Tag: Alex Casalboni

Organizations are adopting microservices architectures to build resilient and scalable applications using AWS Lambda. These applications are composed of multiple serverless functions that implement the business logic. Each function is mapped to API endpoints, methods, and resources using services such as Amazon API Gateway and Application Load Balancer. But sometimes all you need is a simple way to configure an HTTPS endpoint in front of your function without having to learn, configure, and operate additional services besides Lambda. For example, you might need to implement a webhook handler or a simple form validator that runs within an individual Lambda function. Today, I’m happy to announce the general availability of Lambda Function URLs, a new feature that lets you add HTTPS…

The AWS Well-Architected Framework has been helping AWS customers improve their cloud architectures since 2015. The framework consists of design principles, questions, and best practices across multiple pillars: Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization. Today we are introducing a new Sustainability Pillar to help organizations learn, measure, and improve their workloads using environmental best practices for cloud computing. Similar to the other pillars, the Sustainability Pillar contains questions aimed at evaluating the design, architecture, and implementation of your workloads to reduce their energy consumption and improve their efficiency. The pillar is designed as a tool to track your progress toward policies and best practices that support a more sustainable future, not just a simple checklist. The Shared…

Hundreds of thousands of customers use Amazon Simple Queue Service (SQS) to build message-based applications to decouple and scale microservices, distributed systems, and serverless apps. When a message cannot be successfully processed by the queue consumer, you can configure SQS to store it in a dead-letter queue (DLQ). As a software developer or architect, you’d like to examine and review unconsumed messages in your DLQs to figure out why they couldn’t be processed, identify patterns, resolve code errors, and ultimately reprocess these messages in the original queue. The life cycle of these unconsumed messages is part of your error-handling workflow, which is often manual and time consuming. Today, I’m happy to announce the general availability of a new enhanced DLQ…

As an organization facing business problems and dealing with data on a daily basis, the ability to build systems that can predict business outcomes becomes very important. This ability lets you solve problems and move faster by automating slow processes and embedding intelligence in your IT systems. But how do you make sure that all teams and individual decision makers in the organization are empowered to create these machine learning (ML) systems at scale, and without depending on other data science and data engineering teams? As a business user or data analyst, you’d like to build and use prediction systems based on the data that you analyze and process every day, without having to learn about hundreds of algorithms, training…