Category Archives: AWS Service

A vector database is a database that stores data as vectors, which are long lists of numbers that capture the meaning of text, images, or audio. It lets you search by meaning. Ask for “cheap flights to the beach” and it can find a document titled “budget trips to coastal cities,” even though the two […]

MLOps (machine learning operations) is a set of practices and tools that helps teams build, deploy, monitor, and update machine learning models in a reliable, repeatable way. It takes the ideas behind DevOps, such as automation, version control, and continuous delivery, and applies them to machine learning. The goal is simple. Get good models into […]

Amazon EKS (Amazon Elastic Kubernetes Service) is a managed service from AWS that runs Kubernetes for you. AWS looks after the “brain” of the cluster, and your team focuses on deploying and running applications in containers. In short, EKS gives you standard Kubernetes on AWS without the job of building and patching the control servers […]

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 […]

AWS cost optimization means paying for what your workloads actually use and cutting the waste that builds up everywhere else. There is usually a lot of waste. Studies put the average organization’s wasted cloud spend at around 30%, and that figure climbs quietly as infrastructure grows. The savings are well within reach. Teams that work […]

AWS Glue is Amazon’s serverless data integration service. It pulls data from different sources, cleans it up, and loads it somewhere your team can actually query, without anyone provisioning or managing a server. That’s the short version. The longer version involves a few moving parts: crawlers, a data catalog, Spark-based jobs, and a handful of […]