Implement Redshift serverless and provisioned migrations with profiling variants, BladeBridge conversion, S3 transfer, and reconciliation.

Migrate Amazon Redshift with Airlift

The Redshift profile covers SQL objects, stored procedures, WLM queues, Spectrum, COPY/UNLOAD, materialized views, scheduled queries, and downstream BI. Select the profiler variant that matches the actual deployment; Airlift records that source detail with the estate evidence.

What Airlift adds to an Amazon Redshift migration

Stage	Databricks tool or project adapter	Airlift responsibility
discover	the matching Lakebridge Profiler variant and Analyzer scan SQL plus exported estate metadata	accept inventory, dependencies, exclusions, deployment variant, source version, and report digests
plan	assessment output informs target architecture	assign owners and dependency-aware waves; preserve WLM, Spectrum, UDF, and human-work decisions
convert	BladeBridge converts supported Redshift SQL	record attempts, tool generations, artifact digests, warnings, and residue lanes
move data	restartable UNLOAD to S3 plus timestamp, sequence, or application delta	track manifests, watermarks, lag, restart checkpoints, target Delta versions, counts, and reconciliation
validate	Lakebridge Reconcile plus SUPER, Spectrum, workload, and business scenarios	admit independent functional, data, and performance evidence against exact snapshots
certify	Airlift evaluates the active readiness profile	mint a signed certificate identifying artifacts, snapshots, evidence, and policy
cut over	project query, schedule, ingestion, and BI connection effectors	freeze scope, enforce approvals, checkpoint, apply once, verify, and retain rollback evidence
modernize	Unity Catalog, Lakeflow, Delta, and Databricks SQL work	keep distribution, layout, and workload redesign separate from baseline parity

This keeps Spectrum paths, IAM mappings, scheduled queries, ingestion manifests, and BI consumers attached to their SQL dependencies instead of reporting migration progress from converted files alone.

Compile the executable migration pack

Create a versioned manifest containing tables and views, Spectrum objects, WLM rules, COPY/UNLOAD jobs, scheduled queries, UDFs, permissions, and consumers. Select the exact provisioned, Multi-AZ, or serverless variant and mark observed hard cases, then run:

fa migration-pack inspect --file redshift-manifest.json
fa migration-pack plan --file redshift-manifest.json --json > redshift-plan.json

The compiler rejects a mismatched variant, validates dependencies, reports missing Redshift hard cases, and routes unsupported behavior explicitly. Its plan requires an S3 manifest plus watermark restart contract, source-specific Experiments suites, Databricks target mappings, and a Runway deployment manifest. See migration-pack commands for registration and certification.

Inspect and generate a plan

fa source inspect redshift
fa source plan aws_redshift --json > .airlift/redshift-plan.json

Profile and analyze

Profiler variants are redshift_serverless, redshift_provisioned, and redshift_provisioned_multi_az:

databricks labs lakebridge configure-database-profiler
databricks labs lakebridge execute-database-profiler \
  --source-tech redshift_provisioned \
  --output-folder ./artifacts/profile

databricks labs lakebridge analyze \
  --source-directory ./source-export \
  --source-tech "Redshift" \
  --report-file ./artifacts/redshift-analysis.xlsx \
  --generate-json true

Inventory WLM rules, Spectrum paths and IAM dependencies, scheduled queries, load/unload manifests, UDFs, late-binding views, and BI connections in addition to SQL files.

Convert

databricks labs lakebridge transpile \
  --source-dialect redshift \
  --input-source ./source-export/sql \
  --output-folder ./artifacts/converted

BladeBridge is the preferred deterministic path. Common residue includes Python UDFs, leader-node-only functions, WLM behavior, Spectrum-specific constructs, late-binding views, and cross-database queries.

Transfer and reconcile

Use restartable UNLOAD manifests to S3 for the snapshot and select a timestamp, sequence, or application delta for catch-up. Preserve source query snapshot, manifest, watermark, and target Delta version.

databricks labs lakebridge configure-reconcile
databricks labs lakebridge auto-configure-recon-tables
databricks labs lakebridge reconcile

Validate SUPER, semi-structured values, decimal/timestamp behavior, Spectrum data, sort/distribution-sensitive queries, and WLM-sensitive performance. Reconcile and performance are separate readiness tracks.

Certify and cut over

Require independent profiles for data parity, semi-structured behavior, Spectrum-backed queries, and accepted performance thresholds. The project effector may switch ingestion, scheduled queries, application endpoints, and BI connections only after Airlift verifies fresh certificates and approvals. Retain the final UNLOAD/catch-up watermark, endpoint observations, and rollback result with the wave.

Modernize after parity

Replace distribution and sort-key assumptions with measured Delta layout and liquid clustering, move ingestion to Lakeflow, manage S3 through Unity Catalog external locations, and retest workload isolation on Databricks SQL warehouses.

Complete developer command sequence

Generate this exact recipe from the installed CLI so the guide and executable surface stay in sync:

fa source recipe redshift
fa source recipe redshift --variant redshift_serverless --json > .airlift/redshift-recipe.json

The App is engagement-aware. Amazon Redshift appears under Active sources only after the source estate is added to an active engagement. The menu is derived from governed engagement scope; installing Airlift does not expose unrelated source pages.

Every remote mutation below requires --host, --org, authenticated workspace identity, and a stable --idempotency-key. JSON request files contain identifiers, artifact references, and opaque credential references—never passwords, tokens, or connection strings. Run fa <resource> <operation> --help for the current schema and exit semantics.

0. Inspect the source contract

fa source inspect redshift --json > .airlift/redshift-profile.json
fa source plan redshift --variant redshift_serverless --json > .airlift/redshift-capability-plan.json

Expected artifacts:

.airlift/redshift-profile.json
.airlift/redshift-capability-plan.json

Open Engagements → active engagement in the App. This stage is visible at /engagements after replacing the placeholder ID with the governed engagement ID.

1. Create governed scope and connection references

fa engagement create --file engagement.json --idempotency-key migration-create-v1
fa estate register --file redshift-estate.json --idempotency-key redshift-estate-v1
fa connection register --file redshift-connection.json --idempotency-key redshift-connection-v1
fa engagement update --file redshift-scope.json --idempotency-key redshift-scope-v1
fa engagement preflight <engagement-id>

Expected artifacts:

Governed engagement
Source estate
Opaque connection binding

Open Engagements → active engagement in the App. This stage is visible at /engagements/<engagement-id> after replacing the placeholder ID with the governed engagement ID.

2. Assess and accept inventory

fa assessment start --file redshift-assessment-start.json --idempotency-key redshift-assessment-start-v1
fa assessment status <assessment-id> --json
fa assessment record --file redshift-assessment-record.json --idempotency-key redshift-assessment-record-v1
fa assessment accept --file redshift-assessment-accept.json --idempotency-key redshift-assessment-accept-v1
fa inventory list --estate-id <estate-id> --json

Expected artifacts:

Assessment report reference
Normalized inventory
Dependency graph

Open Engagements → active engagement in the App. This stage is visible at /engagements/<engagement-id>/sources/redshift after replacing the placeholder ID with the governed engagement ID.

3. Compile the redshift migration pack

fa migration-pack inspect --file redshift-manifest.json
fa migration-pack plan --file redshift-manifest.json --json > generated/redshift-plan.json

Expected artifacts:

Dependency-aware migration pack
Transfer requirements
Validation requirements
Residue lanes

Open Engagements → active engagement in the App. This stage is visible at /engagements/<engagement-id>/artifacts after replacing the placeholder ID with the governed engagement ID.

4. Convert, move, and remediate

fa plan generate --file redshift-migration-plan.json --idempotency-key redshift-plan-v1
fa conversion batch create --file redshift-batch.json --idempotency-key redshift-batch-v1
fa conversion batch start --file conversion-batch-start.json --idempotency-key conversion-start-v1
fa residue list --engagement-id <engagement-id>
fa transfer plan --file redshift-transfer.json --idempotency-key redshift-transfer-v1
fa transfer run <transfer-id> --idempotency-key transfer-run-v1
fa transfer reconcile <transfer-id> --idempotency-key transfer-reconcile-v1

Expected artifacts:

Target artifacts
Residue cases
Transfer checkpoints
Reconciliation evidence

Open Engagements → active engagement in the App. This stage is visible at /engagements/<engagement-id>/runs after replacing the placeholder ID with the governed engagement ID.

5. Validate independently and inspect discrepancies

fa validation run --file redshift-validation.json --idempotency-key redshift-validation-v1
fa validation status <validation-execution-id> --json
fa discrepancy list --engagement-id <engagement-id>
fa artifact list --engagement-id <engagement-id>

Expected artifacts:

Provider run references
Readiness evidence
Discrepancies

Open Engagements → active engagement in the App. This stage is visible at /engagements/<engagement-id>/runs after replacing the placeholder ID with the governed engagement ID.

6. Certify, cut over, and export evidence

fa certificate list --object-id <object-id>
fa cutover status <wave-id> --json
fa evidence list --engagement-id <engagement-id>
fa evidence export --file redshift-evidence-export.json --idempotency-key redshift-evidence-export-v1

Expected artifacts:

Migration certificates
Cutover evidence
Content-digested evidence export

Open Engagements → active engagement in the App. This stage is visible at /assurance after replacing the placeholder ID with the governed engagement ID.

Runway executes releases; Experiments owns validation verdicts; Airlift owns migration readiness and cutover policy.

What developers see in the App

The contextual source workspace shows the accepted estate and the factory stages for this engagement. Artifacts displays immutable references, content digests, media types, and provider lineage. Runs displays assessment, conversion, transfer, validation, and deployment executions without treating a provider's success as an Airlift verdict.

Airlift Amazon Redshift source workspace showing the governed estate and developer command entry point — Amazon Redshift has its own engagement-scoped workspace; unrelated source systems are not shown.
What you are seeing
This public synthetic capture demonstrates Airlift setup and navigation for Amazon Redshift; it is not evidence of a live connection or certified migration.
What to do next
Register the client estate, bind a credential reference, run the Amazon Redshift assessment recipe, and admit the resulting evidence.
Read the developer workflow

These are automated captures from public synthetic engagements. The source workspace is specific to Amazon Redshift; no unrelated source is presented as its migration journey. For sources without an evidence-backed journey, the image demonstrates setup, navigation, and developer entry points only—not a live connection, converted output, or certified migration. No client data, credentials, workspace hostnames, or internal deployment identifiers are embedded in the images.

Amazon Redshift

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