Synapse Migration
MicrosoftOfficialPublished by Microsoft
- Skill
- Workflow
- Software development
- MIT
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The synapse-migration skill provides a structured, phased workflow for transitioning Synapse Analytics workspaces to Microsoft Fabric. It covers the migration of Spark items, Lake Databases, Linked Services, and Dedicated SQL Pool schema and stored procedures. The skill emphasizes a dependency-ordered approach, requiring gap assessment and explicit approval before conversion. It distinguishes between migrating to a Fabric Lakehouse (schema and code only, no data movement) and a Fabric Warehouse, while providing specific routing for dependent pipeline callers.
What it does
- Discovers and classifies Synapse workspace artifacts.
- Converts Dedicated SQL Pool schema and stored procedures to Spark SQL notebooks or Warehouse objects.
- Migrates Spark items, including notebooks and Spark Job Definitions, to Fabric equivalents.
- Maps Linked Services to Fabric Data Connections or OneLake Shortcuts.
- Manages the migration of approved dependent pipeline callers.
- Validates persisted definitions and artifacts against established contracts.
When to use it
- When migrating a full Synapse workspace to Microsoft Fabric.
- When converting Dedicated SQL Pool schema and procedures to a Lakehouse or Warehouse.
- When porting Spark pools, notebooks, or Spark Job Definitions to Fabric.
- When replacing Synapse Linked Services with Fabric-native connectivity.
Advantages
- Ensures dependency-ordered migration to maintain system integrity.
- Provides clear routing for different workload types (Lakehouse vs. Warehouse).
- Enforces strict validation and approval gates for behavior-changing decisions.
- Supports incremental migration rather than high-risk big-bang cutovers.
- Standardizes the conversion of T-SQL procedures to executable Spark SQL notebooks.
Usage examples
- “Migrate this Dedicated SQL Pool DACPAC to a Fabric Lakehouse and convert the procedures.”
- The agent will assess gaps, obtain approval for procedure-to-notebook mappings, create a migration manifest, convert schema/code artifacts, and validate the results.
- “Migrate this Dedicated SQL Pool to Fabric Warehouse.”
- The agent will assess DDL compatibility, remove unsupported distribution/index declarations, obtain provisioning consent, and prepare for potential data migration.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/synapse-migration/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip synapse-migration.zip -d .agents/skills
Documentation by Microsoft
Telemetry — MANDATORY. Every
api.fabric.microsoft.comcall must carryx-ms-fabric-skill: synapse-migration(az rest:--headers "x-ms-fabric-skill=synapse-migration"), including every LRO poll,fabric_lroand retry. Snippets omit it — add it anyway.
OFFLINE LAKEHOUSE ARTIFACT FAST PATH — DECIDE FIRST. For a no-live-call request with complete supplied inputs and contracts, load only the fast path; do not load
migration-planning-reference.md,dedicated-pool-conversion.md, or implementation scripts. Use one generator for artifacts and final-byte hashes, then one verifier. Do not inspect generated files or run post-pass spot checks. For every optional non-null source default, setmissingValueBehaviortoUseSourceDefaultand restore that default before validation. Do not use this path for a Warehouse target; incomplete and large-procedure requests use their own routes.
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.
Treat a source Dedicated SQL Pool as read-only. Do not run source DDL, DML, stored procedures, or create sample objects.
Dedicated Pool-to-Lakehouse data movement is out of scope. Migrate schema and executable code artifacts only; do not copy source rows or run row-level/business-result equivalence queries. The separate Warehouse route may move data only from a separately approved restored export copy under its own consent gate and restored-source contract.
For Dedicated Pool-to-Lakehouse requests, complete gap assessment, explicit mapping approval, manifest creation, conversion, deployment, and validation in order. Read dedicated-pool-to-lakehouse.md once as the router, then load only the current phase reference.
Stored-procedure
1:1,N:1, andN:Nmappings never apply to views. Views remain schema objects; procedures become traceable Spark SQL notebooks with executable%%sqltransformation cells.Dependent ADF/Synapse callers are conditional scope, not automatic scope. Discover them during assessment, require a separate complete-closure approval, and migrate them only after notebook readiness. Route standalone pipeline requests to
pipeline-migration.Before executing a specialized Dedicated Pool workflow, read the matching contract in dedicated-pool-execution-contracts.md. Its validation, hashing, request-body, resume, and completion-language requirements are mandatory.
Keep Lakehouse and Warehouse paths separate. If the target is unclear, ask before loading path-specific resources. Lakehouse conversion never moves source rows; Warehouse data migration requires its own explicit consent gate and restored-source contract.
For a Fabric Warehouse target, explicitly state that the complete
DISTRIBUTIONandCLUSTERED COLUMNSTORE INDEXdeclarations are removed because Fabric manages distribution, storage, and indexing; a bare mention of either source clause is insufficient.Run setup DDL and CETAS only against the separately approved restored export copy after proving it is not the original production source.
Synapse Analytics to Microsoft Fabric Migration
Core Workflow
Discover the Synapse workspace and classify every source artifact.
Choose targets using workload-routing.md.
Assess gaps before conversion, including runtime, library, connectivity, T-SQL, security, and capacity constraints.
Obtain approval for behavior-changing decisions, target placement, and every stored-procedure-to-notebook mapping.
Create or update
migration-manifest.jsonand persist approval, per-object status, hashes, and checkpoints atomically.Convert and deploy in dependency order, loading only the current phase resource.
Validate persisted definitions and artifacts without executing generated notebooks or pipelines unless a separately approved workflow explicitly requires execution.
Report completed, blocked, skipped, and pending objects without exposing credentials or sensitive values.
For full-workspace orchestration, read migration-orchestrator.md. For a Dedicated Pool-to-Lakehouse migration, use dedicated-pool-to-lakehouse.md as the phase router. For a Warehouse target, load only the matching dw-* resource.
Scope Routing
| Request | Action | Load |
|---|---|---|
| Full Synapse workspace migration | Run phased discovery and migration | migration-orchestrator.md |
| Dedicated SQL Pool schema/code to Lakehouse | Run the strict assessment-to-validation workflow. For guidance-only notebook publication, explicitly state: "The stored procedures were converted from T-SQL to Spark SQL before publication." | dedicated-pool-to-lakehouse.md |
| Guidance-only Dedicated Pool incremental deployment hardening | Answer directly from the focused checklist; do not search scripts or load phase resources. State: "For columns with special characters, enable Delta columnMapping selectively and only with approval." | dedicated-pool-execution-contracts.md |
| Large or complex stored procedure | For a complete offline contract, read only the audit resource once, use one run-local generator and one verifier, do not inspect implementation scripts or generated outputs, and stop after successful verification | dedicated-pool-large-procedure-audit.md |
| Spark pool | Convert configuration and libraries to a Fabric Environment | spark-pool-migration.md |
| Lake Database or HMS | Create or bind the target Lakehouse | lake-database-migration.md or external-hms-migration.md |
| Notebook or Spark Job Definition | Port code, bindings, parameters, and runtime settings | spark-item-migration.md |
| Linked Service | Choose a Fabric Data Connection for external services or a OneLake Shortcut for ADLS Gen2/Blob | connectivity-migration.md |
| Approved dependent procedure callers | Run the internal closure-preserving sub-flow after notebook readback | dedicated-pool-dependent-pipelines.md |
| Standalone pipeline migration | Delegate | pipeline-migration |
| Dedicated SQL Pool to Fabric Warehouse | Run the source extraction, DDL compatibility, approval, optional data, security, and validation route | dw-source-and-extraction.md, then the matching dw-* phase resource |
| Standalone Fabric Warehouse administration | Delegate | sqldw-cli |
| Synapse Link | Use Fabric Mirroring; not covered here | — |
Always report the Lake Database/HMS phase. If none is discovered, mark it NotApplicable (none discovered) while retaining the required target Lakehouse binding.
Load References On Demand
Do not preload all files. Load only the references needed for the current phase:
| Need | Reference |
|---|---|
| Routing, phase order, API audiences, quick examples, troubleshooting, or post-migration handoff | workload-routing.md |
| Dedicated Pool execution variants and response contracts | dedicated-pool-execution-contracts.md |
| Dedicated Pool discovery | dedicated-pool-discovery.md |
| Gap assessment and mapping approval | dedicated-pool-gap-assessment.md |
| Procedure conversion and notebook shape | dedicated-pool-conversion.md |
| Schema/notebook deployment | dedicated-pool-deployment.md |
| Dedicated Pool validation | dedicated-pool-validation.md |
| Runtime/library compatibility | feature-parity.md and library-compatibility.md |
mssparkutils and connector refactoring | utility-api-mapping.md, connector-refactoring.md, and code-patterns.md |
| Capacity planning | capacity-sizing.md |
| Dedicated Pool-to-Warehouse source discovery and extraction | dw-source-and-extraction.md |
| Warehouse DDL compatibility and deployment | dw-ddl-compatibility.md |
| Separately approved Warehouse data migration | dw-data-migration.md |
| Warehouse security and validation | dw-security-validation.md |
| Validation, reporting, and production readiness | validation-testing.md, migration-report.md, and security-governance.md |
Use COMMON-CLI.md only for shared authentication and az rest mechanics not already covered by the phase resource. Use COMMON-CORE.md only for shared Fabric REST patterns.
Must
Preserve every stored-procedure input contract, source default, source decision, and approved target mapping.
Block conversion until gap dispositions, notebook names, dependency grouping, and target workspace placement are explicitly approved.
Use SqlPackage/DMVs for source discovery, Fabric REST for item management, and Fabric Livy statements for Lakehouse schema and Delta execution.
Run the maintained validators required by the selected execution contract; never replace them with ad hoc JSON or cell-shape checks.
Choose the Lakehouse or Warehouse target before loading implementation resources; never apply Warehouse data-movement rules to Lakehouse artifact conversion.
Before persisting any dependent-pipeline source definition, recursively inspect it for secret-bearing or uncertain properties; block the complete selected closure without writing the artifact or mutating a target when any are found.
In every dependent-pipeline response, including guidance-only and pre-approval explanations, state: "Use a
TridentNotebookactivity with exact target identitiestypeProperties.notebookIdandtypeProperties.workspaceId, and pass inputs throughtypeProperties.notebookParameters." Then state: "After deployment, read back each pipeline withPOST /v1/workspaces/{workspaceId}/items/{dataPipelineId}/getDefinitionand validate its canonical hash and structural bindings."For every Linked Service response, first state both replacement classes: Fabric Data Connections for external databases/services and OneLake Shortcuts for ADLS Gen2/Blob storage; then identify which class applies.
Replace
mssparkutilswithnotebookutils, Linked Services with the correct Fabric connection class, andspark.read.synapsesql()with a supported OneLake or JDBC pattern.Externalize workspace and item IDs through parameters or Variable Libraries.
Keep phase status concise, emit bounded heartbeats for long operations, and persist per-object evidence in the manifest.
Prefer
OneLake Shortcuts over copying data.
Fabric Environments for reproducible libraries and Spark settings.
Incremental, dependency-ordered migration over big-bang cutover.
Parameterized notebooks and Variable Libraries for environment promotion.
Lakehouse SQL Endpoint for compatible Serverless SQL Pool read workloads.
Avoid
Do not execute generated notebooks or pipelines as part of artifact migration.
Do not broaden a selected dependent-pipeline closure or route that internal sub-flow to
pipeline-migration.Do not use
sqlcmdagainst the target Fabric Warehouse; use the registered SQL endpoint tooling required by the Warehouse resource.Do not preserve Synapse distribution/storage hints, PolyBase DDL, Linked Service connection strings, or pool-level library installation patterns verbatim.
Do not use target notebooks to orchestrate the migration itself.
Do not hardcode workspace IDs, item IDs, credentials, connection strings, or environment-specific paths.
Examples
Prompt: "Migrate this Dedicated SQL Pool DACPAC to a Fabric Lakehouse and convert the procedures."
Response behavior: Assess gaps first, present and obtain approval for the complete procedure-to-notebook mapping and workspace placement, create the manifest, convert approved schema/code artifacts without moving source rows, validate persisted definitions, and report the resolved Lakehouse and artifact evidence.
Prompt: "Migrate this ADF pipeline to Fabric."
Response behavior: Route to pipeline-migration. Keep it here only when the pipeline is an explicitly approved dependent caller discovered inside an active Dedicated Pool-to-Lakehouse migration.
Prompt: "Migrate this Dedicated SQL Pool to Fabric Warehouse."
Response behavior: Keep this inside synapse-migration, assess DDL compatibility, remove unsupported distribution and columnstore declarations, obtain provisioning consent, and ask separately before any restored-source data migration.
For code transformations and edge cases, load workload-routing.md and the phase-specific resource rather than expanding the main instructions.
Files
- ATTRIBUTION.mdAdded by AutoGineer879 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md14.3 KiB
- apm.yml597 B
- references/dedicated-pool-execution-contracts.md14.5 KiB
- references/workload-routing.md6.0 KiB
- resources/capacity-sizing.md4.1 KiB
- resources/code-patterns.md8.4 KiB
- resources/connectivity-migration.md6.4 KiB
- resources/connector-refactoring.md13.8 KiB
- resources/dedicated-pool-conversion.md39.2 KiB
- resources/dedicated-pool-dependent-pipelines.md23.3 KiB
- resources/dedicated-pool-deployment.md20.0 KiB
- resources/dedicated-pool-discovery.md17.8 KiB
- resources/dedicated-pool-gap-assessment.md17.4 KiB
- resources/dedicated-pool-large-procedure-audit.md24.5 KiB
- resources/dedicated-pool-to-lakehouse.md17.9 KiB
- resources/dedicated-pool-validation.md17.2 KiB
- resources/dw-data-migration.md13.7 KiB
- resources/dw-ddl-compatibility.md9.4 KiB
- resources/dw-security-validation.md15.6 KiB
- resources/dw-source-and-extraction.md8.0 KiB
- resources/external-hms-migration.md20.2 KiB
- resources/feature-parity.md5.4 KiB
- resources/lake-database-migration.md34.8 KiB
- resources/library-compatibility.md7.2 KiB
- resources/migration-gotchas.md16.1 KiB
- resources/migration-orchestrator.md63.0 KiB
- resources/migration-planning-reference.md16.3 KiB
- resources/migration-report.md16.9 KiB
- resources/security-governance.md47.4 KiB
- resources/spark-item-migration.md19.2 KiB
- resources/spark-pool-migration.md16.3 KiB
- resources/utility-api-mapping.md5.4 KiB
- resources/validation-testing.md14.5 KiB
- scripts/Invoke-DedicatedPoolTool.ps1Script941 B
- scripts/dedicated-pool-tool/DedicatedPoolMessageSanitizer.csScript2.1 KiB
- scripts/dedicated-pool-tool/DedicatedPoolTool.csproj346 B
- scripts/dedicated-pool-tool/Program.csScript31.4 KiB
- scripts/dedicated_pool_runtime.pyScript116.9 KiB
- scripts/validate_dedicated_pool_spark.pyScript24.8 KiB
resources/dw-ddl-compatibility.md
DDL Compatibility and Conversion
Load this resource for Steps 3-4 only.
Classification
Auto-fixed: safe mechanical conversion.
Needs review: add
-- MIGRATION REVIEW:to the generated SQL and report it.Blocker: no safe conversion; do not deploy that object.
Table conversion
Remove
DISTRIBUTION = HASH(...),ROUND_ROBIN, andREPLICATE; Fabric manages distribution.Remove clustered columnstore, clustered, and nonclustered index definitions.
Remove dedicated-pool partition clauses and create one regular Fabric table. If data migration is separately approved, export the selected source rows across every partition; otherwise preserve only the schema. Warn that partition boundaries, switching/maintenance operations, and source partition-based performance behavior are not preserved.
Convert every computed column to a regular stored target column. Report the source table, column, expression, target type, and loss of automatic recomputation. If data migration and preservation of the computed value are separately approved, include its evaluated source value in the approved export projection; otherwise preserve only the stored target-column schema and do not read or export source row values. Ask whether the user wants a separate view that reproduces the original computed expression; generate that view only after validating the expression against Fabric T-SQL and receiving approval.
Create all tables without inline source primary-key, unique-key, or foreign-key constraints. After every referenced table exists, emit separate
ALTER TABLE ... ADD CONSTRAINTstatements: primary and unique keys asNONCLUSTERED NOT ENFORCED, and foreign keys asNOT ENFORCED. Order these statements by the foreign-key dependency graph; for a cycle, create every table first and then apply the cycle's constraints. Record and block any constraint whose referenced table or columns did not deploy.Do not deploy DEFAULT or CHECK constraints: the current Fabric Warehouse table-constraint surface supports only primary, foreign, and unique keys in their documented unenforced forms, and explicitly does not support DEFAULT constraints. Record every source DEFAULT/CHECK definition. If equivalent behavior requires application, pipeline, or procedure logic, classify that redesign as Needs review; otherwise classify the missing invariant as a Blocker for dependent writes.
Map unsupported persisted data types:
| Source | Fabric | Classification |
|---|---|---|
money | decimal(19,4) | Auto-fixed |
smallmoney | decimal(10,4) | Auto-fixed |
datetime, smalldatetime | datetime2(6) | Auto-fixed |
tinyint | smallint | Auto-fixed |
binary(n) | varbinary(n) | Auto-fixed |
datetimeoffset | datetime2(6) | Needs review: offset lost |
nchar(n), nvarchar(n) | char(n), varchar(n) | Needs review: require a supported UTF-8 collation on the target Fabric Warehouse and size the target column from observed and worst-case UTF-8 byte requirements; ASCII is 1 byte and non-ASCII Unicode scalar values can require up to 4 bytes; widen with approval |
nvarchar(max) | varchar(max) | Needs review: require a supported UTF-8 target collation and validate encoded byte size against the current 16 MB limit |
For any unsupported source type not listed above (for example geography, geometry, XML, hierarchyid, CLR/user-defined types, or another unsupported persisted type), propose documented Fabric alternatives per column and ask the user to approve a mapping. Do not default everything to varchar and do not silently drop columns. If no mapping is approved, block the table and its dependents and record the source type, proposed alternatives, and decision.
Do not convert nchar or nvarchar until the target Warehouse has an explicitly selected supported UTF-8 collation and the mapped width is byte-safe for the approved data domain. Measure representative encoded values, calculate the worst-case UTF-8 requirement, document truncation risk, and obtain approval for widening. Block the affected table when a safe supported width or collation cannot be established.
Fabric IDENTITY is preview, supports only bigint IDENTITY, and does not support custom seed/increment values. SET IDENTITY_INSERT supports explicit value insertion. Mark identity conversion as Needs review and require approval before preserving source keys through explicit insertion; validate key uniqueness, range, dependent foreign-key relationships, reseeding, and a subsequent generated value in an approved test context.
Code object conversion
Remove distribution clauses, index DDL, and
SET RESULT_SET_CACHING.Remove workload-management definitions and resource-class references. Keep supported
OPTION (LABEL=...)usage.Do not rewrite
NEXT VALUE FORor other sequence references. Sequence objects are excluded from migration; code objects retaining sequence references proceed through normal target compilation validation and fail there if unsupported or unresolved.For every cross-database or linked-server reference, ask the user to map the source server/database/object to a Fabric-accessible Warehouse, Lakehouse SQL endpoint, shortcut-backed table, or other approved target. Block the referencing object and its dependents until all mappings are approved. Rewrite only explicit, unambiguous references, then show the before/after mapping and validate target compilation. Never guess mappings or silently remove remote joins/calls.
Dedicated SQL pools do not support DML or DDL triggers, so none are expected in this migration path. If discovery unexpectedly returns a trigger, stop and verify that the selected source is actually a dedicated SQL pool; report the trigger as a source-scope blocker and do not generate a target trigger definition.
For each source external table, ask whether to keep the data in place through an approved OneLake shortcut/Lakehouse mapping or materialize it into a regular Fabric Warehouse table through a user-approved copy method. Remove Synapse external data source/file format DDL only after the replacement is selected. Block dependent objects until the shortcut target or materialized table exists and its schema is validated.
Convert materialized views to regular views automatically. Remove materialized-view-only syntax, preserve the SELECT definition, and add a prominent warning that physical materialization, refresh behavior, storage, and source performance characteristics are not preserved. Record every conversion in
migration-report.md.Block multi-statement TVFs and non-inlineable scalar UDFs pending redesign. Propagate the blocker to views, procedures, functions, RLS predicates, or other objects that depend on the blocked function. Continue converting independent objects; never generate a placeholder implementation.
For SQL-authenticated users, generate role definitions only; omit user creation, memberships, and direct user grants, and report every omission.
Column-level encryption is unsupported in Fabric Warehouse. Omit the encryption metadata, continue migrating the affected table, and add a prominent non-blocking assessment warning that the target column data will not retain source encryption protection.
DMV conversion
Only auto-replace direct monitoring equivalents, and review column differences:
| Synapse | Fabric |
|---|---|
sys.dm_pdw_exec_requests | sys.dm_exec_requests or queryinsights.exec_requests_history |
sys.dm_pdw_exec_sessions | sys.dm_exec_sessions or queryinsights.exec_sessions_history |
sys.dm_pdw_exec_connections | sys.dm_exec_connections |
Remove distribution and workload-management references that are unnecessary in Fabric. Treat these families as blockers unless manually rewritten:
sys.dm_pdw_request_steps,sys.dm_pdw_sql_requests,sys.dm_pdw_dms_*sys.dm_pdw_wait*,sys.dm_pdw_nodes*,sys.dm_pdw_resource_waits,sys.dm_pdw_errorsPolyBase compute/distributed/DMS/external DMVs
sys.pdw_nodes_*, mapping, loader, and materialized-view catalog families
Use Fabric Query Insights for post-migration history and performance analysis.
Assessment report
Compare source and selected target collations. Report case-sensitivity, UTF-8 byte semantics, string-comparison, uniqueness, and explicit COLLATE risks. Preserve only explicit collations supported by Fabric and flag unsupported clauses for review.
Report source inventory, resolved scope, converted/deployed counts by object type, DEFAULT/CHECK compatibility, collation risks, auto-fixes, review items, blockers, blocked dependency chains, every data-type conversion, security gaps, and DMV compatibility. Require explicit user confirmation before provisioning the Fabric Warehouse.
References
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/synapse-migration · commit f8fac11
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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- microsoft/skills-for-fabric
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