Category: Best Practices

Introduction 20× faster. That’s what customers are seeing when AI-powered automation replaces the manual containerization work that used to consume days of senior engineer time per application. “AWS Transform took our applications from source code to running containers on EKS in just 4-8 hours per app. What used to take 8-10 days is now 20 […]

This post shares quantified results of the company Superhuman, which made AI to be the default way of work for their platform team. As a result, developer output rose 60%, 1,300 autonomous pull requests shipped in a single half, and experimentation rates tripled. This post looks at how the Superhuman’s platform team did it, what […]

Migration teams need a consistent way to right-size AWS Transform MGN replication servers when a wave includes many source servers. The challenge grows when source servers range from small systems to workloads with several tebibytes of provisioned disk capacity. AWS Transform MGN, formerly AWS Application Migration Service, uses lightweight Amazon Elastic Compute Cloud (Amazon EC2) […]

The first AWS Region in Saudi Arabia is on track for December 2026. Learn which workloads to evaluate, what data to prepare, and how an AWS Optimization and Licensing Assessment helps you compare costs before you commit.

Overview Many organizations still run Windows Server 2008 workloads that cannot be upgraded before migration due to application dependencies, vendor support constraints, or licensing limitations. When migrating these servers to AWS using AWS Transform MGN, the choice of target Amazon EC2 instance type determines which drivers the guest operating system needs to communicate with the […]

Introduction If you already work with an AI coding agent, you know how much they can do. Tools like Kiro, Claude Code, and Cursor read repositories, reason over code, and drive multi-step tasks from an IDE or terminal. They’re excellent general-purpose AI coding agents, built to help with everyday software development tasks. But planning and […]

Pratikkumar Chunawala, Principal Consultant, Professional Services, Amazon Web Services (AWS) Introduction This post presents a diagnostic framework for sustaining migration velocity, covering the velocity curve model, two structural forces that cause deceleration, and three leading indicators to detect the pattern early. Migration velocity stalls between waves 20 and 35 in most large-scale programs, not because […]

Most enterprise engineering organizations have deployed AI tooling broadly across teams. The per-team productivity gains are real. But end-to-end improvement hasn’t followed. Backlogs aren’t shrinking. Cycle times haven’t compressed. Tech debt is still growing. The tools aren’t broken. The problem is structural: each team accelerated independently, and the spaces between them are now the entire […]

Introduction In this blog post, we cover the post-cutover phase of an Oracle-to-PostgreSQL migration on Amazon Web Services (AWS), demonstrating how to transform a functional PostgreSQL system into an operationally excellent one. We walk through immediate validation, comprehensive observability, systematic performance optimization, disaster recovery validation, Oracle decommissioning, and the operational excellence foundation, including the continuous […]

Introduction In this blog post, we outline the target architectures and wave-based strategies needed to build functional PostgreSQL environments on Amazon Web Services (AWS), using Zulon City Insurance (ZCINS), a fictional carrier managing 42 Oracle databases, as a model for a successful transition. Once you have assessed your Oracle estate, as laid out in part […]