Dms Schema Conversion

DMS Schema Conversion: Setup Wizard Reference

Table of Contents

• Global Constraints

• Phase 1 — Project Name

• Phase 2 — Target Type Selection

• Phase 3 — Source Database

  • 3d — Offline source configuration

• Phase 4 — Network Investigation & Connectivity

• Phase 5 — Create DMS Subnet Group

• Phase 6 — Database Credentials

• Phase 7 — Create Data Providers

• Phase 8 — S3 Bucket

• Phase 9 — IAM Roles

• Phase 10 — Create Instance Profile

• Phase 11 — Transformation Rules (Optional)

• Phase 12 — Create Migration Project & Summary

Global Constraints

Execute commands using available tools from the AWS MCP server when connected — it provides sandboxed execution, audit logging, and observability. When the MCP server is not available, fall back to the AWS CLI or shell as needed.

• You MUST resolve aws_account_id by running aws sts get-caller-identity and extracting the Account field

• You MUST present one phase at a time — do NOT ask for all parameters at once

• You MUST confirm each resource was created successfully before moving to the next phase

• You MUST show a running summary of collected values at the start of each new phase

• You MUST handle ResourceAlreadyExistsFault and similar errors by reusing the existing resource

• You MUST NOT display or log passwords at any point

• You SHOULD suggest sensible defaults based on already-collected information

Phase 1 — Project Name

Goal: Establish a project name prefix used for all resource names.

Ask:

"What would you like to name this migration project? This will be used as a prefix for all created resources (e.g., myproject → myproject-instance-profile, myproject-s3-bucket, etc.)."

Resource Naming Convention — you MUST use these exact names (no variations):

Constraints:

• Resolve aws_account_id by running aws sts get-caller-identity and extracting the Account field

• Ask the customer which AWS region to use. Do NOT attempt to infer it from the STS response. Store as aws_region.

• If region resolution fails, ask the customer to provide it manually

• The project name MUST be between 1 and 25 characters, start with a lowercase letter or number, and contain only lowercase letters, numbers, and hyphens. Validate this before proceeding. If the customer provides uppercase characters, auto-lowercase the name and inform them. (The 25-character limit ensures the derived S3 bucket name <project_name>-sc-bucket-<account_id>-<region> stays within the 63-character S3 bucket name limit even for the longest AWS region names.)

• After the customer provides a name, you MUST check for existing resources that would be created under that prefix. Run all of the following lookups and present a consolidated summary before proceeding:

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  aws dms describe-migration-projects --filters Name=migration-project-identifier,Values=<project_name>-migration-project
  aws dms describe-instance-profiles --filters Name=instance-profile-identifier,Values=<project_name>-instance-profile
  aws dms describe-replication-subnet-groups --filters Name=replication-subnet-group-id,Values=<project_name>-subnet-group
  aws dms describe-data-providers --filters Name=data-provider-identifier,Values=<project_name>-source
  aws dms describe-data-providers --filters Name=data-provider-identifier,Values=<project_name>-target
  aws s3api head-bucket --bucket <project_name>-sc-bucket-<aws_account_id>-<aws_region>
  aws iam get-role --role-name <project_name>-sc-secrets-role
  aws iam get-role --role-name <project_name>-sc-s3-role
  aws iam get-role --role-name <project_name>-sc-s3-access-role
  aws iam get-role --role-name dms-vpc-role
  aws iam get-role --role-name dms-cloudwatch-logs-role
  

• For each lookup, treat NotFoundException, ResourceNotFoundException, NoSuchEntity, or 404 as "not found" — do NOT surface these as errors to the customer

• After all lookups complete, present a table of what already exists vs. what will be created:

  Resource	Status
  Migration Project <project_name>-migration-project	EXISTS / will be created
  Instance Profile <project_name>-instance-profile	EXISTS / will be created
  Subnet Group <project_name>-subnet-group	EXISTS / will be created
  Source Data Provider <project_name>-source	EXISTS / will be created
  Target Data Provider <project_name>-target	EXISTS / will be created
  S3 Bucket <project_name>-sc-bucket-<aws_account_id>-<aws_region>	EXISTS / will be created
  Secrets IAM Role <project_name>-sc-secrets-role	EXISTS / will be created
  S3 IAM Role <project_name>-sc-s3-role	EXISTS / will be created
  S3 Access Role <project_name>-sc-s3-access-role (offline source)	EXISTS / will be created if needed
  DMS VPC Role dms-vpc-role	EXISTS / will be created
  DMS CloudWatch Role dms-cloudwatch-logs-role	EXISTS / will be created

• If the migration project already exists, inform the customer and ask: "A migration project with this name already exists. Would you like to (1) choose a different name, or (2) continue anyway and reuse existing resources where possible? If you choose option 2, please provide a new name for any resources that need to be recreated."

• You MUST wait for the customer's confirmation before proceeding to Phase 2

Phase 2 — Target Type Selection

Goal: Determine whether the target is a live database instance or a virtual target.

Explain:

"DMS Schema Conversion supports two target modes:

• Live database — connects to a live Amazon RDS, Aurora, or Redshift instance. DMS reads its network config automatically.

• Virtual — no live target database needed. Useful for reviewing converted schema without an actual DB.

Which would you like? (live / virtual)"

Supported target engines: aurora-postgresql, postgres, mysql, aurora, redshift, db2. See DMS SC supported target databases for the full list. A value of aurora represents Amazon Aurora MySQL-Compatible Edition.

Constraints:

• Accept live or virtual (case-insensitive); store as use_virtual_target

• If live: Ask for the target engine type (e.g., aurora-postgresql, mysql, redshift). Then ask:

  "Is your target an Amazon RDS/Aurora instance or Redshift cluster? If yes, provide the ARN and I'll retrieve connection details automatically. Otherwise, provide hostname, port, database name."

  • If ARN provided: Call aws rds describe-db-instances (or describe-db-clusters for Aurora, or aws redshift describe-clusters for Redshift) to fetch target_hostname, target_port, and target_database_name. Also extract target_vpc_id, target_subnet_ids, and target_security_group_ids from the instance/cluster metadata. Inform the customer of what was found.

  • If no ARN: Ask for the target database connection info (hostname, port, database name). Also ask for the VPC ID, subnet IDs, and security group IDs associated with the target.

  Store as target_engine, target_hostname, target_port, target_database_name, target_vpc_id, target_subnet_ids, target_security_group_ids.

• If virtual: Ask for the target engine type (e.g., aurora-postgresql, mysql, redshift). Store as target_engine.

  Prepare the target data provider params for use in Phase 7b:

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  target_data_provider_params = {
      "DataProviderName": "<project_name>-target",
      "Engine": "<target_engine>",
      "Virtual": True,
      "Settings": {
          "<TargetEngineSettings>": {
              "ServerName": "virtual",
              "Port": <default_port>,
              "DatabaseName": "virtual",
              "SslMode": "none"
          }
      }
  }
  

  Map target_engine → Settings key and default port:

  • aurora-postgresql or postgres → PostgreSqlSettings, port 5432

  • mysql or aurora → MySqlSettings, port 3306

  • redshift → RedshiftSettings, port 5439

  • db2 → IbmDb2LuwSettings, port 50000

Phase 3 — Source Database

Goal: Collect source engine and connection details.

3a — Source type

Ask for source engine. Supported source engines: sqlserver, oracle, mysql, postgres, db2, db2-zos, sybase. See DMS SC supported source databases for the full list. The customer may provide the engine name in any format — map it to the correct API identifier automatically.

3b — Source mode (online / offline)

If source engine is sqlserver, ask:

"Would you like to connect directly to the source database (online mode), or use exported DDL scripts from S3 (offline mode)?

• Online — DMS connects to your database to read metadata directly.

• Offline — DMS reads metadata from DDL scripts you've uploaded to S3. No database connectivity required."

Store as source_mode (online or offline).

If offline: Proceed to Phase 3d — Offline Source Configuration.

If source engine is NOT sqlserver, set source_mode = online (offline is available only for SQL Server).

3c — Source connection (online mode only)

Skip this step if source_mode = offline.

Ask for hostname, port, and database name in a single prompt. If the source is an RDS instance, offer to look up the connection details automatically:

"Is your source database an RDS instance? If yes, provide the RDS instance ARN or identifier and I'll retrieve the connection details automatically. Otherwise, please provide the hostname, port, and database name."

• If RDS source: Call aws rds describe-db-instances (or describe-db-clusters for Aurora) to fetch source_hostname, source_port, and source_database_name. Inform the customer of what was found.

• If not RDS: Ask for hostname, port, and database name directly.

Store as source_hostname, source_port, source_database_name.

3d — Offline source configuration

Skip this step if source_mode = online.

Step 1 — DDL Scripts (Offline Source)

Ask:

"What is the current state of your DDL scripts?

1. Already exported and uploaded to S3

2. Already exported but not yet uploaded to S3

3. Not yet exported — I'd like help"

Option 1 (exported + uploaded): Proceed to Step 2.

Option 2 (exported, not uploaded):

Ensure the DDL scripts end up as individual .sql files in S3. If the customer provides an archive (.zip, .tar.gz, .tar), extract it first. Adapt to whatever the customer provides:

• Agent has filesystem access to the files: Extract if archive, then upload .sql files to S3 with --sse AES256.

• Agent does NOT have filesystem access (remote): Provide the customer with a simple command. For a folder of .sql files: aws s3 sync ./ s3://<bucket>/<prefix>/ --sse AES256. For an archive: ask the customer to upload it to S3 with aws s3 cp, then the agent downloads, extracts, and re-uploads the .sql files to the correct prefix.

Constraints:

• Do NOT generate presigned URLs as the default upload method — prefer aws s3 sync or aws s3 cp.

• Do NOT ask the customer about encryption for files the agent uploads — always use --sse AES256.

• Do NOT ask for the database name during upload — derive it from DDL content after upload (see Step 3). Use any reasonable prefix for the initial upload (e.g., ddl/ or the project name).

Verify upload: aws s3 ls s3://<bucket>/<prefix>/ --recursive | head -10. Proceed to Step 2.

Option 3 (not exported):

Provide the customer with a template export script. Do NOT ask for database credentials — always present the script with placeholder variables for the customer to fill in.

Read Export SQL Server database objects and generate a PowerShell SMO script with clearly marked placeholders (hostname, database name, output directory, username, password). Let the customer run it independently.

Alternatively, provide the documentation link and DDL structure requirements (below) for customers who prefer their own tooling.

If the customer provides a file path or mentions having files at any point, switch to Option 2 flow immediately.

DDL structure requirements (inform customer if they export themselves):

• One SQL file per database object

• Each file contains exactly one CREATE statement

• USE [DatabaseName]; at the top of each file

• All objects for one database under a single S3 prefix

• No DML or DROP statements

Step 2 — S3 Configuration (Offline Source)

1. S3 path: Ask:

   "Please provide the S3 path to your DDL scripts (e.g., s3://my-bucket/MyDatabase/)."

   Store as ddl_s3_path.

2. Verify S3 content and region: List objects to confirm scripts are present:

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   aws s3 ls <ddl_s3_path> --recursive | head -10
   

   If empty or path not found, inform the customer and ask to correct.

   Also verify the bucket is in the same region as the DMS resources:

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   aws s3api get-bucket-location --bucket <bucket_name>
   

   A null or empty LocationConstraint means the bucket is in us-east-1. If the bucket region does not match aws_region, warn the customer: "Your DDL scripts bucket is in a different region than your DMS resources. DMS requires the S3 bucket to be in the same region. Please provide a bucket in <aws_region> or copy the scripts to a bucket in that region."

3. S3 access role: Ask:

   "Do you have an IAM role that grants DMS read access to this S3 bucket? If yes, provide the ARN. If no, I'll create one."

   • If provided: Validate with aws iam get-role. Store as offline_s3_access_role_arn.

   • If not provided: Create the role in Phase 9e.

4. KMS encryption (optional): Skip this step if the agent uploaded the files (the agent already used SSE-S3 / --sse AES256 which is the recommended default for DMS Schema Conversion).

   Only ask if the customer provided a pre-existing S3 path (Option 1):

   "Are the S3 objects encrypted with a customer-managed KMS key? (yes / no)"

   • If yes: Ask for the KMS key ARN. Store as s3_kms_key_arn. The S3 access role will need kms:Decrypt permission on this key (handled in Phase 9e).

   • If no: No additional configuration needed (SSE-S3 is the default and requires no extra permissions).

   Constraint: Do NOT ask about encryption if you already uploaded the files yourself — you know the answer.

Step 3 — Prepare Source Data Provider Settings (Offline Source)

Derive DatabaseName from DDL content:

The DatabaseName field MUST match the database name used in the DDL scripts. DMS uses it to construct the metadata tree and match USE [DatabaseName] statements. An incorrect value causes import to fail with "Unexpected application error".

To derive the correct value:

1. Download one .sql file from the S3 path (preferably _create_database.sql or any file with a USE statement):

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   aws s3 cp <ddl_s3_path><first_file> - | head -5
   

2. Look for USE [<name>] or CREATE DATABASE [<name>] — extract <name> as the database name. Do not log or persist this output.

3. If no USE/CREATE DATABASE statement is found, use the last path segment of ddl_s3_path (the folder name containing the DDL scripts) as the database name.

4. If the DDL scripts are at the bucket root (no prefix folder), ask the customer for the database name.

Store the derived value as <database_name>.

source_engine = "sqlserver"
source_mode = "offline"
source_data_provider_params = {
    "DataProviderName": "<project_name>-source",
    "Engine": "sqlserver",
    "Virtual": True,
    "Settings": {
        "MicrosoftSqlServerSettings": {
            "ServerName": "offline",
            "Port": 1433,
            "DatabaseName": "<database_name>",
            "SslMode": "none",
            "S3Path": "<ddl_s3_path>",
            "S3AccessRoleArn": "<offline_s3_access_role_arn>"
        }
    }
}

Use source_data_provider_params directly as the params argument when calling CreateDataProvider in Phase 7a.

Constraint: Do NOT hardcode "DatabaseName": "offline". Do NOT ask the customer for the database name if it can be derived from the DDL scripts or S3 path.

Phase 4 — Network Investigation & Connectivity

Goal: Determine VPC, subnets, and security groups for the DMS instance profile.

4a — Derive or ask for VPC

Skip Phase 4 entirely (4a, 4b, 4c) if source_mode = offline AND use_virtual_target = true. No network configuration is needed — the instance profile will be created without subnet group or security groups.

• If live target: Use target_vpc_id from Phase 2. Ask if the customer also wants to reuse the target subnets and security groups. If yes, skip to 4c.

  Note: Reusing the same security group is less secure than creating a dedicated SG with minimal permissions.

• If virtual target AND source_mode = online: Use the VPC where the source database resides. If the source is an RDS instance, derive the VPC from the RDS metadata. Otherwise, ask the customer which VPC the source database is in.

4b — Collect subnets and security groups manually

• Ask for at least two subnet IDs from different AZs (comma-separated)

• Validate with: aws ec2 describe-subnets --subnet-ids <ids> --query Subnets[*].{ID:SubnetId,AZ:AvailabilityZone,VPC:VpcId}

• Verify all subnets belong to the same VPC and span at least 2 AZs

• Ask for security group IDs (comma-separated)

• After collecting security group IDs, run aws ec2 describe-security-groups --group-ids <ids> and check for rules referencing 0.0.0.0/0 or ::/0. If found, warn the customer and recommend scoping rules to the specific database port and source CIDR or security group reference.

4c — Connectivity confirmation

Skip this step if source_mode = offline — no source database connectivity is needed.

Ask:

"Does your source database require special network setup to be reachable from this VPC? (VPN, Direct Connect, VPC peering, firewall rules) (yes / no)"

• If yes: Guide the customer through the network setup based on https://docs.aws.amazon.com/dms/latest/userguide/instance-profiles-network.html. Read the documentation and help them configure VPN, Direct Connect, VPC peering, or firewall rules as needed.

• If no: Reference https://docs.aws.amazon.com/dms/latest/userguide/instance-profiles-network.html#instance-profiles-network-one-vpc. Read the documentation requirements and validate that the customer's network configuration meets all of them.

Store final vpc_id, subnet_ids, security_group_ids.

Phase 5 — Create DMS Subnet Group

Skip this phase if source_mode = offline AND use_virtual_target = true.

Goal: Create the subnet group for the DMS instance profile.

aws dms create-replication-subnet-group \
  --replication-subnet-group-identifier <project_name>-subnet-group \
  --replication-subnet-group-description "Subnet group for <project_name>" \
  --subnet-ids <subnet_ids>

Store subnet_group_identifier. On ResourceAlreadyExistsFault, reuse existing.

Phase 6 — Database Credentials

Goal: Collect the Secrets Manager secrets for both source and target database credentials.

6a — Source credentials

Ask if the customer needs help setting up source database credentials. Guide the customer based on source data provider prerequisites for required permissions.

Ask for the Secrets Manager secret ARN containing the source database credentials:

"Please provide the ARN of the Secrets Manager secret with your source database username and password. If your source is an RDS instance, you can find the secret in the RDS console under 'Connectivity & security'."

Important: The secret must contain a JSON with keys username and password. Warn the customer that the RDS-managed admin secret has extensive privileges that Schema Conversion does not need. Recommend creating a dedicated database user with minimal required permissions. See required permissions for the full list.

Store as source_secret_arn.

6b — Target credentials

Ask if the customer needs help setting up target database credentials. Guide the customer based on target data provider prerequisites for required permissions.

If virtual target: A secret is still required by DMS even though it won't be used for an actual connection. Create a placeholder secret automatically (the password is non-sensitive — used only to satisfy the API schema requirement):

aws secretsmanager create-secret \
  --name <project_name>-target-dummy-secret \
  --secret-string '{"username":"virtual_placeholder","password":"'"$(openssl rand -base64 16)"'"}'

On ResourceExistsException, reuse the existing secret. Store the ARN as target_secret_arn.

If live target (RDS/Aurora/Redshift): If the customer provided an ARN in Phase 2, automatically retrieve the associated secret ARN from the instance/cluster metadata (e.g., MasterUserSecret.SecretArn from describe-db-instances or describe-db-clusters). Inform the customer of the secret found. If no secret is associated with the instance, fall back to asking manually.

If live target (other or manual): Ask:

"Please provide the ARN of the Secrets Manager secret with your target database username and password."

Important: Warn the customer that managed admin secrets have extensive privileges that Schema Conversion does not need. Recommend creating a dedicated database user with minimal required permissions and storing those credentials in a separate secret.

Store as target_secret_arn.

Phase 7 — Create Data Providers

Goal: Register source and target data providers in DMS.

7a — Source data provider

If source_mode = offline:

aws dms create-data-provider \
  --data-provider-name <project_name>-source \
  --engine sqlserver \
  --virtual \
  --settings '{"MicrosoftSqlServerSettings":{"ServerName":"offline","Port":1433,"DatabaseName":"<database_name>","SslMode":"none","S3Path":"<ddl_s3_path>","S3AccessRoleArn":"<offline_s3_access_role_arn>"}}'

If source_mode = online:

aws dms create-data-provider \
  --data-provider-name <project_name>-source \
  --engine <source_engine> \
  --settings '{"<EngineSettings>":{"ServerName":"<source_hostname>","Port":<source_port>,"DatabaseName":"<source_database_name>","SslMode":"<ssl_mode>"}}'

Store source_data_provider_arn. Do NOT include credentials in settings.

SSL/TLS: For offline mode, SslMode is already set to "none" — do NOT ask the customer. For online mode, ask the customer which SSL mode to use (require, verify-ca, verify-full, none). Recommend require or higher. Warning: none transmits credentials and data unencrypted — use only in isolated test environments with no sensitive data.

7b — Target data provider

If virtual target:

aws dms create-data-provider \
  --data-provider-name <project_name>-target \
  --engine <target_engine> \
  --virtual \
  --settings '{"<TargetEngineSettings>":{"ServerName":"virtual","Port":<default_port>,"DatabaseName":"virtual","SslMode":"none"}}'

Use the same engine → Settings key mapping from Phase 2 (PostgreSqlSettings/5432, MySqlSettings/3306, RedshiftSettings/5439, IbmDb2LuwSettings/50000).

If live target:

aws dms create-data-provider \
  --data-provider-name <project_name>-target \
  --engine <target_engine> \
  --settings '{"<EngineSettings>":{"ServerName":"<target_hostname>","Port":<target_port>,"DatabaseName":"<target_database_name>","SslMode":"<ssl_mode>"}}'

Do NOT pass Virtual for live targets.

Store target_data_provider_arn.

7c — Verify Virtual flag

You MUST verify both data providers have the correct Virtual flag immediately after creation.

Expected values:

• Source: Virtual = True if source_mode = offline, False if online

• Target: Virtual = True if use_virtual_target = true, False if live target

For each data provider, describe and check the Virtual field:

aws dms describe-data-providers \
  --filters Name=data-provider-identifier,Values=<project_name>-source

If the Virtual flag does not match the expected value, attempt to modify:

aws dms modify-data-provider \
  --data-provider-identifier <project_name>-source \
  --engine <engine> \
  --virtual \
  --settings '<settings_json_from_describe>'

If modify fails ("Cannot convert a non-virtual data provider to virtual"), delete and recreate with the correct flag:

aws dms delete-data-provider \
  --data-provider-identifier <project_name>-source

aws dms create-data-provider \
  --data-provider-name <project_name>-source \
  --engine <engine> \
  --virtual \
  --settings '<settings_json>'

Repeat for the target data provider. After any recreate, re-store the new ARN from the create-data-provider response — the old ARN is no longer valid. Do NOT proceed to Phase 8 until both data providers have the correct Virtual flag.

Phase 8 — S3 Bucket

Goal: Ensure an S3 bucket exists for migration artifacts.

Ask if the customer has an existing bucket. If yes, validate with aws s3api head-bucket. If no, create <project_name>-sc-bucket-<aws_account_id>-<aws_region>.

# For us-east-1:
aws s3api create-bucket --bucket <bucket_name> --region us-east-1

# For all other regions:
aws s3api create-bucket \
  --bucket <bucket_name> \
  --region <aws_region> \
  --create-bucket-configuration LocationConstraint=<aws_region>

aws s3api put-bucket-versioning \
  --bucket <bucket_name> \
  --versioning-configuration Status=Enabled

aws s3api put-public-access-block \
  --bucket <bucket_name> \
  --public-access-block-configuration BlockPublicAcls=true,IgnorePublicAcls=true,BlockPublicPolicy=true,RestrictPublicBuckets=true

aws s3api put-bucket-policy --bucket <bucket_name> --policy '{
  "Version": "2012-10-17",
  "Statement": [{
    "Sid": "DenyInsecureTransport",
    "Effect": "Deny",
    "Principal": "*",
    "Action": "s3:*",
    "Resource": ["arn:aws:s3:::<bucket_name>", "arn:aws:s3:::<bucket_name>/*"],
    "Condition": {"Bool": {"aws:SecureTransport": "false"}}
  }]
}'

Constraints:

• The bucket name MUST include the region suffix: <project_name>-sc-bucket-<aws_account_id>-<aws_region>

• Do NOT configure SSE-KMS — DMS Schema Conversion only supports SSE-S3 (default)

• Store bucket_name

Phase 9 — IAM Roles

Goal: Create IAM roles: Secrets Manager access role, S3 access role, DMS VPC role, and DMS CloudWatch Logs role.

Important — two distinct S3 roles exist. Do NOT confuse them when troubleshooting:

When an S3 permission error occurs during import, the problem is almost always the S3 Access Role (9e) — not the S3 Role (9b). When an S3 error occurs during project creation or export, the problem is the S3 Role (9b).

9a — Secrets Manager Role

Ask if an existing role is available. If yes, validate with aws iam get-role. If no, create:

1. Create the role with trust policy (includes condition keys to prevent confused deputy):

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   aws iam create-role \
     --role-name <project_name>-sc-secrets-role \
     --assume-role-policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":{"Service":"dms.amazonaws.com"},"Action":"sts:AssumeRole","Condition":{"StringEquals":{"aws:SourceAccount":"<aws_account_id>"},"ArnLike":{"aws:SourceArn":"arn:aws:dms:<aws_region>:<aws_account_id>:*"}}}]}'
   

2. Attach a policy granting access to the secret ARNs used by the migration project. See IAM policies for DMS for the required permissions (Secrets Manager and KMS actions). Scope the resource to <source_secret_arn> and <target_secret_arn>.

Store secrets_role_arn.

9b — S3 Role

Ask if an existing role is available. If yes, validate. If no, create:

1. Create the role with trust policy (includes condition keys to prevent confused deputy):

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   aws iam create-role \
     --role-name <project_name>-sc-s3-role \
     --assume-role-policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":{"Service":"dms.amazonaws.com"},"Action":"sts:AssumeRole","Condition":{"StringEquals":{"aws:SourceAccount":"<aws_account_id>"},"ArnLike":{"aws:SourceArn":"arn:aws:dms:<aws_region>:<aws_account_id>:*"}}}]}'
   

2. Attach a policy granting S3 access to the artifacts bucket. Follow the exact policy from IAM policies for DMS SC: two statements — bucket-level (s3:ListBucket, s3:GetBucketLocation, s3:GetBucketVersioning on arn:aws:s3:::<bucket_name>) and object-level (s3:PutObject, s3:GetObject, s3:GetObjectVersion on arn:aws:s3:::<bucket_name>/*). Add aws:ResourceAccount condition for least-privilege.

Store s3_role_arn.

9c — DMS VPC Role

Required by DMS to manage VPC and ENI resources. The role name MUST be exactly dms-vpc-role — DMS looks it up by this fixed name. See IAM roles for DMS for details.

First check if the role exists:

aws iam get-role --role-name dms-vpc-role

If the role already exists (found in Phase 1 lookup or via the check above), skip creation. Otherwise create it:

1. Create the role with trust policy for dms.amazonaws.com (includes condition keys to prevent confused deputy):

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   aws iam create-role \
     --role-name dms-vpc-role \
     --assume-role-policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":{"Service":"dms.amazonaws.com"},"Action":"sts:AssumeRole","Condition":{"StringEquals":{"aws:SourceAccount":"<aws_account_id>"},"ArnLike":{"aws:SourceArn":"arn:aws:dms:<aws_region>:<aws_account_id>:*"}}}]}'
   

2. Attach the AWS managed policy:

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   aws iam attach-role-policy \
     --role-name dms-vpc-role \
     --policy-arn arn:aws:iam::aws:policy/service-role/AmazonDMSVPCManagementRole
   

9d — DMS CloudWatch Logs Role

Required by DMS to publish schema conversion logs to CloudWatch. The role name MUST be exactly dms-cloudwatch-logs-role. See IAM roles for DMS for details.

First check if the role exists:

aws iam get-role --role-name dms-cloudwatch-logs-role

If the role already exists (found in Phase 1 lookup or via the check above), skip creation. Otherwise create it:

1. Create the role with trust policy for dms.amazonaws.com (includes condition keys to prevent confused deputy):

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   aws iam create-role \
     --role-name dms-cloudwatch-logs-role \
     --assume-role-policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":{"Service":"dms.amazonaws.com"},"Action":"sts:AssumeRole","Condition":{"StringEquals":{"aws:SourceAccount":"<aws_account_id>"},"ArnLike":{"aws:SourceArn":"arn:aws:dms:<aws_region>:<aws_account_id>:*"}}}]}'
   

2. Attach the AWS managed policy:

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   aws iam attach-role-policy \
     --role-name dms-cloudwatch-logs-role \
     --policy-arn arn:aws:iam::aws:policy/service-role/AmazonDMSCloudWatchLogsRole
   

9e — S3 Access Role for Offline Source

Skip this step if source_mode = online or the customer already provided offline_s3_access_role_arn in Phase 3d.

Create an IAM role allowing DMS to read DDL scripts from the customer's S3 bucket (the bucket from ddl_s3_path, NOT the migration artifacts bucket from Phase 8):

1. Create the role with trust policy:

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   aws iam create-role \
     --role-name <project_name>-sc-s3-access-role \
     --assume-role-policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":{"Service":"dms.amazonaws.com"},"Action":"sts:AssumeRole","Condition":{"StringEquals":{"aws:SourceAccount":"<aws_account_id>"},"ArnLike":{"aws:SourceArn":"arn:aws:dms:<aws_region>:<aws_account_id>:*"}}}]}'
   

2. Attach S3 read policy scoped to the DDL scripts bucket (extract bucket name from ddl_s3_path):

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   aws iam put-role-policy \
     --role-name <project_name>-sc-s3-access-role \
     --policy-name S3ReadAccess \
     --policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Action":"s3:ListBucket","Resource":"arn:aws:s3:::<ddl_bucket_name>"},{"Effect":"Allow","Action":"s3:GetObject","Resource":"arn:aws:s3:::<ddl_bucket_name>/*"}]}'
   

3. If s3_kms_key_arn is set, add KMS decrypt:

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   aws iam put-role-policy \
     --role-name <project_name>-sc-s3-access-role \
     --policy-name KmsDecrypt \
     --policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Action":"kms:Decrypt","Resource":"<s3_kms_key_arn>","Condition":{"StringEquals":{"kms:ViaService":"s3.<aws_region>.amazonaws.com"}}}]}'
   

Store offline_s3_access_role_arn.

Phase 10 — Create Instance Profile

Goal: Create the DMS instance profile that ties together the subnet group and security groups.

If source_mode = offline AND use_virtual_target = true:

aws dms create-instance-profile \
  --instance-profile-name <project_name>-instance-profile

Otherwise:

aws dms create-instance-profile \
  --instance-profile-name <project_name>-instance-profile \
  --subnet-group-identifier <subnet_group_identifier> \
  --vpc-security-groups <security_group_ids>

Store instance_profile_arn and instance_profile_name.

Phase 11 — Transformation Rules (Optional)

You MUST ask the customer about transformation rules before proceeding to Phase 12:

"Would you like to apply any transformation rules during conversion — such as renaming schemas, converting object names to uppercase/lowercase, or adding prefixes/suffixes? (yes / no)"

If yes, help them build the rules JSON. See Transformation rules in DMS Schema Conversion for format and options. Store as transformation_rules. If no, set to null.

Phase 12 — Create Migration Project & Summary

12a — Create Migration Project

Build source descriptor (always includes secret):

• {"DataProviderIdentifier": "<source_data_provider_arn>", "SecretsManagerSecretId": "<source_secret_arn>", "SecretsManagerAccessRoleArn": "<secrets_role_arn>"}

Build target descriptor (always includes secret):

• {"DataProviderIdentifier": "<target_data_provider_arn>", "SecretsManagerSecretId": "<target_secret_arn>", "SecretsManagerAccessRoleArn": "<secrets_role_arn>"}

aws dms create-migration-project \
  --migration-project-name <project_name>-migration-project \
  --instance-profile-identifier <instance_profile_name> \
  --schema-conversion-application-attributes '{"S3BucketPath":"s3://<bucket_name>","S3BucketRoleArn":"<s3_role_arn>"}' \
  --source-data-provider-descriptors '[{"DataProviderIdentifier":"<source_data_provider_arn>","SecretsManagerSecretId":"<source_secret_arn>","SecretsManagerAccessRoleArn":"<secrets_role_arn>"}]' \
  --target-data-provider-descriptors '[{"DataProviderIdentifier":"<target_data_provider_arn>","SecretsManagerSecretId":"<target_secret_arn>","SecretsManagerAccessRoleArn":"<secrets_role_arn>"}]'
  [--transformation-rules '<json>' if not null]

Store migration_project_arn and migration_project_name.

12b — Verify

If create-migration-project returns an error, surface the error message to the customer and refer to troubleshooting.md for diagnosis. Common sync errors include AccessDeniedFault (IAM permissions), ResourceNotFoundFault (instance profile or data provider not found), and InvalidResourceStateFault.

12c — Summary Table

Then inform the customer:

"Setup complete."