Codetown
Codetown ::: a software developer's community
November 2008 Blog Posts (5)
Mule, Codetown, Success
We'll rely on Codetown for posting events and RSVPs, so please keep an eye on it and RSVP for upcoming events.
There's a Notes section that has some hints about using Codetown. Please look around and see what is here. I think you'll like it a lot!
In January, we have Carol McDonald of Sun coming with a great talk. Details in the Events… Continue
Added by Michael Levin on November 21, 2008 at 10:06am — 1 Comment
FYI -- the final version of NetBeans 6.5 was released this morning
Introduction to NetBeans IDE 6.5
http://www.netbeans.org/kb/docs/ide/nb65-intro-screencast.html
In this screencast, Sridhar Reddy shows new Java developers NetBeans IDE 6.5 editor features and gives a short introduction on how to edit, compile… Continue
Added by Michael Levin on November 19, 2008 at 5:11pm — No Comments
Øredev features Josh Marinacci on JavaFX
Malmo, Sweden: Added by Michael Levin on November 16, 2008 at 5:00pm — No Comments
LA JUG looking for presentations
Added by Michael Levin on November 16, 2008 at 4:30pm — 1 Comment
nbPython a go!
http://codesnakes.blogspot.com/2008/11/python-in-netbeans-is-go.html
Wednesday, November 12, 2008
Python in Netbeans is a go!!!!
After a 6 months of development. nbPython has been given the green light to be release as the official python build for Netbeans. The EA release will be… Continue
Added by Michael Levin on November 13, 2008 at 8:00am — No Comments
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Happy 10th year, JCertif!
Notes
Welcome to Codetown!
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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InfoQ Reading List
OpenCode: an Open-source AI Coding Agent Competing with Claude Code and Copilot
Open-source AI coding tool OpenCode features a native terminal-based UI, multi-session support, and compatibility with over 75 models, including Claude, OpenAI, Gemini, and local models. In addition to its CLI tool, OpenCode is also available as a desktop app and and an IDE extension for VS Code, Cursor, and other tools.
By Sergio De SimoneGetting Feedback from Test-Driven Development and Testing in Production
Teams rely on strong unit and integration tests instead of end-to-end tests. Using TDD, pair programming, and good design, they ship small changes often, test in production for real feedback, and use feature toggles to reduce risk, Ola Hast and Asgaut Mjølne Söderbom mentioned in their talk about continuous delivery with pair programming.
By Ben LindersGoogle Pushes for gRPC Support in Model Context Protocol
Google Cloud is bridging a critical gap for enterprises by introducing a gRPC transport package for the Model Context Protocol (MCP), enhancing integration for businesses already using gRPC. This game-changer reduces development friction, ensuring AI agents seamlessly connect with existing services while boosting performance and efficiency. Join the evolving landscape of AI integration!
By Steef-Jan WiggersLinkedIn Re-Architects Service Discovery: Replacing Zookeeper with Kafka and xDS at Scale
LinkedIn's engineering team successfully upgraded its legacy ZooKeeper service discovery platform to enhance scalability and performance. By leveraging Apache Kafka and the xDS protocol, the new architecture enables eventual consistency, supports multiple languages, and allows migration without downtime. Post-upgrade, latency vastly improved, facilitating hundreds of thousands of app instances.
By Patrick FarryPresentation: Beyond the Warehouse: Why BigQuery Alone Won’t Solve Your Data Problems
Sarah Usher discusses the architectural "breaking point" where warehouses like BigQuery struggle with latency and cost. She explains the necessity of a conceptual data lifecycle (Raw, Curated, Use Case) to regain control over lineage and innovation. She shares practical strategies to design a single source of truth that empowers both ML teams and analytics without bottlenecking scale.
By Sarah Usher
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