Article: AWS Lambda Under the Hood
InfoQ Articles
MARCH 14, 2024
Mike Danilov, a senior principal engineer at AWS, presented on AWS Lambda and what is under the hood during QCon San Francisco 2023.
InfoQ Articles
MARCH 14, 2024
Mike Danilov, a senior principal engineer at AWS, presented on AWS Lambda and what is under the hood during QCon San Francisco 2023.
InfoQ Articles
MARCH 21, 2024
Explore Cloudflare's distributed PostgreSQL clusters and learn how a cross-region architecture ensures resilience. Discover how data storage and access at the edge deliver massive performance gains by reducing location-sensitive latency and why architecting for degraded states is much harder than for failure states.
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InfoQ Articles
MARCH 27, 2024
Only doing product-led work can lead to an unmaintainable system with lots of downtime. Unfortunately, getting time to work on the things that would prevent that can be challenging. Engineering roadmaps balance many competing demands, and the people making the decisions aren’t always the closest to the code.
InfoQ Articles
MARCH 22, 2024
Cellular architecture is a design pattern that helps achieve high availability in multi-tenant applications. The goal is to design your application so that you can deploy all of its components into an isolated "cell" that is fully self-sufficient. It can benefit your customers regarding availability and ensure you hit your SLAs. By Chris Price
InfoQ Articles
MARCH 25, 2024
In this article Diwan shared how the Netflix membership team does distributed systems: the architecture bets, technology choices, and operational semantics that serve the needs of Netflix’s ever-growing member base. By Surabhi Diwan
InfoQ Articles
MARCH 26, 2024
Aayush Mudgal describes how Pinterest serves advertisements. He discussed in detail how Machine Learning is used to serve ads at large scale. He went over ads marketplaces and the ad delivery funnel, the ad serving architecture , and two of the main problems: ads retrieval and ranking.
InfoQ Articles
FEBRUARY 15, 2024
This article explores how generative AI affects fraud detection by reducing false positives and dynamically adapting to changing fraud patterns. This combination offers a potent preventive solution when integrated with machine learning. The efficacy and scalability of fraud prevention initiatives are enhanced by this innovative approach.
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