Migrating to Azure Cosmos DB

Table of Contents

Introduction

Migrating your existing data and applications to Azure Cosmos DB offers significant benefits, including global distribution, guaranteed low latency, elastic scalability, and multi-model support. This document guides you through various strategies and best practices for a successful migration.

Note: Carefully plan your migration to minimize downtime and ensure data integrity.

Migration Strategies

Choosing the right migration strategy depends on your application's architecture, downtime tolerance, and existing data sources.

Lift and Shift

This approach involves moving your existing database with minimal changes to Cosmos DB. It's suitable for simpler migrations where compatibility is high. You might use the Cosmos DB Data Migration Tool or Azure Data Migration Service for this.

Phased Migration

A more complex but often less disruptive strategy. You migrate specific parts of your application or data in phases, allowing you to test and validate each step. This often involves running your application against both the source and Cosmos DB simultaneously for a period.

Hybrid Approach

Combines elements of lift-and-shift and phased migration. You might migrate bulk data using a tool and then use application-level changes for ongoing synchronization or specific feature adoption.

Pre-Migration Checklist

Before initiating the migration, ensure you have the following in place:

  • Define Target Schema: Understand how your data will map to Cosmos DB containers and items.
  • Capacity Planning: Estimate required throughput (RU/s) and storage.
  • Choose API: Select the appropriate Cosmos DB API (SQL, MongoDB, Cassandra, Gremlin, Table).
  • Identify Data Sources: Document all data sources to be migrated.
  • Downtime Window: Determine acceptable downtime and plan accordingly.
  • Backup Strategy: Ensure you have reliable backups of your source data.
  • Testing Environment: Set up a dedicated environment for migration testing.
Tip: For relational databases, consider how to denormalize your data for optimal performance in Cosmos DB.

Migration Tools

Azure provides several tools to facilitate your migration:

Azure Data Migration Service (DMS)

A managed service that enables seamless migrations from multiple database sources to Azure data platforms with minimal downtime. DMS supports various source databases and can be configured for online (minimal downtime) or offline migrations.

Cosmos DB Data Migration Tool

A command-line utility that helps import data from various sources (like SQL Server, CSV, JSON files) into Azure Cosmos DB. It's useful for smaller datasets or offline migrations.


# Example command for Data Migration Tool (simplified)
<path_to_tool>\DataMigrationConsole.exe <source_config> <target_config>

Custom Scripts

For complex scenarios or specific transformations, you can write custom scripts using Azure SDKs (e.g., Python, Node.js, .NET) to read from your source and write to Cosmos DB.

Migration Process Steps

  1. Set up Azure Cosmos DB Account: Create your Cosmos DB account and desired database/container.
  2. Choose and Configure Tool: Select the appropriate migration tool and configure its connection strings and settings.
  3. Perform Initial Data Load: Use the tool to migrate your bulk data.
  4. Implement Change Data Capture (CDC): If performing an online migration, set up a mechanism to capture ongoing changes in the source.
  5. Synchronize Changes: Apply captured changes to Cosmos DB to keep it in sync.
  6. Cutover: Redirect your application traffic to Azure Cosmos DB.
  7. Monitor: Closely monitor performance and application behavior after cutover.

Post-Migration Validation

After the migration and cutover, it's crucial to validate the integrity and performance of your data in Cosmos DB:

  • Data Completeness: Verify that all expected data has been migrated.
  • Data Accuracy: Perform spot checks to ensure data accuracy.
  • Application Functionality: Test all application features that interact with the database.
  • Performance Benchmarking: Measure query performance and compare it against your targets.
  • Cost Review: Monitor your Cosmos DB costs and adjust RU/s as needed.
Warning: Thorough testing is paramount. Inadequate validation can lead to data loss or application failures.

Important Considerations

  • Network Latency: Ensure your application has low latency to your Cosmos DB region.
  • Throughput Provisioning: Start with provisioned throughput and adjust based on actual usage. Consider autoscale for dynamic workloads.
  • Partition Key Design: A well-designed partition key is critical for performance and scalability.
  • Indexing Policies: Optimize indexing policies to improve query performance.
  • Cost Optimization: Regularly review your RU/s consumption and storage to manage costs effectively.
  • Rollback Plan: Always have a documented rollback plan in case of unforeseen issues.

This guide provides a comprehensive overview of migrating to Azure Cosmos DB. For detailed instructions on specific tools and scenarios, please refer to the official Azure documentation and community resources.