Best Practices for High-Risk AWS Migration

Migrations Done Right: Success Stories & Lessons Learned by Fernando Francisco Cristiani. “Migrations will be part of your career at some point. Usually because your architecture is not scaling well for your growing business” They are difficult! • run over a long period of time • very hard to estimate • scope is unpredictable • keeping yourself and your team motivated is challenging • explicit expectations management and building trust is crucial All Eyes on You • migration project is over schedule and/or budget • your team starts becoming the bottleneck • you are in the spotlight You will feel under the “eye of Sauron” It’s All About Trust • “getting things done consistently over a long period of time“ as the main source of building trust (doing what you said you would over & over) • split problem into business relevant increments • get things done & deliver consistently • communicate clearly Splitting Your Migration • avoid big bang! • chunk it up into business relevant increments in a way that aligns with the roadmap • build trust by delivering and delivering • leverage high priority projects to advance your migration • accept you will have two systems running in parallel • begin with the end in mind: define your final goal & make sure they contribute towards the goal in a genuine way • rain drop migrations: organic distributed on-the-fly migrations triggered by existing use cases (eg migrate when customer logs in) • make sure you know when you’re finished • good fit for use cases with expiration or regular cycles • pragmatic and simple way of migrating the most important use cases first Delivering Safely • emphasis on safely! Avoiding downtime and incidents • you will need to split your traffic as you go • release on non-prod environments • release code to prod with feature flag off • enable it in prod for some whitelisted users • gradually roll out to more users —> monitor & verify (rinse & repeat) • once it is released to all users, remove the feature flag (don’t forget about this!) • feature flags & repository pattern (or another pattern that encapsulates the data) • feature flags at gateway level (AWS Cloudfront + Lambda@Edge) • backend feature flag —> user routed to a different UI • passthrough (put new service in front of the old service) Communicate Clearly / Show Progress • visibility is essential. Anyone should be able to understand the progress of the migration at any time without asking you • proactively communicate progress on a regular basis • you might have to build custom tools to show progress (eg dashboards, UI) • make sure to choose a variable that shows progress in an accurate way Don’t Forget About • backups • decommission any unused services • delete unused code • delete all feature flags and associated code • delete any leftovers of migration framework • communicate explicitly and broadly at the end of the migration • celebrate!!

As a former AWS Technical Delivery Manager, I taught hundreds of customers how to migrate their workloads to AWS. Last week, I spent a few days working with individuals on a migration project, and I'm sharing a few tips below. First, 𝐀𝐖𝐒 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 (𝐀𝐃𝐒) removes the guesswork with EC2 recommendations to run your workloads to plan migrations with AWS Migration Hub by:  • Gathering Server and DB inventory for Database Migration Service.  • Server utilization data to generate rightsized EC2 instances.  • Map network communication patterns to understand application dependencies and group servers together.  • Export processes are running on the servers with agents installed. Second, 𝐀𝐖𝐒 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐌𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 (𝐃𝐌𝐒) makes it easy to securely assess, convert, and automate the migration of your databases and analytics workloads with network controls and real-time visibility. DMS minimizes operational disruptions to your applications by keeping source systems fully operational until the migration is complete. Third, 𝐀𝐖𝐒 𝐌𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐇𝐮𝐛 is a centralized platform that enables you to monitor your migration from planning to end-to-end execution, providing automated recommendations to accelerate your transformation. What I really like is these services are included in the Free and Paid plan tiers, allowing SMBs with AWS credits to evaluate their workloads for migration and modernization. 𝑾𝒆 𝒔𝒑𝒆𝒏𝒕 𝒍𝒆𝒔𝒔 𝒕𝒉𝒂𝒏 $10  to gather server information, EC2 recommendations, and test cutover. For 𝐀𝐈 𝐰𝐨𝐫𝐤𝐥𝐨𝐚𝐝𝐬 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐆𝐏𝐔-𝐚𝐬-𝐚-𝐬𝐞𝐫𝐯𝐢𝐜𝐞 𝐦𝐚𝐫𝐤𝐞𝐭, analysts project that small and medium-sized businesses will allocate more than half of their technology budgets to cloud services. With the cloud migration market expected to grow from $232B to $806B by 2029 (+28%), SMBs are leading the charge, especially those investing in AI, AIOps, and DevOps to modernize faster. Starting in November, 𝐀𝐖𝐒 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 takes things a step further as the first agentic AI service developed to accelerate enterprise modernization by deploying specialized AI agents to automate complex tasks, such as assessments, code analysis, refactoring, decomposition, dependency mapping, validation, and transformation planning, thereby dramatically reducing project timelines. The service helps reduce both modernization costs and ongoing maintenance expenses while identifying opportunities to eliminate legacy licensing costs for large enterprises. AWS Transform is the next leap bringing agentic AI into migration and modernization. If you’ve tested any of these new AI-driven migration tools, I’d love to hear your experience.

𝗧𝗵𝗲 𝗺𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗔𝗪𝗦 𝘁𝗵𝗮𝘁 𝗮𝗹𝗺𝗼𝘀𝘁 𝗸𝗶𝗹𝗹𝗲𝗱 𝘁𝗵𝗲 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 Your CTO announces a cloud migration. Everyone’s excited. AWS promises scalability, cost savings, and modern infrastructure. After six months of planning, you kick off the project. Eighteen months later, you’re spending triple the estimate, half the systems are still on-prem, and the team is ready to walk. 𝗪𝗵𝘆 𝗺𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗴𝗼 𝘀𝗶𝗱𝗲𝘄𝗮𝘆𝘀: Leadership treats cloud migration as a tech upgrade. It’s not. It changes how you operate, architect, and manage costs. Teams plan for the tech shift but ignore the operating model shift. Companies that survive treat migrations as business transformations. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝘁𝗿𝗮𝗽𝘀:  • Lift and shift first, optimize later. You just moved data center problems into AWS with higher costs.  • Six-month timeline. Missed the undocumented services and dependencies that derail cutovers.  • Assumed cost savings. No controls meant engineers spun up resources freely until the first $200K bill.  • Minimal process change. On-call, deployment, and monitoring all had to be redesigned. 𝗪𝗵𝗮𝘁 𝗯𝗿𝗼𝗸𝗲:  • Network latency. Cross-AZ hops slowed monolithic calls by seconds.  • Database licensing. Oracle on RDS turned a $40K annual license into $15K a month.  • Egress costs. Chatty microservices added $30K in data transfer fees.  • Security model mismatch. Public IPs and default passwords appeared when perimeter security failed.  • Skills gap. VMware experts struggled with AWS. Progress slowed drastically. 𝗪𝗵𝗮𝘁 𝘀𝗮𝘃𝗲𝗱 𝗶𝘁: Leadership paused, admitted the failure, and brought in AWS architects to coach and embed with teams. 𝗪𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝗲𝗱:  • Adopted hybrid for 18 months to build in-house expertise.  • Rearchitected apps into containers and moved to managed databases.  • Implemented FinOps early with tagging, alerts, and ownership.  • Formed a dedicated migration team so product velocity didn’t stall.  • Used phased cutovers with rollback options to de-risk each step. If you’re planning a migration, double your timeline and triple your budget. Not from pessimism, but experience, most companies underestimate both. The ones that don’t are the ones that make it. What was the most expensive surprise in your cloud migration? #AWS #awscommunity #kubernetes #CloudNative #DevOps #Containers #TechLeadership

I've ensured 100+ AWS migration projects succeed. Found key reasons why migrations could fail. (This is how we solved it, and you can too) 1. Ever-changing migration plans Constantly changing your migration plan, like 'Lift and Shift', 'Re-platforming', 'Re-hosting' etc., is a red flag. This inconsistency can lead to unforeseen dependencies and legacy system issues. To mitigate this, conduct thorough application dependency mapping and discovery before planning migration phases. 2. Inconsistent migration methods In a multi-tier web application migration project, using different methods like 'Re-hosting', 'Re-platforming', and 'Refactoring' for different applications will prove inefficient. It can lead you to integration issues and performance bottlenecks. Avoid it by proper standardization, defining clear target architectures, and grouping similar applications together. 3. Ineffective escalation process In a large data warehouse migration project, you can face issues with data consistency and integrity. These technical issues need to be promptly escalated to the right team for quick resolution. As a solution, establish a strict governance structure and communication plan to ensure blockers reach the right teams promptly. 4. Late emerging migration issues While doing CRM system migration, unforeseen data migration complexities can surface late, causing delays and significant rework. To address this, implement mechanisms like early design processes, tools, and escalation paths to identify issues sooner and maintain project momentum. 5. Lack of stakeholder alignment This can usually be faced while undergoing an ERP system migration. Stakeholder buy-in can prove to be critical. Without alignment, miscommunication between the migration team and business stakeholders can lead to roadblocks. Ensure alignment early by highlighting how AWS benefits specific objectives, fostering strong support throughout the migration process. Just remember that the future is unpredictable. But if planned well, then things are manageable! In the same way, Murat Yanar, Director at Amazon Web Services (AWS), once said, “You may not be able to predict the future needs of your business precisely. But the AWS cloud provides services to meet these ever-changing demands and help you innovate flexibly and securely.” Curious to know: What’s your biggest challenge when it comes to AWS migration? #aws #database #scalability #softwareengineering #simform

🚀 Cross-Account & Cross-Region Migration of Encrypted EC2 Instances In real-world cloud environments, migrating resources securely across AWS accounts and regions is often more complex than it appears, especially when encrypted volumes are involved. I recently faced such a challenge and successfully solved it using a combination of KMS, AMIs, and cross-region sharing techniques.   🔍 Project Scenario: EC2 instances were running in the Ireland region with encrypted volumes using a KMS key. The goal was to migrate those servers to a different AWS account in the UAE region. However, encrypted volumes cannot be directly shared across regions, and that’s where the real challenge begins.   🔧 My Approach: ✅ Created a new KMS key in the UAE region and shared it with the new account to control encryption in the target region. ✅ In the Ireland region, created an AMI from the existing encrypted EC2 instance. ✅ Copied that AMI from Ireland to UAE using the new KMS key for encryption during transfer. ✅ Once in the UAE, I shared the copied AMI with the target AWS account. ✅ Launched EC2 instances from the shared encrypted AMI in the new account.   🛡️ Why This Solution Was Needed: AWS does not allow direct sharing of encrypted AMIs across regions. You must first copy the AMI into the target region using a KMS key created in that region. Only after this step can you share the encrypted AMI with another AWS account securely.   📌 Key Services Used: This experience deepened my knowledge of secure migration practices, especially how to handle region and account boundaries in AWS while maintaining encryption policies. #aws #devops #ec2 #kms #migration #encryptedvolumes #awsproject #cloudengineering #awssecurity #muhammadmuzammil #devops #devopsengineer #cloud #cloudengineer #muzammilcloud

On prem to Cloud migration Step-by-Step AWS Cloud Migration Process 1. Plan the Migration Assessment: Identify the current environment (servers, databases, dependencies, and configurations). Inventory: Document application components and dependencies. Sizing: Determine AWS resources (EC2 instance types, RDS configurations, etc.) based on current usage. Network Design: Plan VPC setup, subnets, security groups, and connectivity. Backup Plan: Create a fallback plan for any issues during migration. 2. Prepare the AWS Environment VPC Setup: Create a VPC with subnets across multiple Availability Zones (AZs). Security: Configure security groups, IAM roles, and policies. Database Configuration: Set up an Amazon RDS instance or EC2-based database for the migration. AD Server: Use AWS Managed Microsoft AD or deploy your AD on EC2. Application Server: Launch EC2 instances and configure the operating system and required dependencies. 3. Migrate Database Backup: Create a backup of the current database. Export/Import: Use database migration tools (e.g., AWS DMS or native database tools) to migrate data to the AWS database. Replication: Set up database replication for real-time sync with the on-prem database. Validation: Verify data consistency and integrity post-migration. 4. Migrate Application Server Packaging: Package the application (e.g., as Docker containers, AMIs, or simple binaries). Deployment: Deploy the application on AWS EC2 instances or use AWS Elastic Beanstalk. DNS Configuration: Update DNS records to point to the AWS environment. 5. Migrate Active Directory (AD) Replication: Create a replica of the on-prem AD in AWS using the AD Trust setup. DNS Sync: Sync DNS entries between on-prem and AWS environments. Validation: Test authentication and resource access. 6. Test and Validate End-to-End Testing: Validate the complete environment (application, database, and AD). Performance Check: Monitor performance using CloudWatch and address any issues. Failover Testing: Simulate failure scenarios to ensure HA/DR readiness. 7. Cutover and Go Live Schedule Downtime: Coordinate with stakeholders and users for a minimal downtime window. Final Sync: Perform a final sync of the database and switch traffic to AWS. DNS Propagation: Update DNS settings to route traffic to the AWS environment (may take up to 24 hours). Monitoring: Continuously monitor AWS resources and performance post-migration. 8. Post-Migration Optimization Scaling: Implement auto-scaling policies for the application. Security: Regularly review and improve security configurations. Cost Optimization: Use AWS Cost Explorer to analyze and optimize resource usage. Downtime Considerations Database Migration: Plan a maintenance window of 2–4 hours for the final database sync and cutover. DNS Propagation: Approx. 15 minutes to 24 hours, depending on TTL settings. Use short TTLs during migration to minimize delays. #AWSMigration #CloudMigration #MinimalDowntime #DatabaseToAWS #ApplicationToAWS #ADToAWS