Codetown ::: a software developer's community
15 members Latest Activity: May 6, 2018 Ever wonder how Google Translate works? It's computational linguistics! Join us here and learn all about it and more. Jim White will be our guide.…
16 members Latest Activity: Aug 21, 2015 Cloud Computing is "the next big thing". The recent JavaOne featured Cloud Computing more than any other technology. Come join us and explore /…
8 members
Latest Activity: Jun 5, 2014
Come join us here at the RDC JUG Town! Stanislas Matayo and the group in Kinshasa welcome you.
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Sub‑100-ms APIs emerge from disciplined architecture using latency budgets, minimized hops, async fan‑out, layered caching, circuit breakers, and strong observability. But long‑term speed depends on culture, with teams owning p99, monitoring drift, managing thread pools, and treating performance as a shared, continuous responsibility.
By Saranya Vedagiri
Uber engineers detailed how they evolved their storage platform from static rate limiting to a priority-aware load management system. The approach protects Docstore and Schemaless, Uber’s MySQL-based distributed databases, by colocating control with storage, prioritizing critical traffic, and dynamically shedding load under overload conditions.
By Leela Kumili
Continuous learning, adaptability, and strong support networks are the foundations for thriving teams, Matthew Card mentioned. Trust is built through consistent, fair leadership and addressing toxic behaviour, bias, and microaggressions early. By fostering growth, psychological safety, and accountability, people-first leadership drives resilience, collaboration, and performance.
By Ben Linders
Google DeepMind researchers have introduced ATLAS, a set of scaling laws for multilingual language models that formalize how model size, training data volume, and language mixtures interact as the number of supported languages increases.
By Robert Krzaczyński
Moumita Bhattacharya discusses the evolution of Netflix’s ranking systems, from the multi-model architecture to a Unified Contextual Recommender (UniCoRn). She explains how they built a task-agnostic User Foundation Model to capture long-term member preferences. Learn how they solve system challenges like high-throughput inference and the tradeoff between relevance and personalization.
By Moumita Bhattacharya
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