Category: Technical How-to

Agentic AI systems are rapidly expanding beyond the digital world and into the physical, where AI agents perceive, reason, and act in real environments. As AI systems increasingly interact with the physical world through robotics, autonomous vehicles, and smart infrastructure, a fundamental question emerges: how do we build agents that leverage massive cloud compute for […]

Until recently, building AI agents meant wrestling with complex orchestration frameworks. Developers wrote elaborate state machines, predefined workflows, and extensive error-handling code to guide language models through multi-step tasks. We needed to build elaborate decision trees to handle “what if the API call fails?” or “what if the user asks something unexpected?” Despite this effort, […]

When we introduced the Strands Agents SDK, our goal was to make agentic development simple and flexible by embracing a model-driven approach. Today, we’re excited to highlight how you can use Claude 4’s interleaved thinking beta feature with Strands to further simplify how you write AI agents to solve complex tasks with tools. With a […]

In today’s fast-paced software development landscape, containerization has become an essential tool for building and deploying applications. With all the necessary tools and dependencies encapsulated in a container, developers can effortlessly set up and replicate development environments on various machines. The key steps involved in building and running containers typically include: Building container images using […]

Use HCL to orchestrate tasks that query AWS (and other services you regularly use), then act on the results.

We built a formal model of Cedar in Lean, and proved that Cedar’s components satisfy key safety and security properties.

Learn how to build a multicloud resource data lake populated by open source CloudQuery, how to normalize the data to perform analytics against it, and recommendations for how to implement CloudQuery to operate at scale.

Learn how to use the Backstage add-on from Amazon EKS Blueprints and the Backstage pattern from Amazon EKS Blueprints Patterns, to deploy a pre-built and pre-configured Backstage application.

Apache Airflow‘s active open source community, familiar Python development as directed acyclic graph (DAG) workflows, and extensive library of pre-built integrations have helped it become a leading tool for data scientists and engineers for creating data pipelines. Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a fully managed service that makes running open source […]

This is the second blog post in our series “Istio on EKS”, where we uncover Istio’s transformative benefits for microservices in Amazon Elastic Kubernetes Service (Amazon EKS). In our previous blog, Getting started with Istio on EKS, we explained how to set up Istio on Amazon EKS. We covered core aspects such as Istio Gateway, […]