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Cloud Computing Village Discussions (7)
| Discussions | Replies | Latest Activity |
|---|---|---|
What's the difference between Grid computing and Cloud ComputingI don't clearly catch the difference betwenn these two concept. Someone told me that the essential différence is that the cloud computing g… Started by Hervé-greg MOKWABO |
5 |
Nov 29, 2011 Reply by Hervé-greg MOKWABO |
Searching for Cloud architectureAfter reviewing architecture models from several vendors and industry organizations, I believe we are witnessing an early evolutionary peri… Started by Chris Haddad |
0 | Nov 25, 2011 |
EnsembleEnsemble: service orchestration for the cloud (my work for Ubuntu Server) http://fewbar.com/2011/06/so-what-is-ensemble-anyway - via Jim Ba… Started by Michael Levin |
1 |
Nov 1, 2011 Reply by Michael Levin |
Shameless Plug: New ApplicationHey everyone, Don't know if you remember me but I did the Android class last year. Anyway I just published my first app. It is a pay app b… Started by Jackie Gleason |
1 |
Oct 25, 2011 Reply by Michael Levin |
Issues to Consider with Cloud ComputingThinking about Cloud Computing raises some concerns. Security is one concern that looms in many minds. What are some issues and how can we… Started by Michael Levin |
0 | Oct 25, 2011 |
Advantages of Cloud ComputingAny time we use devices that are detached, remote, or somehow "managed" outside our normal environment, we realize advantages. Some obvious… Started by Michael Levin |
0 | Oct 25, 2011 |
What is Cloud Computing?What is Cloud Computing? Of course, the name Cloud Computing is a metaphor that describes the grouping together of data in a virtual storag… Started by Michael Levin |
0 | Oct 25, 2011 |
Happy 10th year, JCertif!
Notes
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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
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By Steef-Jan WiggersArticle: Scaling Java-Based Real-Time Systems: The Hidden Tradeoffs of Event-Driven Design
Event-driven architecture promises scalability, but in Java-based real-time systems the tradeoffs only surface in production. Drawing on a Java/Kafka contact center platform handling 80k BHCC across 10k agents, this article details where the design breaks down—state management, partition limits, deduplication, JVM tuning, cascading consumer failures—and the Redis-backed patterns that fixed each.
By Sagar Deepak Joshi
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