Category: Technical How-to

Amazon MQ for RabbitMQ is an AWS managed version of RabbitMQ. The service manages the provisioning, setup, and maintenance of RabbitMQ, reducing operational overhead for companies. Now, with Amazon MQ for RabbitMQ as an event source for AWS Lambda, you can process messages from the service. This allows you to integrate Amazon MQ for RabbitMQ […]

In this post, I show how the existing settings in the Alleycat application are not sufficient for handling the expected amount of traffic. I walk through the metrics visualizations for Kinesis Data Streams, Lambda, and DynamoDB to find which quotas should be increased.

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.

This post is written by Sebastian Lee, Solution Architect, Startup Singapore. Amazon Lightsail is a great starting point for those looking to get started on AWS. Lightsail is ideal for startups, SMBs, and hobbyist developers because it simplifies the deployment of instances, databases, load-balancers, CDNs, and even containers. However, you cannot track metrics beyond  CPU […]

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.

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.

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 written by Scott Howe – Sr. Secure Hybrid Edge Solutions Architect and Schneider Larbi – Sr. Partner Solutions Architect (VMware & Outposts) AWS Outposts is a fully managed offering that extends AWS infrastructure into your data center to facilitate workloads requiring local processing, data residency, minimal application latency, and 2-step migration journeys.  Due […]

This post is contributed by Scott Horsfield, Principal Solutions Architect for EC2 Scalability, Surabhi Agarwal,  Senior Product Manager for EC2 Auto Scaling, and Chad Schmutzer, Principal Developer Advocate for Amazon EC2. Customers have been using EC2 Auto Scaling to architect sophisticated, scalable, and robust applications on the AWS Cloud for over a decade. Launched in […]