
COMMON-CLI.md —
az rest/az loginCLI patterns, authentication recipes, pipeline run/schedule operationsITEM-DEFINITIONS-CORE.md —
DataPipelineandVariableLibraryitem definition structures (pipeline-content.json, variables.json)SPARK-AUTHORING-CORE.md — Fabric notebook item creation (needed when notebook items don't exist yet in Fabric)
For the notebook side of the migration (the notebooks that pipeline activities call), use the companion synapse-migration skill to migrate the notebook content itself.
Table of Contents
| Topic | Reference |
|---|---|
| Pre-Migration Assessment (run first) | pipeline-assessment.md |
| Migration Orchestrator | pipeline-orchestrator.md |
| API-Driven Migration Workflow | § API-Driven Migration Workflow |
| Activity Type Mapping | activity-mapping.md |
| Notebook Activity Migration (primary focus) | notebook-activity-migration.md |
| Linked Services → Connections | linked-service-to-connection.md |
| Dataset Inlining | dataset-inlining.md |
| Global Parameters → Variable Library | global-parameters-to-variable-library.md |
| Pipeline Gotchas & Parked Activities | pipeline-gotchas.md |
| Validation & Testing | validation-testing.md |
| Migration Report | migration-report.md |
Context Loading Guide
IMPORTANT — Load only what you need. Do NOT read all resource files upfront.
| When | Read This File |
|---|---|
| User asks for an assessment, scope, or plan before migrating | pipeline-assessment.md |
| User asks to migrate a full pipeline workspace | pipeline-orchestrator.md |
| User asks about activity type mapping or unsupported activities | activity-mapping.md |
| User has SynapseNotebook activities (most common) | notebook-activity-migration.md |
| User asks about linked services or connections | linked-service-to-connection.md |
| User asks about Copy, Lookup, or GetMetadata with datasets | dataset-inlining.md |
| User has global parameters to convert | global-parameters-to-variable-library.md |
| User hits SSIS, SHIR, Databricks, or other blockers | pipeline-gotchas.md |
| Post-migration verification | validation-testing.md |
| Generating a migration summary | migration-report.md |
API-Driven Migration Workflow
Authentication
| Target | Token Audience |
|---|---|
| Synapse Data Plane (pipelines, datasets, linked services) | https://dev.azuresynapse.net |
| Synapse ARM (global parameters, workspace properties) | https://management.azure.com |
| Fabric REST API (create pipelines, connections, Variable Libraries) | https://api.fabric.microsoft.com |
Use
az account get-access-token --resource <audience> --query accessToken -o tsvto acquire tokens.
Synapse Data-Plane API Reference
| Operation | Endpoint |
|---|---|
| List all pipelines | GET https://{ws}.dev.azuresynapse.net/pipelines?api-version=2020-12-01 |
| Get pipeline definition | GET https://{ws}.dev.azuresynapse.net/pipelines/{name}?api-version=2020-12-01 |
| List all datasets | GET https://{ws}.dev.azuresynapse.net/datasets?api-version=2020-12-01 |
| Get dataset definition | GET https://{ws}.dev.azuresynapse.net/datasets/{name}?api-version=2020-12-01 |
| List all linked services | GET https://{ws}.dev.azuresynapse.net/linkedservices?api-version=2020-12-01 |
| Get linked service | GET https://{ws}.dev.azuresynapse.net/linkedservices/{name}?api-version=2020-12-01 |
| Get workspace (global parameters) | GET https://management.azure.com/subscriptions/{subId}/resourceGroups/{rg}/providers/Microsoft.Synapse/workspaces/{ws}?api-version=2021-06-01 |
Fabric API Reference
| Operation | Endpoint |
|---|---|
| List connections | GET https://api.fabric.microsoft.com/v1/connections |
| Create connection | POST https://api.fabric.microsoft.com/v1/connections |
| Create pipeline item | POST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items |
| Update pipeline definition | POST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items/{id}/updateDefinition |
| Get pipeline definition | POST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items/{id}/getDefinition |
| Create Variable Library | POST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items (type: VariableLibrary) |
| List notebooks in workspace | GET https://api.fabric.microsoft.com/v1/workspaces/{wsId}/notebooks |
Assessment Mode (Optional but Recommended)
Before creating any items in Fabric, run the pipeline assessment to understand scope, complexity, and blockers. The assessment is read-only — it queries Synapse APIs only and produces a markdown report.
Copilot workflow — no Python script file needed:
Ask the user: "What is the name of your Synapse workspace?"
Auto-discover subscription ID and resource group via
az account showandaz synapse workspace showRun the assessment code inline from the terminal
Print the full report output directly in the chat
| When to Use | Action |
|---|---|
| User wants to understand migration scope before committing | Ask for workspace name → load pipeline-assessment.md → run inline |
| User asks "what will and won't migrate?" | Run assessment, present the Executive Summary section |
| User asks for a migration plan or scoping document | Run assessment, print report in chat |
| User has already decided to migrate | Skip assessment — go straight to Migration Phases below |
To also save the report to disk, pass
output_path=f"pipeline-assessment-{SYNAPSE_WS}.md"togenerate_assessment_report(). ThePipelineAssessmentobjects it produces feed directly into the migration scripts in pipeline-orchestrator.md.
Migration Mode (Inline — No Script File Required)
Copilot performs the migration directly from the terminal. No Python files to save or run manually.
Ask the user for:
Synapse workspace name (reuse from assessment if already run)
Fabric workspace name
Which pipelines to migrate — specific names, or
*for allOptional name suffix to append to each pipeline in Fabric (e.g.
_migrated) — leave blank to keep the original name
Everything else is auto-discovered:
Subscription ID and resource group via
az account show+az synapse workspace showFabric workspace ID via
GET /v1/workspacesfiltered by display nameNotebook GUIDs in Fabric via
GET /v1/workspaces/{wsId}/notebooks(required forSynapseNotebook → TridentNotebook)Connection names in Fabric via
GET /v1/connections(when datasets reference linked services)
What is fully automated inline:
✅
SynapseNotebook→TridentNotebook— type rename, GUID lookup, removesparkPool/sessionConfiguration, fix timeout to 12h max✅ All compatible activity types — pass through with minor property adjustments
✅ Dataset inlining into activity
typeProperties✅ Global parameter expressions rewritten to
@pipeline().libraryVariables.<name>✅ Pipeline JSON assembly and deployment to Fabric via REST
Copilot checks before starting — will pause and report if:
A notebook referenced by a
SynapseNotebookactivity does not exist in the Fabric workspace yetA Fabric Connection is missing for a linked service referenced by dataset activities
Load pipeline-orchestrator.md for the complete inline runner.
Migration Phases (Execute in Order)
| Phase | Source | Target | Resource |
|---|---|---|---|
| Phase 0 | Synapse notebooks (referenced by pipeline activities) | Fabric Notebooks | synapse-migration skill |
| Phase 1 | Synapse global parameters | Fabric Variable Library | global-parameters-to-variable-library.md |
| Phase 2 | Synapse linked services | Fabric Connections | linked-service-to-connection.md |
| Phase 3 | Synapse datasets | Inlined into activities | dataset-inlining.md |
| Phase 4 | Synapse pipeline activities | Fabric pipeline activities | activity-mapping.md + notebook-activity-migration.md |
| Phase 5 | Assembled pipeline JSON | Fabric DataPipeline item | pipeline-orchestrator.md |
| Final | — | Validation | validation-testing.md |
Phase 0 must precede Phase 4: Fabric Notebook GUIDs are needed before TridentNotebook activities can be written. Phase 2 must precede Phase 3: Connection names must exist before they can be referenced in inlined datasets.
Activity Type Quick Reference
Full mapping table, before/after examples, and parking decisions are in activity-mapping.md.
| Synapse Activity | Fabric Equivalent | Status |
|---|---|---|
SynapseNotebook | TridentNotebook | ✅ Migrated — see notebook-activity-migration.md |
Copy | Copy | ✅ Migrated — datasets inlined |
Lookup | Lookup | ✅ Migrated — datasets inlined |
GetMetadata | GetMetadata | ✅ Migrated — datasets inlined |
Validation | GetMetadata + IfCondition | ✅ Migrated — split into 2 activities |
ForEach | ForEach | ✅ Compatible |
IfCondition | IfCondition | ✅ Compatible |
Switch | Switch | ✅ Compatible |
Until | Until | ✅ Compatible |
Wait | Wait | ✅ Compatible |
Fail | Fail | ✅ Compatible |
SetVariable | SetVariable | ✅ Compatible |
AppendVariable | AppendVariable | ✅ Compatible |
ExecutePipeline | ExecutePipeline | ✅ Compatible — add workspaceId |
WebActivity | WebActivity | ✅ Compatible |
Script | Script | ✅ Compatible — update connection refs |
Delete | Delete | ✅ Migrated — datasets inlined |
Filter | Filter | ✅ Compatible |
SparkJobDefinition (Synapse SJD) | SparkJobDefinition | ✅ Update GUID refs |
HDInsightSpark | TridentNotebook or SparkJobDefinition | ⚠️ Rewrite required |
AzureMLBatchExecution | WebActivity | ⚠️ Rewrite as REST call |
AzureFunctionActivity | WebActivity | ⚠️ Rewrite — use function URL + key |
DatabricksNotebook | ⛔ Parked | See pipeline-gotchas.md |
DatabricksSparkJar | ⛔ Parked | See pipeline-gotchas.md |
DatabricksSparkPython | ⛔ Parked | See pipeline-gotchas.md |
ExecuteSSISPackage | ⛔ Parked | See pipeline-gotchas.md |
AzureBatch | ⛔ Parked | No Fabric equivalent |
Custom | ⛔ Parked | No Fabric equivalent |
Must / Prefer / Avoid
MUST DO
Migrate notebooks before pipelines — Fabric TridentNotebook activities require notebook GUIDs, not names. Use the synapse-migration skill first
Create Fabric Connections before building pipeline JSON — linked service names in Synapse become connection references in Fabric; you need the connection names before inlining datasets
Inline all dataset definitions — Fabric Data Factory has no Dataset item type; all
inputs/outputsdataset properties must be embedded in each activityReplace
@pipeline().globalParameters.<name>with@pipeline().libraryVariables.<name>after creating the Variable LibraryReplace Validation activities with a
GetMetadata+IfConditionpair —Validationdoes not exist as an activity type in FabricRemove
sparkPoolandsessionConfigurationfrom migrated notebook activities — pool selection and session config belong in the Fabric Environment attached to the notebook
PREFER
Variable Library with Value Sets for dev/test/prod environments — use
@pipeline().libraryVariables.<name>with environment-specific Value Sets instead of pipeline-level parameters for environment promotionParameterized
notebookParametersover hardcoded values in TridentNotebook activities — mirrors Synapse parameterized notebook patternTest notebook activities individually before running the full migrated pipeline — notebook GUIDs are the most common source of failure
OneLake Lakehouse sources/sinks for Copy activities where applicable — eliminates the need for external connections for data already in OneLake
AVOID
Do not reference notebooks by name in
TridentNotebookactivities — use the GUID from the Fabric workspace notebook listDo not carry over Synapse triggers — they are not migrated by this skill; recreate schedules in Fabric after validating the pipeline
Do not attempt to migrate SSIS, Databricks, or AzureBatch activities without reading pipeline-gotchas.md first — these require manual intervention
Do not hardcode workspace/item GUIDs in pipeline JSON — use Variable Library entries or pipeline parameters so environments can be promoted without editing pipeline JSON
Do not use
@pipeline().globalParameterssyntax after migration — this expression path does not exist in Fabric; all migrated global parameters must be accessed via@pipeline().libraryVariables
Migration Gotchas — Quick Reference
Full troubleshooting guide is in pipeline-gotchas.md.
| # | Flag ID | Issue | Severity | Resolution Summary |
|---|---|---|---|---|
| PG1 | NOTEBOOK_GUID_NOT_FOUND | Notebook not yet migrated to Fabric when building TridentNotebook activity | High | Run synapse-migration skill first; get GUID from GET /v1/workspaces/{wsId}/notebooks |
| PG2 | DATASET_NOT_INLINED | Activity still references a named dataset (not valid in Fabric) | High | Apply dataset-inlining.md patterns to embed dataset properties into activity source/sink |
| PG3 | GLOBAL_PARAM_EXPRESSION | @pipeline().globalParameters.<name> expression left in migrated pipeline | High | Replace with @pipeline().libraryVariables.<name> after creating Variable Library |
| PG4 | VALIDATION_ACTIVITY_UNSUPPORTED | Validation activity type left in pipeline JSON | High | Rewrite as GetMetadata + IfCondition — see activity-mapping.md |
| PG5 | SHIR_CONNECTOR_PARKED | Activity uses a linked service backed by a Self-Hosted Integration Runtime | Medium | Must set up on-premises data gateway in Fabric; see pipeline-gotchas.md |
| PG6 | SSIS_ACTIVITY_PARKED | ExecuteSSISPackage activity cannot be migrated | High | Parked — no Fabric equivalent; see pipeline-gotchas.md for alternatives |
| PG7 | DATABRICKS_ACTIVITY_PARKED | Databricks activity type has no Fabric native equivalent | High | Parked — use Databricks REST API via WebActivity as workaround; see pipeline-gotchas.md |
| PG8 | SPARKPOOL_REF_ORPHANED | sparkPool / targetBigDataPool reference left in TridentNotebook activity | Medium | Remove sparkPool and sessionConfiguration blocks; pool config belongs in Fabric Environment |
| PG9 | EXECUTE_PIPELINE_NO_WORKSPACE | ExecutePipeline activity missing workspaceId for referenced pipeline | Medium | Add workspaceId to typeProperties; required even for same-workspace child pipelines — omitting it causes runtime failures |
| PG10 | LINKED_SERVICE_NO_CONNECTION | Linked service has no matching Fabric Connection | High | Create connection manually or via API; update connection reference in inlined dataset |
Post-Migration: What's Next
After pipeline migration, hand off to these companion skills and tools:
| Task | Skill / Tool |
|---|---|
| Migrate notebook content (mssparkutils → notebookutils, linked services) | synapse-migration skill |
| Schedule migrated pipelines | COMMON-CLI.md § Job Scheduling |
| Monitor pipeline runs | Fabric workspace → Monitor hub |
| Build new Fabric pipelines | Refer to ITEM-DEFINITIONS-CORE.md § DataPipeline |
| Explore migrated Lakehouse data post-pipeline run | spark-cli or sqldw-cli skill |
Examples
SynapseNotebook → TridentNotebook activity (before/after)
{
"name": "Run_Notebook",
"type": "SynapseNotebook",
"typeProperties": {
"notebook": {"referenceName": "MyNotebook", "type": "NotebookReference"},
"sparkPool": {"referenceName": "BigPool", "type": "BigDataPoolReference"}
}
}After migration (GUID from GET /v1/workspaces/{wsId}/notebooks):
{
"name": "Run_Notebook",
"type": "TridentNotebook",
"typeProperties": {
"notebookId": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
"workspaceId": "yyyyyyyy-yyyy-yyyy-yyyy-yyyyyyyyyyyy"
}
}Global parameter expression rewrite
Before (Synapse): @pipeline().globalParameters.batchDate
After (Fabric): @pipeline().libraryVariables.batchDateDataset inlining: Copy activity — dataset reference → connection display name
Synapse dataset InputBlobDataset (will be inlined and removed):
{
"type": "AzureBlob",
"linkedServiceName": {"referenceName": "AzureBlobLinkedService"},
"typeProperties": {"folderPath": "input/", "fileName": "data.csv"}
}Synapse Copy activity (before — references dataset by name):
{
"name": "CopyData", "type": "Copy",
"inputs": [{"referenceName": "InputBlobDataset", "type": "DatasetReference"}],
"typeProperties": {"source": {"type": "BlobSource"}, "sink": {"type": "BlobSink"}}
}After migration (connection display name for AzureBlobLinkedService is My ADLS Connection):
{
"name": "CopyData", "type": "Copy",
"typeProperties": {
"source": {"type": "BlobSource", "storeSettings": {"type": "AzureBlobStorageReadSettings"}},
"sink": {"type": "BlobSink", "storeSettings": {"type": "AzureBlobStorageWriteSettings"}}
},
"linkedService": {"referenceName": "My ADLS Connection", "type": "LinkedServiceReference"}
}See activity-mapping.md and notebook-activity-migration.md for full before/after examples.
Files
- ATTRIBUTION.mdAdded by AutoGineer881 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md21.3 KiB
- apm.yml450 B
- resources/activity-mapping.md16.2 KiB
- resources/dataset-inlining.md28.1 KiB
- resources/global-parameters-to-variable-library.md18.7 KiB
- resources/linked-service-to-connection.md16.0 KiB
- resources/migration-report.md16.3 KiB
- resources/notebook-activity-migration.md21.3 KiB
- resources/pipeline-assessment.md35.3 KiB
- resources/pipeline-gotchas.md16.3 KiB
- resources/pipeline-orchestrator.md44.7 KiB
- resources/validation-testing.md19.7 KiB
resources/linked-service-to-connection.md
Linked Services → Fabric Connections
Reference for mapping Synapse Analytics linked service types to Fabric Connection types for use in pipeline activities.
Scope: This file covers pipeline-oriented connection migration. For notebook connectivity (ADLS shortcuts,
notebookutils.credentials), see the synapse-migration skill's connectivity-migration.md.
Decision Guide
| Synapse Linked Service Type | Fabric Connection Type | Notes |
|---|---|---|
| Azure Data Lake Storage Gen2 | AzureDataLakeStorage | Most common — used by Copy, Lookup, GetMetadata, Delete |
| Azure Blob Storage | AzureBlobStorage | Blob-based sources and sinks |
| Azure SQL Database | AzureSqlDatabase | SQL source/sink in Copy; Script, Lookup |
| Azure SQL Managed Instance | SqlServerDatabase | MI connection type |
| Azure Synapse Analytics (Dedicated SQL) | AzureSqlDatabase or direct Fabric Warehouse ref | Post-migration, the pool becomes a Fabric Warehouse |
| Azure Database for PostgreSQL | PostgreSqlDatabase | |
| Azure Database for MySQL | MySqlDatabase | |
| Azure Cosmos DB (SQL API) | CosmosDb | |
| Azure Event Hubs | AzureEventHubs | Pipeline event-based activities |
| Azure Service Bus | AzureServiceBus | |
| REST / HTTP | RestService or ODataRest | Generic REST calls; also covered by WebActivity (no connection) |
| Key Vault | Not needed as a connection | Pipeline options: (1) WebActivity with MSI to call Key Vault REST API, (2) pipeline parameter typed as SecureString, or (3) store non-secret config in a Variable Library |
| File System | FileServer | On-premises; requires on-premises data gateway |
| SQL Server (on-premises) | SqlServerDatabase | On-premises; requires on-premises data gateway |
| Oracle | Oracle | On-premises or cloud; gateway may be required |
| SAP (any) | ⚠️ Check Fabric connector support | Many SAP connectors require gateway |
| Teradata | Teradata | Requires on-premises data gateway |
| Amazon S3 | AmazonS3 | |
| Google Cloud Storage | GoogleCloudStorage | |
| FTP / SFTP | Ftp / Sftp | |
| SharePoint | SharePointOnlineList | |
| Dynamics 365 | Dynamics | |
| Salesforce | Salesforce |
For Self-Hosted Integration Runtime (SHIR) backed linked services: see pipeline-gotchas.md § PG5 — you must configure an on-premises data gateway in Fabric.
How Fabric Connections Work in Pipelines
In Fabric Data Factory, connections are workspace-level resources. A pipeline activity references a connection by name via a LinkedServiceReference set on activity.linkedService — a root-level activity property that is a sibling of typeProperties, not nested inside source/sink/dataset. (For cross-system Copy activities, the second connection is embedded under typeProperties.sink.linkedService; see dataset-inlining.md and activity-mapping.md.) Connection display names in Fabric and linked service names in Synapse are independent values — but if you create the Fabric connection using the same display name as the Synapse linked service, the referenceName fields in your migrated pipeline JSON will resolve as-is with no remapping needed.
If you intentionally use different names (e.g. environment-prefixed Fabric connections like
ADLS_Production_Connection), you must maintain a Synapse-name → Fabric-name mapping and rewrite eachreferenceNameduring migration. See the Name-Matching Strategy below.
Name-Matching Strategy
The simplest migration approach is to create Fabric connections with the same display name as the Synapse linked service. This means the referenceName fields in your pipeline activity JSON need no changes after inlining datasets.
If names differ, you must maintain a mapping table:
{
"AzureDataLakeStorage1": "ADLS_Production_Connection",
"AzureSqlDB_Sales": "SQL_Sales_Connection"
}Creating Fabric Connections via API
List Existing Connections
FABRIC_TOKEN="<fabric-token>"
az rest --method GET \
--headers "Authorization=Bearer ${FABRIC_TOKEN}" \
--url "https://api.fabric.microsoft.com/v1/connections" \
--query "value[].{name:displayName, type:connectionDetails.type, id:id}" -o tableCreate a Connection
The connection creation API is:
POST https://api.fabric.microsoft.com/v1/connectionsConnection creation requires connectivityType, displayName, connectionDetails (with type, creationMethod, and parameters), and credentialDetails (with credentials nested inside). Connector identity comes from connectionDetails.type + connectionDetails.creationMethod — there is no top-level connectorId field. See the Create Connection REST API reference and use ListSupportedConnectionTypes to discover the exact type / creationMethod / parameter names for each connector.
Note: As of mid-2025, connection creation via API requires interactive OAuth for some connector types. For fully automated creation, use the Fabric portal and note the resulting connection name for use in pipeline JSON.
Example: Azure Data Lake Storage Gen2
az rest --method POST \
--headers "Authorization=Bearer ${FABRIC_TOKEN}" "Content-Type=application/json" \
--url "https://api.fabric.microsoft.com/v1/connections" \
--body '{
"connectivityType": "ShareableCloud",
"displayName": "AzureDataLakeStorage1",
"connectionDetails": {
"type": "AzureDataLakeStorage",
"creationMethod": "AzureDataLakeStorage",
"parameters": [
{
"dataType": "Text",
"name": "server",
"value": "https://<storageaccount>.dfs.core.windows.net"
}
]
},
"credentialDetails": {
"singleSignOnType": "None",
"connectionEncryption": "NotEncrypted",
"skipTestConnection": false,
"credentials": {
"credentialType": "WorkspaceIdentity"
}
}
}'Payload shape (critical): Per the Create Connection REST API, the body has no top-level
connectorIdfield. Connector identity comes fromconnectionDetails.type+connectionDetails.creationMethod. Credentials live undercredentialDetails.credentials(notcredentialDetails.singleCredential). The exactparametersnames (server,database,path, etc.) vary per connector — discover them via ListSupportedConnectionTypes before constructing the body.
Example: Azure SQL Database
az rest --method POST \
--headers "Authorization=Bearer ${FABRIC_TOKEN}" "Content-Type=application/json" \
--url "https://api.fabric.microsoft.com/v1/connections" \
--body '{
"connectivityType": "ShareableCloud",
"displayName": "AzureSqlDB_Sales",
"connectionDetails": {
"type": "AzureSqlDatabase",
"creationMethod": "AzureSqlDatabase",
"parameters": [
{
"dataType": "Text",
"name": "server",
"value": "<server>.database.windows.net"
},
{
"dataType": "Text",
"name": "database",
"value": "<database-name>"
}
]
},
"credentialDetails": {
"singleSignOnType": "None",
"connectionEncryption": "NotEncrypted",
"skipTestConnection": false,
"credentials": {
"credentialType": "WorkspaceIdentity"
}
}
}'For ServicePrincipal auth, replace the
credentialsblock undercredentialDetailswith{"credentialType": "ServicePrincipal", "tenantId": "...", "servicePrincipalClientId": "...", "servicePrincipalSecret": "..."}and supply via--body @body.json(see the security note below — never passservicePrincipalSecretinline).
Security note: Never pass
servicePrincipalSecret(or any secret credential value) as a literal string in a shell command — it will appear in shell history and process logs. The credential lives atcredentialDetails.credentials.servicePrincipalSecretin the request body. Prefer one of:
WorkspaceIdentity (managed identity) — set
credentialDetails.credentials.credentialTypeto"WorkspaceIdentity"and omit secret fields entirely. This is the recommended approach when the Fabric workspace has a managed identity assigned.File redirection (recommended for service-principal flows): write the JSON body to a temp file with restricted permissions and pass
--body @body.json. The secret never appears on the command line or inpsoutput.Linux/macOS (
chmod 600for owner-only access):printf '{"credentialDetails":{"singleSignOnType":"None","connectionEncryption":"NotEncrypted","skipTestConnection":false,"credentials":{"credentialType":"ServicePrincipal","servicePrincipalClientId":"...","servicePrincipalSecret":"%s","tenantId":"..."}}}' "$MY_SP_SECRET" > /tmp/conn_body.json chmod 600 /tmp/conn_body.json az rest --method POST --url "..." --body @/tmp/conn_body.json rm /tmp/conn_body.jsonWindows PowerShell (
icaclsto restrict the ACL to the current user, then delete; uses$env:TEMPso the path is portable across user profiles):$body = "{`"credentialDetails`":{`"singleSignOnType`":`"None`",`"connectionEncryption`":`"NotEncrypted`",`"skipTestConnection`":false,`"credentials`":{`"credentialType`":`"ServicePrincipal`",`"servicePrincipalClientId`":`"...`",`"servicePrincipalSecret`":`"$env:MY_SP_SECRET`",`"tenantId`":`"...`"}}}" $tmp = Join-Path $env:TEMP "conn_body.json" Set-Content -Path $tmp -Value $body -Encoding UTF8 -NoNewline icacls $tmp /inheritance:r /grant:r "$($env:USERNAME):(R,W)" | Out-Null az rest --method POST --url "..." --body "@$tmp" Remove-Item $tmp -ForceEnvironment variable (requires double-quoted JSON): if you prefer an inline command, use double-quotes around the JSON body so the shell expands
$MY_SP_SECRET; single-quoted strings silently embed the literal text$MY_SP_SECRETinstead of the value:az rest --method POST --url "..." \ --body "{\"credentialDetails\":{\"singleSignOnType\":\"None\",\"connectionEncryption\":\"NotEncrypted\",\"skipTestConnection\":false,\"credentials\":{\"credentialType\":\"ServicePrincipal\",\"servicePrincipalClientId\":\"...\",\"servicePrincipalSecret\":\"$MY_SP_SECRET\",\"tenantId\":\"...\"}}}"Ensure
MY_SP_SECRETis set only in the current session and not exported to child processes (exportis optional; avoid writing it to.bashrc/.profile).
Credential Type Mapping
| Synapse Auth Method | Fabric Credential Type |
|---|---|
| Managed Identity | WorkspaceIdentity |
| Service Principal (client secret) | ServicePrincipal |
| Service Principal (certificate) | ServicePrincipalCertificate |
| Account Key (storage) | Key |
| SQL Authentication (username/password) | Basic |
| OAuth2 | OAuth2 |
| Anonymous | Anonymous |
Prefer
WorkspaceIdentityover service principal or key-based credentials where possible — it eliminates secret rotation and aligns with Fabric's identity model.
Extracting Linked Service Configuration from Synapse
import requests, json
SYNAPSE_TOKEN = "<synapse-data-plane-token>"
SYNAPSE_ENDPOINT = "https://myworkspace.dev.azuresynapse.net"
headers = {"Authorization": f"Bearer {SYNAPSE_TOKEN}"}
def get_all_linked_services():
url = f"{SYNAPSE_ENDPOINT}/linkedservices?api-version=2020-12-01"
items = []
while url:
r = requests.get(url, headers=headers)
r.raise_for_status()
data = r.json()
items.extend(data.get("value", []))
url = data.get("nextLink")
return items
linked_services = get_all_linked_services()
for ls in linked_services:
name = ls["name"]
ls_type = ls["properties"]["type"]
connect_via = ls["properties"].get("connectVia", {}).get("referenceName", "AutoResolveIntegrationRuntime")
print(f" {name}: {ls_type} (via {connect_via})")Integration Runtime (IR) → Gateway Mapping
| Synapse IR Type | Fabric Equivalent |
|---|---|
AutoResolveIntegrationRuntime | Cloud / built-in (no action needed) |
ManagedIntegrationRuntime | Fabric-managed cloud compute (no action needed) |
Self-Hosted IR (IntegrationRuntimeReference) | On-premises data gateway — must be installed and registered in Fabric |
| Azure Integration Runtime (specific region) | Fabric uses regional compute automatically (no explicit IR selection) |
SHIR → Gateway: The Fabric portal path is: Settings → Manage connections and gateways → On-premises data gateways. Install the on-premises data gateway and register it before creating SHIR-backed connections in Fabric. See pipeline-gotchas.md § PG5 for the full procedure.
Build Linked Service → Connection Map (Script)
Convention note (display name vs GUID): This skill standardizes on the connection display name in pipeline activity
linkedService.referenceNameblocks. The canonical Copy-activity alternative is to reference the connection GUID viaexternalReferences.connectionin the activity'stypeProperties. Both forms are accepted by the Fabric pipeline runtime; the display-name form is preferred here because (a) it round-trips cleanly throughget_connection_id_map()without an extra GUID-resolution step at author time and (b) it keeps the generated pipeline JSON diff-readable when a connection is recreated with the same name but a new GUID. Both forms have been hand-validated against a live Fabric workspace as of June 2026. If you have a strict policy requiring GUID references, swap thereferenceNamefor anexternalReferences.connectionentry per the Fabric Copy activity reference — the rest of the migration flow is unchanged.
After creating all Fabric connections, build the mapping file used by dataset inlining and activity transformation:
import requests, json
from urllib.parse import quote
FABRIC_TOKEN = "<fabric-token>"
headers = {"Authorization": f"Bearer {FABRIC_TOKEN}"}
def get_connection_id_map():
"""Return {connectionDisplayName: connectionId} for API operations (e.g. verifying a connection exists).
NOTE: Pipeline activity JSON uses the connection display name in referenceName — NOT the GUID.
Use the keys of this map (display names) when writing pipeline JSON.
Use the values (GUIDs) only for Fabric API calls that require a connection ID.
"""
url = "https://api.fabric.microsoft.com/v1/connections"
connections = {}
while url:
r = requests.get(url, headers=headers)
r.raise_for_status()
data = r.json()
for c in data.get("value", []):
connections[c["displayName"]] = c["id"]
cont = data.get("continuationToken")
# Fabric continuation tokens are base64-like and routinely contain
# '+', '/', '=' which must be percent-encoded; raw concatenation
# breaks pagination on workspaces with > 1 page of connections.
url = (
f"https://api.fabric.microsoft.com/v1/connections"
f"?continuationToken={quote(cont, safe='')}"
) if cont else None
return connections
connection_id_map = get_connection_id_map()
print(json.dumps(connection_id_map, indent=2))
# {
# "AzureDataLakeStorage1": "aaaa-...", # key = display name used in pipeline referenceName
# "AzureSqlDB_Sales": "bbbb-..." # value = GUID used in API calls only
# }Save this output as connection_map.json for use in Phase 3 (dataset inlining) and Phase 4 (activity transformation).
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
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Attribution and licence
- Published by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/skills-for-fabric · skills/pipeline-migration · commit f8fac11
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- microsoft/skills-for-fabric
AutoGineer is not affiliated with or endorsed by Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download pipeline-migration.zip