How to Migrate Legacy Systems to Cloud

Working on a legacy system taught me a pattern I use now for every migration. 𝗦𝘁𝗿𝗮𝗻𝗴𝗹𝗲𝗿 𝗙𝗶𝗴 is a pattern you must know for legacy system migrations. This pattern incrementally replaces specific pieces of functionality with new applications and services. The first step (Stage 0) is to create a Facade that intercepts requests to the backend legacy system. Now, you can use this facade to route the requests to the legacy application or the new services. After that, the fun begins. You start migrating existing features to the new system. Consumers are not affected since they keep using the same interfaces. You can add new features with the facade routing users to the correct application. In the meantime, the legacy application continues working and taking care of the non-migrated features. Over time, all features migrate to the new system, and the legacy system is no longer necessary. The Strangler Fig pattern is a practical approach for migrating legacy systems. - Allow for gradual migration. - Low-risk transition to a new architecture. - Avoid disruption to end-users. - Maintain the integrity of the legacy system during the migration process. There are no more excuses now. Stop pushing that giant ball of mud. Start improving your legacy systems! Share your stories. 😉

𝗠𝗼𝗱𝗲𝗿𝗻𝗶𝘇𝗶𝗻𝗴 𝗟𝗲𝗴𝗮𝗰𝘆 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘄𝗶𝘁𝗵 𝗔𝗪𝗦: 𝗟𝗲𝘀𝘀𝗼𝗻𝘀 𝗟𝗲𝗮𝗿𝗻𝗲𝗱 Legacy applications can hold your business back: high maintenance costs, scalability challenges, and lack of agility. Modernizing with AWS offers a chance to unlock innovation, but it’s not without challenges. Here are some hard-earned lessons I’ve learned along the way: 1️⃣ 𝗕𝗿𝗲𝗮𝗸 𝗗𝗼𝘄𝗻 𝘁𝗵𝗲 𝗠𝗼𝗻𝗼𝗹𝗶𝘁𝗵 𝗦𝘁𝗲𝗽-𝗯𝘆-𝗦𝘁𝗲𝗽 Trying to refactor everything at once? That’s a recipe for disaster.  Instead, adopt an incremental approach: • Start by identifying business-critical components. • Migrate to microservices in stages using containers (ECS, EKS). • Introduce APIs gradually to reduce tight coupling. 2️⃣ 𝗖𝗵𝗼𝗼𝘀𝗲 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗔𝗪𝗦 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 AWS offers countless services, but not all are the right fit. Select based on your workload needs: • 𝗖𝗼𝗺𝗽𝘂𝘁𝗲: Lambda for event-driven tasks, ECS/EKS for containerized workloads. • 𝗦𝘁𝗼𝗿𝗮𝗴𝗲: S3 for static content, RDS or Aurora for relational workloads. • 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴: SQS and EventBridge for decoupling components. 3️⃣ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 Manual deployments and configurations increase complexity and risk. Use: • 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 (𝗜𝗮𝗖): Terraform or AWS CloudFormation to define environments. • 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀: Automate testing and deployment with AWS CodePipeline. • 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴: CloudWatch and X-Ray to gain visibility and ensure performance. 4️⃣ 𝗕𝗮𝗹𝗮𝗻𝗰𝗲 𝗖𝗼𝘀𝘁 𝗮𝗻𝗱 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 Modernization doesn’t mean throwing money at the cloud. Optimize costs by: • Right-sizing EC2 instances or shifting to serverless where possible. • Using Savings Plans and auto-scaling to keep costs under control. • Leveraging AWS Cost Explorer to identify waste and optimize spending. 5️⃣ 𝗜𝗻𝘃𝗼𝗹𝘃𝗲 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀 𝗘𝗮𝗿𝗹𝘆 Modernization is not just a tech initiative; it’s a business transformation. Engage teams early to align goals and expectations across development, operations, and leadership. 6️⃣ 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗤𝘂𝗶𝗰𝗸 𝗪𝗶𝗻𝘀 A successful modernization effort starts small, proves value, and expands. Identify low-risk, high-impact areas to deliver quick wins and build momentum. 💡 𝗣𝗿𝗼 𝗧𝗶𝗽: Modernization is an ongoing journey, not a one-time project. Continuously monitor, optimize, and adapt to stay ahead. What modernization challenges have you faced? #AWS #awscommunity

Migrating databases to cloud-native solutions is a significant step toward achieving better scalability, reliability, and cost efficiency. Recently, I completed a migration project where I moved a MariaDB database to an Amazon Aurora MySQL-Compatible database using AWS Database Migration Service (DMS). Here’s a simplified and educational breakdown of the process. 💡 Key Steps in the Migration Process 1️⃣ Setting Up the Target Database • Created an Amazon Aurora MySQL-Compatible database cluster using Amazon RDS. • Selected appropriate configurations for instance type, storage, and VPC security settings. • Ensured the database was private and accessible only within the designated network. 2️⃣ Preparing for the Migration • Configured a replication subnet group to define where the DMS replication instance would operate. • Launched a DMS replication instance to handle the migration tasks efficiently. 3️⃣ Creating Source and Target Endpoints • Source Endpoint: Configured to connect to the MariaDB database in the source environment. • Target Endpoint: Configured to connect to the Amazon Aurora database. • Verified connectivity for both endpoints before initiating the migration. 4️⃣ Running the Migration Task • Created a migration task in AWS DMS to replicate data from the source to the target database. • Configured table mappings to specify which schemas and tables to migrate. • Monitored the task for progress and completion. 5️⃣ Updating DNS Records • Updated DNS entries to redirect application traffic to the new Aurora database. • Verified the changes to ensure the application connected seamlessly to the target database. 6️⃣ Finalizing the Migration • Confirmed data consistency and application functionality with the new database. • Gracefully shut down the source database to complete the migration process. ⚙️ Tools and AWS Services Used • Amazon Aurora: A managed MySQL-compatible database offering high performance and reliability. • AWS Database Migration Service (DMS): Simplifies data migration with minimal downtime. • Amazon RDS: Automates database operations such as backups and patching. • Amazon VPC: Provides secure connectivity during migration. 🏗️ Best Practices for Database Migration • Plan the Migration: Define the source and target configurations, security, and access requirements. • Minimize Downtime: Use continuous data replication to ensure smooth transition with minimal application disruption. • Secure Connectivity: Use VPC and security groups to maintain strict access controls. • Test Thoroughly: Validate database functionality and application integration post-migration. I would love to mention some amazing individuals who have inspired me and who I learn from and collaborate with: Neal K. Davis Steven Moran Eric Huerta Prasad Rao Azeez Salu Mike Hammond Teegan A. Bartos Kumail Rizvi Benjamin Muschko #AWS #DatabaseMigration #CloudComputing #AmazonAurora #CloudArchitecture #DMS #RDS