Database Migration Strategy Assessment¶

Date: 2025-10-13 Author: Claude Code Assessment Status: Analysis Complete - No Changes Made

Executive Summary¶

The S5 Slidefactory project uses a hybrid migration approach combining manual SQL scripts with Python-based migrations. The current system is functional but inconsistent, mixing multiple migration patterns without a unified strategy. The project would benefit from consolidating to a single migration framework (Alembic recommended).

Key Finding: The database schema is well-designed with proper indexes and vector search support, but the migration management is fragmented across multiple locations with no version tracking system in place.

Current Migration Landscape¶

Migration Files Distribution¶

Total Migration Files: 9 files across 3 locations

1. Root Migrations Directory (/migrations/)¶

7 SQL files:

1. 002_add_results_data_table.sql (50 lines)
2. Creates results_data table for workflow results
3. Adds trigger for updated_at timestamp

4. Comprehensive indexes and comments

5. 003_add_engine_type_to_workflow_meta_files.sql (31 lines)

6. Adds engine_type, uploaded_by, execution_id, is_active, description columns
7. Creates indexes for performance

8. Supports N8N-first architecture

9. add_engine_reference_to_processes.sql (15 lines)

10. Adds engine reference to processes table

11. Brief migration

12. create_api_keys_table.sql (43 lines)

13. Creates api_keys table for programmatic access
14. Includes rate limiting and usage tracking

15. Proper indexes and comments

16. extend_workflow_meta_files.sql (39 lines)

17. Extends workflow meta files table

18. Adds file tracking capabilities

19. remove_workflow_meta_files_fk.sql (9 lines)

20. Removes foreign key constraint from app_workflow_meta_files

21. Allows templates for any workflow folder

22. README.md (56 lines)

23. Documents migration process
24. Provides execution instructions
25. Good documentation

2. Context Module Migrations (/app/context/migrations/)¶

2 Python files (Alembic-style):

1. add_raw_file_path.py (14 lines)
2. Alembic migration
3. Adds raw_file_path column to context_documents
4. Includes upgrade/downgrade functions

5. Date: 2024-02-21

6. migrate_content_to_minio.py (5417+ bytes, not fully examined)

7. Data migration script
8. Migrates content to MinIO storage
9. Likely a one-time data transformation

3. Initialization Scripts (Root)¶

2 SQL files:

1. init.sql (448 lines)
2. Complete database schema from scratch
3. Includes all tables, indexes, enums, comments
4. Incorporates all migrations up to current version

5. Used for new installations

6. init.azure.sql (location found but not examined)

7. Likely Azure-specific initialization
8. May have Azure-specific configurations

Migration Patterns Analysis¶

Pattern 1: Manual SQL Migrations (Primary)¶

Location: /migrations/*.sql

Characteristics: - Hand-written SQL scripts - Include CREATE TABLE IF NOT EXISTS for idempotency - Comprehensive comments and documentation - Indexes created inline - No automatic version tracking

Example:

-- Migration: Add results_data table
-- Date: 2025-10-03
CREATE TABLE IF NOT EXISTS results_data (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    execution_id VARCHAR(255) NOT NULL,
    ...
);

Strengths: - Clear, readable SQL - Idempotent (safe to re-run) - Good documentation - Direct database control

Weaknesses: - No automatic version tracking - Manual execution required - No rollback support - Requires psql knowledge

Pattern 2: Alembic Migrations (Legacy)¶

Location: /app/context/migrations/*.py

Characteristics: - Python-based Alembic framework - Includes revision IDs - Has upgrade/downgrade functions - Module-specific location

Example:

"""add raw file path column

Revision ID: add_raw_file_path
Create Date: 2024-02-21
"""
from alembic import op
import sqlalchemy as sa

def upgrade():
    op.add_column('context_documents',
                  sa.Column('raw_file_path', sa.String(), nullable=True))

def downgrade():
    op.drop_column('context_documents', 'raw_file_path')

Strengths: - Version tracking built-in - Rollback support - Database-agnostic (mostly) - Python integration

Weaknesses: - Only 2 migrations (not widely adopted) - Module-specific location - No central Alembic configuration found - Unclear if still in use

Pattern 3: Initialization Schema¶

Location: /init.sql

Characteristics: - Complete database schema definition - Includes all migrations "baked in" - Used for new installations only - Must be manually updated when migrations are added

Strengths: - Single-file database setup for new installs - Comprehensive and complete - Well-documented with comments

Weaknesses: - Must be manually kept in sync with migrations - No version tracking - Not suitable for upgrading existing databases

Database Schema Overview¶

Tables (19 total)¶

Core Application Tables¶

1. app_processes
2. Workflow execution tracking
3. Stores execution state, context, results

4. Indexes: id, user_id, workflow_folder, workflow_id, context_id

5. app_workflows

6. Workflow instances
7. Links to workflow metadata

8. Foreign key to app_workflow_meta

9. app_workflow_meta

10. Workflow definitions and metadata
11. JSON fields for workflow_definition, prompts_data, file_references

12. Unique constraint on folder

13. app_workflow_meta_files

14. File references in blob storage
15. Supports multiple engine types (n8n, prefect, windmill)
16. Soft delete with is_active flag

17. No foreign key to allow templates for any workflow

18. app_prompts

19. Prompt storage for workflows

20. Versioned with sequence/dimension tracking

21. app_users

22. User accounts

23. Simple structure (id, name, email, password, attributes)

24. app_storage_items

25. Storage item tracking

26. app_dimension_order

27. Dimension ordering for workflows

28. app_sequence_order

29. Sequence ordering for workflows

Context Module Tables¶

1. context_documents

   • Document metadata
   • Links to document content in storage
   • Optional workflow tracking via workflow_folder
   • Indexes for context_id, timestamp, document_type

2. context_chunks

   • Text chunks from documents
   • Includes pgvector embeddings (1024 dimensions)
   • Foreign key to context_documents
   • Vector similarity indexes (ivfflat)
   • Cosine distance index for semantic search

Data Tables¶

1. results_data

   • Unified workflow results storage
   • Decoupled from app_processes
   • JSONB content field
   • Trigger for updated_at timestamp
   • Created: 2025-10-03

2. api_keys

   • API key authentication
   • SHA256 hashed keys
   • Rate limiting support
   • Usage tracking
   • Created: 2025-02-10

3. cache_scraped_raw

   • Web scraping cache
   • URL and content storage

Custom Types (2)¶

1. executionstate ENUM
2. Values: pending, running, finished, canceled

3. Used by app_processes

4. workflowexecutionstate ENUM

5. Values: pending, running, finished, canceled
6. Used by app_workflows

PostgreSQL Extensions¶

1. vector (pgvector)
2. Vector similarity search
3. Required for context module embeddings
4. Critical dependency

Schema Design Assessment¶

Strengths¶

1. Vector Search Integration ✅¶

Excellent implementation: - pgvector extension properly installed - 1024-dimensional embeddings - IVFFlat indexes for performance - Cosine distance index for semantic search

CREATE TABLE context_chunks (
    embedding vector NULL,
    ...
);

CREATE INDEX context_chunks_embedding_cosine_idx
ON context_chunks USING ivfflat (embedding vector_cosine_ops)
WITH (lists = 100);

2. Comprehensive Indexing ✅¶

Well-optimized: - Primary key indexes on all tables - Foreign key indexes for joins - Composite indexes for common queries - Vector indexes for similarity search

Example composite index:

CREATE INDEX idx_context_documents_context_timestamp
ON context_documents (context_id, timestamp DESC);

3. Documentation ✅¶

Excellent table and column comments:

COMMENT ON TABLE results_data IS 'Unified storage for workflow results...';
COMMENT ON COLUMN results_data.execution_id IS 'Workflow execution ID...';

4. JSON Flexibility ✅¶

Strategic use of JSON/JSONB: - workflow_definition (JSON) - results_data.content (JSONB) - api_keys.scopes (JSONB) - Allows flexible schema evolution

5. Soft Deletes ✅¶

Proper soft delete pattern:

is_active BOOLEAN NOT NULL DEFAULT TRUE

Used in: - app_workflow_meta_files - api_keys - app_users

Weaknesses¶

1. Removed Foreign Key Constraint ⚠️¶

Issue:

-- Foreign key constraint removed to allow templates for any workflow folder
-- CONSTRAINT fk_workflow_meta_files_folder FOREIGN KEY (workflow_folder)
-- REFERENCES app_workflow_meta(folder) ON DELETE CASCADE

Impact: - No referential integrity - Orphaned records possible - Manual cleanup required

Rationale: Allow templates for workflows not yet in database (N8N-first)

Recommendation: Consider using ON DELETE SET NULL instead of removing FK entirely

2. Mixed Timestamp Conventions ⚠️¶

Inconsistency: - Some tables: created_at timestamp - Some tables: created_at TIMESTAMP WITH TIME ZONE - Results table: Uses triggers for updated_at - Others: No automatic updates

Impact: Timezone confusion, inconsistent behavior

Recommendation: Standardize on TIMESTAMP WITH TIME ZONE

3. No Migration Version Table ❌¶

Problem: - No schema_migrations or alembic_version table - Cannot track which migrations have been applied - Manual bookkeeping required

Impact: - Risk of re-running migrations - No audit trail - Difficult to determine database version

Recommendation: Add migration tracking table

4. Dual Migration Systems ⚠️¶

Confusion: - SQL migrations in /migrations/ - Alembic migrations in /app/context/migrations/ - No clear standard

Impact: - Developer confusion - Inconsistent approaches - Maintenance burden

Recommendation: Consolidate to single approach

Migration Execution Analysis¶

Current Process (from /migrations/README.md)¶

For New Installations¶

psql $DATABASE_URL < init.sql

Works well: Single command, complete setup

For Existing Installations¶

# Manual approach
psql $DATABASE_URL

# Run each migration
\i migrations/002_add_results_data_table.sql
\i migrations/003_add_engine_type_to_workflow_meta_files.sql

Problems: - Manual tracking of which migrations applied - Easy to miss migrations - No rollback if migration fails midway

Batch Approach¶

for file in migrations/*.sql; do
    echo "Running migration: $file"
    psql $DATABASE_URL < "$file"
done

Problems: - Runs all migrations (including already applied) - Relies on IF NOT EXISTS safety - No failure handling - No version tracking

Migration Health Assessment¶

Migration File Quality¶

Scoring by Migration:

1. ✅ 002_add_results_data_table.sql (Excellent)
2. Idempotent (IF NOT EXISTS)
3. Comprehensive indexes
4. Detailed comments
5. Trigger for timestamps

6. Migration date documented

7. ✅ 003_add_engine_type_to_workflow_meta_files.sql (Excellent)

8. Idempotent (IF NOT EXISTS, ADD COLUMN IF NOT EXISTS)
9. Proper indexes
10. Clear comments

11. Migration date documented

12. ⚠️ add_engine_reference_to_processes.sql (Good)

13. Brief, no documentation
14. No date
15. No comments

16. Functional but minimal

17. ✅ create_api_keys_table.sql (Excellent)

18. Idempotent
19. Comprehensive indexes
20. Detailed comments
21. Security considerations (hashing)

22. Migration date documented

23. ⚠️ extend_workflow_meta_files.sql (Good)

24. Functional
25. Limited documentation

26. Could be more comprehensive

27. ⚠️ remove_workflow_meta_files_fk.sql (Concerning)

28. Removes referential integrity
29. Brief explanation

30. Consider alternative approaches

31. ✅ README.md (Excellent)

32. Clear documentation
33. Usage instructions
34. Best practices
35. Rollback guidance

Overall Migration Quality: Good (⚠️ with concerns)¶

Strengths: - Most migrations are idempotent - Good documentation in recent migrations - README provides clear instructions

Concerns: - Inconsistent documentation quality - No version tracking - No automated rollback - Removed FK constraint is risky

Database Version Tracking Problem¶

Current State: No Version Tracking ❌¶

Problems:

1. No audit trail
2. Cannot determine which migrations applied
3. Cannot verify database is up-to-date

4. Manual tracking required

5. Risk of missing migrations

6. New deployments may skip migrations

7. Developers may not know which to run

8. No rollback capability

9. Cannot undo migrations

10. Manual SQL required for rollback

11. Difficult collaboration

12. Multiple developers may create conflicting migrations
13. No conflict detection

Recommended Solution: Add Version Tracking¶

Option 1: Alembic (Recommended)¶

Pros: - Industry standard - Automatic version tracking - Rollback support - Database-agnostic - Python integration

Implementation:

# Install Alembic
pip install alembic

# Initialize Alembic
alembic init alembic

# Generate migration
alembic revision --autogenerate -m "add new table"

# Apply migrations
alembic upgrade head

# Rollback
alembic downgrade -1

Alembic creates version table:

CREATE TABLE alembic_version (
    version_num VARCHAR(32) NOT NULL,
    CONSTRAINT alembic_version_pkc PRIMARY KEY (version_num)
);

Option 2: Custom Version Table¶

Simpler alternative:

CREATE TABLE schema_migrations (
    version VARCHAR(14) NOT NULL PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    applied_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(),
    CONSTRAINT schema_migrations_pkey PRIMARY KEY (version)
);

-- Example entries
INSERT INTO schema_migrations (version, name)
VALUES
    ('20250210', 'create_api_keys_table'),
    ('20251003', 'add_results_data_table');

Migration wrapper script:

#!/bin/bash
# run_migration.sh

VERSION=$1
NAME=$2
SQL_FILE=$3

# Check if already applied
EXISTS=$(psql $DATABASE_URL -tAc "SELECT 1 FROM schema_migrations WHERE version='$VERSION'")

if [ "$EXISTS" = "1" ]; then
    echo "Migration $VERSION already applied, skipping"
    exit 0
fi

# Run migration
psql $DATABASE_URL < "$SQL_FILE"

# Record version
psql $DATABASE_URL -c "INSERT INTO schema_migrations (version, name) VALUES ('$VERSION', '$NAME')"

echo "Migration $VERSION applied successfully"

Migration Strategy Comparison¶

Current Approach: Manual SQL¶

Recommended: Alembic¶

Consolidation Recommendations¶

Priority 1: Add Version Tracking (Immediate)¶

Option A: Adopt Alembic (Recommended)¶

Steps:

1. Install Alembic

   pip install alembic
   echo "alembic>=1.13.0" >> requirements.txt
   

2. Initialize Alembic

   alembic init alembic
   

3. Configure Alembic Edit alembic/env.py:

   from app.config import settings
   config.set_main_option('sqlalchemy.url', settings.DATABASE_URL)
   

4. Mark Existing Migrations as Applied

   # Stamp database as already at current state
   alembic stamp head
   

5. Convert Existing SQL Migrations Create Alembic equivalents:

   alembic revision -m "existing_schema_baseline"
   # Empty upgrade/downgrade (already applied)
   

6. Future Migrations via Alembic

   alembic revision -m "add new table"
   # Edit generated file
   alembic upgrade head
   

Option B: Add Simple Version Table¶

Steps:

1. Create version table

   CREATE TABLE schema_migrations (
       version VARCHAR(14) PRIMARY KEY,
       name VARCHAR(255) NOT NULL,
       applied_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
   );
   

2. Record existing migrations

   INSERT INTO schema_migrations (version, name) VALUES
       ('20250210', 'create_api_keys_table'),
       ('20251003', 'add_results_data_table'),
       ('20251003_02', 'add_engine_type_to_workflow_meta_files');
   

3. Create migration runner script (see above)

4. Update migration process

5. Rename migrations with version prefix: YYYYMMDD_description.sql
6. Use runner script instead of direct psql

Priority 2: Consolidate Migration Locations¶

Recommendation: Single /migrations/ Directory¶

Rationale: - Centralized location - Easier to find - No module-specific confusion

Steps:

1. Keep /migrations/ as primary
2. All SQL migrations go here

3. Or all Alembic migrations go to /alembic/versions/

4. Move or deprecate /app/context/migrations/

   # If using Alembic
   mv app/context/migrations/*.py alembic/versions/
   
   # If using SQL
   # Convert to SQL and move to /migrations/
   

5. Update documentation

6. Make location clear in CLAUDE.md
7. Update migration README

Priority 3: Standardize Migration Format¶

If Using SQL¶

Standard template:

-- Migration: [Title]
-- Version: YYYYMMDD_NN
-- Date: YYYY-MM-DD
-- Description: [Detailed description]
--
-- Rollback: [Rollback instructions or SQL]

-- Migration code here
CREATE TABLE IF NOT EXISTS new_table (
    ...
);

-- Record migration (if using version table)
INSERT INTO schema_migrations (version, name)
VALUES ('20251013_01', 'add_new_table')
ON CONFLICT DO NOTHING;

If Using Alembic¶

Use Alembic conventions: - Auto-generated revision IDs - Clear upgrade/downgrade functions - Comprehensive docstrings

Priority 4: Fix Timestamp Inconsistencies¶

Standardize on: TIMESTAMP WITH TIME ZONE

Migration:

-- Migration: Standardize timestamps
-- Version: 20251013_02
-- Date: 2025-10-13

-- Update all timestamp columns to TIMESTAMPTZ
ALTER TABLE app_processes
    ALTER COLUMN created_at TYPE TIMESTAMP WITH TIME ZONE,
    ALTER COLUMN finished_at TYPE TIMESTAMP WITH TIME ZONE;

ALTER TABLE app_workflows
    ALTER COLUMN created_at TYPE TIMESTAMP WITH TIME ZONE,
    ALTER COLUMN finished_at TYPE TIMESTAMP WITH TIME ZONE;

-- Continue for all tables...

Priority 5: Reconsider Foreign Key Removal¶

Current state: FK removed from app_workflow_meta_files

Alternative approach:

-- Instead of removing FK, use ON DELETE SET NULL
ALTER TABLE app_workflow_meta_files
ADD CONSTRAINT fk_workflow_meta_files_folder
FOREIGN KEY (workflow_folder)
REFERENCES app_workflow_meta(folder)
ON DELETE SET NULL;

-- Add check constraint for active templates
ALTER TABLE app_workflow_meta_files
ADD CONSTRAINT chk_active_has_valid_folder
CHECK (
    is_active = FALSE OR
    workflow_folder IN (SELECT folder FROM app_workflow_meta)
);

Benefits: - Maintains referential integrity for valid workflows - Allows orphaned templates (via NULL) - Provides data quality checks

CI/CD Integration¶

Current State: Unknown¶

Likely manual deployment based on migration approach

Recommended CI/CD Integration¶

With Alembic¶

# .github/workflows/deploy.yml
- name: Run Database Migrations
  run: |
    alembic upgrade head
  env:
    DATABASE_URL: ${{ secrets.DATABASE_URL }}

With SQL Migrations + Version Table¶

# .github/workflows/deploy.yml
- name: Run Database Migrations
  run: |
    for file in migrations/*.sql; do
      ./scripts/run_migration.sh "$file"
    done
  env:
    DATABASE_URL: ${{ secrets.DATABASE_URL }}

Migration Safety Checks¶

# Pre-deployment checks
- name: Check Database Migration Status
  run: |
    # Verify all migrations applied
    alembic current

    # Dry-run pending migrations
    alembic upgrade head --sql > migration.sql
    cat migration.sql

Rollback Strategy¶

Current State: No Rollback Support ❌¶

Problem: Cannot undo migrations if issues arise

Recommended Rollback Approach¶

With Alembic¶

# Rollback one migration
alembic downgrade -1

# Rollback to specific version
alembic downgrade abc123

# Rollback all migrations
alembic downgrade base

With SQL Migrations¶

Add rollback SQL to each migration:

-- Migration: Add new table
-- Rollback SQL:
--   DROP TABLE IF EXISTS new_table CASCADE;
--   DELETE FROM schema_migrations WHERE version = '20251013_01';

CREATE TABLE IF NOT EXISTS new_table (...);

Create rollback script:

# rollback_migration.sh
VERSION=$1
SQL_FILE=$2

# Extract rollback SQL from comments
ROLLBACK_SQL=$(grep -A 10 "Rollback:" "$SQL_FILE" | grep -v "Rollback:")

# Execute rollback
echo "$ROLLBACK_SQL" | psql $DATABASE_URL

# Remove from version table
psql $DATABASE_URL -c "DELETE FROM schema_migrations WHERE version='$VERSION'"

Testing Strategy for Migrations¶

Current State: No Migration Tests ❌¶

Problem: Cannot verify migrations work correctly

Recommended Testing Approach¶

1. Migration Test Suite¶

# tests/integration/test_migrations.py
import pytest
from sqlalchemy import create_engine, inspect

@pytest.mark.database
class TestMigrations:
    def test_migration_forward_backward(self):
        """Test migration can apply and rollback."""
        # Start with clean database
        # Apply migration
        # Verify schema changes
        # Rollback migration
        # Verify original state
        pass

    def test_migration_idempotency(self):
        """Test migration can be applied multiple times."""
        # Apply migration twice
        # Verify no errors
        pass

    def test_all_tables_exist(self):
        """Test all expected tables exist."""
        engine = create_engine(DATABASE_URL)
        inspector = inspect(engine)
        tables = inspector.get_table_names()

        expected_tables = [
            'app_processes', 'app_workflows', 'context_documents',
            'context_chunks', 'results_data', 'api_keys'
        ]

        for table in expected_tables:
            assert table in tables

    def test_vector_extension_installed(self):
        """Test pgvector extension is available."""
        # Query pg_extension for vector
        pass

2. CI/CD Migration Test¶

# .github/workflows/test-migrations.yml
name: Test Migrations
on: [push, pull_request]

jobs:
  test-migrations:
    runs-on: ubuntu-latest
    services:
      postgres:
        image: pgvector/pgvector:pg15
        env:
          POSTGRES_PASSWORD: postgres
        options: >-
          --health-cmd pg_isready
          --health-interval 10s
          --health-timeout 5s
          --health-retries 5

    steps:
      - uses: actions/checkout@v4

      - name: Run migrations on fresh database
        run: |
          psql -h localhost -U postgres < init.sql

      - name: Test migration rollback
        run: |
          alembic downgrade -1
          alembic upgrade head

      - name: Run migration tests
        run: pytest tests/integration/test_migrations.py

Migration Best Practices¶

DO ✅¶

1. Version Control All Migrations
2. Commit all migration files to git

3. Never edit applied migrations

4. Write Idempotent Migrations

5. Use IF NOT EXISTS, IF EXISTS

6. Safe to re-run

7. Include Rollback Instructions

8. Document how to undo migration

9. Provide rollback SQL

10. Test Migrations

11. Test on staging before production

12. Test rollback procedures

13. Document Migrations

14. Clear description
15. Date and author

16. Rationale for changes

17. Use Transactions

18. Wrap migrations in transactions when possible

19. Ensure atomicity

20. Add Indexes for Performance

21. Include indexes in migration

22. Consider concurrent index creation

23. Communicate Schema Changes

24. Notify team of breaking changes
25. Update documentation

DON'T ❌¶

1. Don't Edit Applied Migrations
2. Create new migration instead

3. Maintains history

4. Don't Remove Foreign Keys Lightly

5. Consider alternatives (SET NULL)

6. Maintain referential integrity

7. Don't Skip Version Tracking

8. Always track which migrations applied

9. Essential for production safety

10. Don't Deploy Untested Migrations

11. Test on staging first

12. Verify rollback works

13. Don't Mix Migration Approaches

14. Choose one: SQL or Alembic

15. Be consistent

16. Don't Forget Indexes

17. Add indexes for foreign keys

18. Consider query patterns

19. Don't Ignore Data Migrations

20. Test with production-like data

21. Consider data volume

22. Don't Hardcode Values

23. Use placeholders or environment variables
24. Allow for environment differences

Summary and Action Plan¶

Current State Assessment¶

Critical Issues¶

1. ❌ No migration version tracking - Cannot determine database state
2. ❌ No rollback support - Cannot undo problematic migrations
3. ⚠️ Dual migration systems - SQL + Alembic creates confusion
4. ⚠️ Removed foreign keys - Loss of referential integrity

Immediate Action Plan (This Week)¶

Option A: Adopt Alembic (Recommended)

# Day 1: Setup
pip install alembic
alembic init alembic

# Day 2: Configuration
# Edit alembic/env.py to use app.config.settings

# Day 3: Baseline
alembic stamp head  # Mark current state

# Day 4: Documentation
# Update CLAUDE.md with new migration process

# Day 5: First new migration
alembic revision -m "example new migration"

Option B: Add Version Tracking Table

# Day 1: Create version table
psql $DATABASE_URL < migrations/001_create_schema_migrations.sql

# Day 2: Record existing migrations
psql $DATABASE_URL -c "INSERT INTO schema_migrations ..."

# Day 3: Create runner script
chmod +x scripts/run_migration.sh

# Day 4: Test on staging
./scripts/run_migration.sh migrations/test_migration.sql

# Day 5: Documentation
# Update migrations/README.md

Short-term Goals (This Month)¶

1. Implement version tracking (Week 1)
2. Consolidate migration locations (Week 2)
3. Add migration tests (Week 3)
4. Standardize timestamp types (Week 4)
5. Document new migration process

Long-term Goals (Next 3 Months)¶

1. Reconsider foreign key removal (find alternative)
2. Implement automated migration testing in CI/CD
3. Create migration rollback playbook
4. Add database backup/restore process
5. Consider database-agnostic migrations (if multi-DB future)

Conclusion¶

The S5 Slidefactory database schema is well-designed and functional, but the migration management strategy needs improvement. The current manual SQL approach works but lacks critical features like version tracking and rollback support.

Key Recommendations:

1. Adopt Alembic for structured, trackable migrations
2. Add version tracking immediately (critical)
3. Consolidate to single migration location
4. Implement migration tests for safety
5. Standardize timestamp types across schema

Biggest Risk: Without version tracking, production databases may be in unknown states, making troubleshooting and upgrades difficult.

Biggest Opportunity: Switching to Alembic would provide professional-grade migration management with minimal effort, significantly improving database change safety and developer experience.

Recommended Next Step: Start with Alembic adoption this week. The schema is stable enough that this change can be made safely, and future development will benefit greatly from proper migration tooling.