Category: *Post Types

In this post, I explain the all-time leaderboard logic in the Alleycat application. This is an asynchronous, eventually consistent process that checks batching of incoming records for new personal records. This uses Kinesis Data Firehose to provide a zero-administration way to deliver and process large batches of records continuously.

Beginning July 19, 2021, the Java 8 managed runtime in AWS Lambda will migrate from the current Open Java Development Kit (OpenJDK) implementation to the latest Amazon Corretto implementation.

This post is written by Fahad Mustafa, Cloud Application Architect, AWS Professional Services There are many ways to deploy ASP.NET web apps to AWS. Each with its own use cases and differing pricing models. But what if you have a small website and database that you must deploy rapidly, manage, and scale? What if you […]

This post focuses on ingesting data into Kinesis Data Streams. I explain the two approaches used by the Alleycat frontend and the simulator application and highlight other approaches that you can use. I show how messages are routed to shards using partition keys. Finally, I explore additional factors to consider when ingesting data, to improve efficiency and reduce cost.

This post is written by Pallavi Ravishankar a Senior Product Manager and Jason Nicholls an Enterprise Solutions Architect. Failure management is a key part of the reliability pillar within the AWS Well-Architected Framework. But things fail, and operating systems are no exception. An operating system update, application update, a misconfiguration, missing driver, or incorrect security […]

In this post, I introduce the Alleycat racing application for processing streaming data. I explain the virtual racing logic and provide an overview of the application architecture. I summarize the deployment process for the different parts of the solution and show how to test the frontend once the deployment is complete.

This post is the final part in a 3-part series on performance optimization in Lambda. The Lambda service makes frequent performance improvements in the underlying hardware, software, and architecture of the service. This post identifies the parts of the Lambda lifecycle where developers can make the most impact on performance.

This post is the second in a 3-part series on performance optimization in Lambda. It explains the effect of the memory configuration on Lambda performance, and why the memory setting also controls the compute power and networking I/O available to a function.

April 19, 2024: This post is considered deprecated. Updated guidance can be found at Architecting for Disaster Recovery on AWS Outposts Racks with AWS Elastic Disaster Recovery. This post is written by Scott Howe – Sr. Secure Hybrid Edge Solutions Architect and Schneider Larbi – Sr. Partner Solutions Architect (VMware & Outposts) AWS Outposts is a […]

The AWS Serverless team is excited to bring you the second annual serverless-first event, Serverless Live, on May 19. We’ll be livestreaming technical deep dives, demos, and live Q&A to help you get the most out of the cloud. The event opens with a keynote by Adrian Cockcroft, VP of Sustainability Architecture. It’s followed by […]