Cloud Cost Optimization

Generative AI in banking means using models that produce language, summaries, and answers rather than models that only score or classify. A credit model tells you a number. A generative model reads fifty pages of a prospectus and writes the two-paragraph summary an analyst would have written by hand. Vietnamese banks moved past the pilot […]

Amazon SageMaker is the AWS platform for building, training, and running machine learning models on managed infrastructure. You supply the data and the model code. AWS supplies the GPU clusters, the container orchestration, the scaling, and the endpoint your application calls. The name covers more ground than it used to, which is where most of […]

Amazon Aurora is a relational database engine that AWS built for its own infrastructure, compatible with MySQL and PostgreSQL, and delivered through the same managed service that runs Amazon RDS. Most teams meet it at a specific moment. The RDS instance that has been fine for two years starts to strain under peak traffic, and […]

The AWS Well-Architected Framework is a set of design principles and evaluation questions that AWS uses to assess whether a cloud workload is built soundly. It organises that assessment into six pillars: operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. Most teams meet the framework for the first time during an audit, a […]

RAG stands for retrieval-augmented generation. It is a design pattern where an application searches your own documents first, then hands the relevant passages to a large language model as context, so the answer comes from your data instead of the model’s training set. It solves two problems at the same time. Models go stale the […]