Codetown ::: a software developer's community
I have a virtual event to announce that you can participate in online called the NightHacking Tour.
Steven Chin is a friend and colleague of mine. He's a Java…
ContinueAdded by Michael Levin on October 23, 2012 at 6:00am — No Comments
Got CDI? Wonder what dependency injection and JEE6 are all about? What the heck is Spring? RSVP, por favor. This is an event you won't want to miss! Check it out here and please RSVP so we'll know how much pizza to order. Invite your…
Added by Michael Levin on October 16, 2012 at 8:11am — 1 Comment
A good time was had by all at our October GatorJUG meeting. Kevin Neelands discussed Android Design Patterns in the context of his recent work on the job with an Android app. The lessons learned he presented were not just interesting but huge timesavers for him. They also dramatically…
Added by Michael Levin on October 15, 2012 at 7:00am — No Comments
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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.
Check out the Codetown Jobs group.

Grab updated its internal platform to monitor Apache Kafka data quality in real time. The system uses FlinkSQL and an LLM to detect syntactic and semantic errors. It currently tracks 100+ topics, preventing invalid data from reaching downstream users. This proactive strategy aligns with industry trends to treat data streams as reliable products.
By Patrick Farry
Serving Large Language Models (LLMs) at scale is complex. Modern LLMs now exceed the memory and compute capacity of a single GPU or even a single multi-GPU node. As a result, inference workloads for 70B+, 120B+ parameter models, or pipelines with large context windows, require multi-node, distributed GPU deployments.
By Claudio Masolo
Karrot replaced its legacy recommendation system with a scalable architecture that leverages various AWS services. The company sought to address challenges related to tight coupling, limited scalability, and poor reliability in its previous solution, opting instead for a distributed, event-driven architecture built on top of scalable cloud services.
By Rafal Gancarz
Sharing your work as a software engineer inspires others, invites feedback, and fosters personal growth, Suhail Patel said at QCon London. Normalizing and owning incidents builds trust, and it supports understanding the complexities. AI enables automation but needs proper guidance, context, and security guardrails.
By Ben LindersThe article shares goals and strategies for scaling cloud and distributed applications, focusing on lessons learned from cloud migration at Chase.com at JP Morgan Chase. The discussion centers on three primary goals and the strategies addressing the goals, concluding how these approaches were achieved in practice. For those managing large-scale systems, these lessons provide valuable guidance!
By Durai Arasan
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