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Pipeline Migration

MicrosoftOfficialPublished by Microsoft

  • Skill
  • Workflow
  • Cloud and DevOps
  • MIT
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From the author

Migrates Synapse Data Factory pipelines to Fabric Data Factory, turning linked services into Fabric connections, inlining datasets into activities, converting global parameters to Variable Libraries, and mapping SynapseNotebook to TridentNotebook. Use for pipeline JSON. For Synapse Spark notebook code use synapse-migration.
— the description by Microsoft

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

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/microsoft/pipeline-migration/download
  2. Unzip 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.com call must carry x-ms-fabric-skill: pipeline-migration (az rest: --headers "x-ms-fabric-skill=pipeline-migration"), including every LRO poll, fabric_lro and retry. Snippets omit it — add it anyway.

CRITICAL NOTES

  1. To find workspace details (including its ID) from a workspace name: list all workspaces, then use JMESPath filtering

  2. 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

  3. Fabric does NOT have a "Dataset" item type — all dataset properties are inlined into activity typeProperties

  4. Linked Services map to Fabric Connections — in pipeline activity JSON, referenceName on the activity's linkedService block uses the Fabric connection display name (not the connection GUID); the connection GUID is used only on Fabric REST API calls

  5. Notebook activities change from SynapseNotebook to TridentNotebook and reference notebooks by GUID, not by name

  6. Synapse global parameters become a Variable Library item in Fabric, referenced as @pipeline().libraryVariables.<name>. Variable Library Number types are not consumable in pipelines — Synapse Float/Double are mapped to String for runtime compatibility

  7. The Validation activity type does not exist in Fabric — it must be rewritten as GetMetadata + IfCondition

  8. Triggers are intentionally excluded from this skill — recreate schedules manually in Fabric after migration

  9. 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 login CLI patterns, authentication recipes, pipeline run/schedule operations

  • ITEM-DEFINITIONS-CORE.md — DataPipeline and VariableLibrary item 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

TopicReference
Pre-Migration Assessment (run first)pipeline-assessment.md
Migration Orchestratorpipeline-orchestrator.md
API-Driven Migration Workflow§ API-Driven Migration Workflow
Activity Type Mappingactivity-mapping.md
Notebook Activity Migration (primary focus)notebook-activity-migration.md
Linked Services → Connectionslinked-service-to-connection.md
Dataset Inliningdataset-inlining.md
Global Parameters → Variable Libraryglobal-parameters-to-variable-library.md
Pipeline Gotchas & Parked Activitiespipeline-gotchas.md
Validation & Testingvalidation-testing.md
Migration Reportmigration-report.md
Context Loading Guide

IMPORTANT — Load only what you need. Do NOT read all resource files upfront.

WhenRead This File
User asks for an assessment, scope, or plan before migratingpipeline-assessment.md
User asks to migrate a full pipeline workspacepipeline-orchestrator.md
User asks about activity type mapping or unsupported activitiesactivity-mapping.md
User has SynapseNotebook activities (most common)notebook-activity-migration.md
User asks about linked services or connectionslinked-service-to-connection.md
User asks about Copy, Lookup, or GetMetadata with datasetsdataset-inlining.md
User has global parameters to convertglobal-parameters-to-variable-library.md
User hits SSIS, SHIR, Databricks, or other blockerspipeline-gotchas.md
Post-migration verificationvalidation-testing.md
Generating a migration summarymigration-report.md

API-Driven Migration Workflow

Authentication
TargetToken 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 tsv to acquire tokens.

Synapse Data-Plane API Reference
OperationEndpoint
List all pipelinesGET https://{ws}.dev.azuresynapse.net/pipelines?api-version=2020-12-01
Get pipeline definitionGET https://{ws}.dev.azuresynapse.net/pipelines/{name}?api-version=2020-12-01
List all datasetsGET https://{ws}.dev.azuresynapse.net/datasets?api-version=2020-12-01
Get dataset definitionGET https://{ws}.dev.azuresynapse.net/datasets/{name}?api-version=2020-12-01
List all linked servicesGET https://{ws}.dev.azuresynapse.net/linkedservices?api-version=2020-12-01
Get linked serviceGET 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
OperationEndpoint
List connectionsGET https://api.fabric.microsoft.com/v1/connections
Create connectionPOST https://api.fabric.microsoft.com/v1/connections
Create pipeline itemPOST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items
Update pipeline definitionPOST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items/{id}/updateDefinition
Get pipeline definitionPOST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items/{id}/getDefinition
Create Variable LibraryPOST https://api.fabric.microsoft.com/v1/workspaces/{wsId}/items (type: VariableLibrary)
List notebooks in workspaceGET https://api.fabric.microsoft.com/v1/workspaces/{wsId}/notebooks

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:

  1. Ask the user: "What is the name of your Synapse workspace?"

  2. Auto-discover subscription ID and resource group via az account show and az synapse workspace show

  3. Run the assessment code inline from the terminal

  4. Print the full report output directly in the chat

When to UseAction
User wants to understand migration scope before committingAsk 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 documentRun assessment, print report in chat
User has already decided to migrateSkip assessment — go straight to Migration Phases below

To also save the report to disk, pass output_path=f"pipeline-assessment-{SYNAPSE_WS}.md" to generate_assessment_report(). The PipelineAssessment objects 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:

  1. Synapse workspace name (reuse from assessment if already run)

  2. Fabric workspace name

  3. Which pipelines to migrate — specific names, or * for all

  4. Optional 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 show

  • Fabric workspace ID via GET /v1/workspaces filtered by display name

  • Notebook GUIDs in Fabric via GET /v1/workspaces/{wsId}/notebooks (required for SynapseNotebook → 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, remove sparkPool/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 SynapseNotebook activity does not exist in the Fabric workspace yet

  • A 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)

PhaseSourceTargetResource
Phase 0Synapse notebooks (referenced by pipeline activities)Fabric Notebookssynapse-migration skill
Phase 1Synapse global parametersFabric Variable Libraryglobal-parameters-to-variable-library.md
Phase 2Synapse linked servicesFabric Connectionslinked-service-to-connection.md
Phase 3Synapse datasetsInlined into activitiesdataset-inlining.md
Phase 4Synapse pipeline activitiesFabric pipeline activitiesactivity-mapping.md + notebook-activity-migration.md
Phase 5Assembled pipeline JSONFabric DataPipeline itempipeline-orchestrator.md
Final—Validationvalidation-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 ActivityFabric EquivalentStatus
SynapseNotebookTridentNotebook✅ Migrated — see notebook-activity-migration.md
CopyCopy✅ Migrated — datasets inlined
LookupLookup✅ Migrated — datasets inlined
GetMetadataGetMetadata✅ Migrated — datasets inlined
ValidationGetMetadata + IfCondition✅ Migrated — split into 2 activities
ForEachForEach✅ Compatible
IfConditionIfCondition✅ Compatible
SwitchSwitch✅ Compatible
UntilUntil✅ Compatible
WaitWait✅ Compatible
FailFail✅ Compatible
SetVariableSetVariable✅ Compatible
AppendVariableAppendVariable✅ Compatible
ExecutePipelineExecutePipeline✅ Compatible — add workspaceId
WebActivityWebActivity✅ Compatible
ScriptScript✅ Compatible — update connection refs
DeleteDelete✅ Migrated — datasets inlined
FilterFilter✅ Compatible
SparkJobDefinition (Synapse SJD)SparkJobDefinition✅ Update GUID refs
HDInsightSparkTridentNotebook or SparkJobDefinition⚠️ Rewrite required
AzureMLBatchExecutionWebActivity⚠️ Rewrite as REST call
AzureFunctionActivityWebActivity⚠️ Rewrite — use function URL + key
DatabricksNotebook⛔ ParkedSee pipeline-gotchas.md
DatabricksSparkJar⛔ ParkedSee pipeline-gotchas.md
DatabricksSparkPython⛔ ParkedSee pipeline-gotchas.md
ExecuteSSISPackage⛔ ParkedSee pipeline-gotchas.md
AzureBatch⛔ ParkedNo Fabric equivalent
Custom⛔ ParkedNo 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/outputs dataset properties must be embedded in each activity

  • Replace @pipeline().globalParameters.<name> with @pipeline().libraryVariables.<name> after creating the Variable Library

  • Replace Validation activities with a GetMetadata + IfCondition pair — Validation does not exist as an activity type in Fabric

  • Remove sparkPool and sessionConfiguration from 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 promotion

  • Parameterized notebookParameters over hardcoded values in TridentNotebook activities — mirrors Synapse parameterized notebook pattern

  • Test 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 TridentNotebook activities — use the GUID from the Fabric workspace notebook list

  • Do 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().globalParameters syntax 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 IDIssueSeverityResolution Summary
PG1NOTEBOOK_GUID_NOT_FOUNDNotebook not yet migrated to Fabric when building TridentNotebook activityHighRun synapse-migration skill first; get GUID from GET /v1/workspaces/{wsId}/notebooks
PG2DATASET_NOT_INLINEDActivity still references a named dataset (not valid in Fabric)HighApply dataset-inlining.md patterns to embed dataset properties into activity source/sink
PG3GLOBAL_PARAM_EXPRESSION@pipeline().globalParameters.<name> expression left in migrated pipelineHighReplace with @pipeline().libraryVariables.<name> after creating Variable Library
PG4VALIDATION_ACTIVITY_UNSUPPORTEDValidation activity type left in pipeline JSONHighRewrite as GetMetadata + IfCondition — see activity-mapping.md
PG5SHIR_CONNECTOR_PARKEDActivity uses a linked service backed by a Self-Hosted Integration RuntimeMediumMust set up on-premises data gateway in Fabric; see pipeline-gotchas.md
PG6SSIS_ACTIVITY_PARKEDExecuteSSISPackage activity cannot be migratedHighParked — no Fabric equivalent; see pipeline-gotchas.md for alternatives
PG7DATABRICKS_ACTIVITY_PARKEDDatabricks activity type has no Fabric native equivalentHighParked — use Databricks REST API via WebActivity as workaround; see pipeline-gotchas.md
PG8SPARKPOOL_REF_ORPHANEDsparkPool / targetBigDataPool reference left in TridentNotebook activityMediumRemove sparkPool and sessionConfiguration blocks; pool config belongs in Fabric Environment
PG9EXECUTE_PIPELINE_NO_WORKSPACEExecutePipeline activity missing workspaceId for referenced pipelineMediumAdd workspaceId to typeProperties; required even for same-workspace child pipelines — omitting it causes runtime failures
PG10LINKED_SERVICE_NO_CONNECTIONLinked service has no matching Fabric ConnectionHighCreate 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:

TaskSkill / Tool
Migrate notebook content (mssparkutils → notebookutils, linked services)synapse-migration skill
Schedule migrated pipelinesCOMMON-CLI.md § Job Scheduling
Monitor pipeline runsFabric workspace → Monitor hub
Build new Fabric pipelinesRefer to ITEM-DEFINITIONS-CORE.md § DataPipeline
Explore migrated Lakehouse data post-pipeline runspark-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.batchDate

Dataset 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

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 TypeFabric Connection TypeNotes
Azure Data Lake Storage Gen2AzureDataLakeStorageMost common — used by Copy, Lookup, GetMetadata, Delete
Azure Blob StorageAzureBlobStorageBlob-based sources and sinks
Azure SQL DatabaseAzureSqlDatabaseSQL source/sink in Copy; Script, Lookup
Azure SQL Managed InstanceSqlServerDatabaseMI connection type
Azure Synapse Analytics (Dedicated SQL)AzureSqlDatabase or direct Fabric Warehouse refPost-migration, the pool becomes a Fabric Warehouse
Azure Database for PostgreSQLPostgreSqlDatabase
Azure Database for MySQLMySqlDatabase
Azure Cosmos DB (SQL API)CosmosDb
Azure Event HubsAzureEventHubsPipeline event-based activities
Azure Service BusAzureServiceBus
REST / HTTPRestService or ODataRestGeneric REST calls; also covered by WebActivity (no connection)
Key VaultNot needed as a connectionPipeline 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 SystemFileServerOn-premises; requires on-premises data gateway
SQL Server (on-premises)SqlServerDatabaseOn-premises; requires on-premises data gateway
OracleOracleOn-premises or cloud; gateway may be required
SAP (any)⚠️ Check Fabric connector supportMany SAP connectors require gateway
TeradataTeradataRequires on-premises data gateway
Amazon S3AmazonS3
Google Cloud StorageGoogleCloudStorage
FTP / SFTPFtp / Sftp
SharePointSharePointOnlineList
Dynamics 365Dynamics
SalesforceSalesforce

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 each referenceName during 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 table
Create a Connection

The connection creation API is:

POST https://api.fabric.microsoft.com/v1/connections

Connection 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 connectorId field. Connector identity comes from connectionDetails.type + connectionDetails.creationMethod. Credentials live under credentialDetails.credentials (not credentialDetails.singleCredential). The exact parameters names (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 credentials block under credentialDetails with {"credentialType": "ServicePrincipal", "tenantId": "...", "servicePrincipalClientId": "...", "servicePrincipalSecret": "..."} and supply via --body @body.json (see the security note below — never pass servicePrincipalSecret inline).

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 at credentialDetails.credentials.servicePrincipalSecret in the request body. Prefer one of:

  • WorkspaceIdentity (managed identity) — set credentialDetails.credentials.credentialType to "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 in ps output.

    Linux/macOS (chmod 600 for 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.json

    Windows PowerShell (icacls to restrict the ACL to the current user, then delete; uses $env:TEMP so 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 -Force
  • Environment 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_SECRET instead 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_SECRET is set only in the current session and not exported to child processes (export is optional; avoid writing it to .bashrc/.profile).


Credential Type Mapping

Synapse Auth MethodFabric Credential Type
Managed IdentityWorkspaceIdentity
Service Principal (client secret)ServicePrincipal
Service Principal (certificate)ServicePrincipalCertificate
Account Key (storage)Key
SQL Authentication (username/password)Basic
OAuth2OAuth2
AnonymousAnonymous

Prefer WorkspaceIdentity over 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 TypeFabric Equivalent
AutoResolveIntegrationRuntimeCloud / built-in (no action needed)
ManagedIntegrationRuntimeFabric-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.referenceName blocks. The canonical Copy-activity alternative is to reference the connection GUID via externalReferences.connection in the activity's typeProperties. Both forms are accepted by the Fabric pipeline runtime; the display-name form is preferred here because (a) it round-trips cleanly through get_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 the referenceName for an externalReferences.connection entry 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

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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
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