Joshua Harlow on Task Distribution
Explore expert insights from Joshua Harlow on task distribution in Python. Understand how to design scalable systems with queue-based approaches, create simple APIs, isolate network I/O, and build resilient applications prepared for failure scenarios.
We'll cover the following...
We'll cover the following...
Asking an expert
Following is a conversation with an experienced Python developer Joshua Harlow on the topic of task distribution.
Joshua Harlow
| Q: Hi Josh! Could you introduce yourself and explain how you came to Python? |
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| A: Well hi there! I grew up in upstate New York. I went to school at RIT (and prior to that Clarkson University as well as a NY state college) and graduated in 2007 with a Masters in Computer Science. During this time, I interned at IBM where I did some automation work using Jython and Intel, where I helped the graphics team by interconnecting Ruby and C#. While I was in college, I got very interested in distributed systems, and the interconnect/potential when combined with AI as well as a stint in language theory and applications. |
| After graduation, I came to work at Yahoo. After working on various projects such as the homepage (www.yahoo.com), I got recruited into a sub-team under the CTO organization where we were tasked with determining the cloud solution Yahoo should invest in and use. OpenStack was a nascent open source cloud technology back then, but it was what we thought had the most potential. Since OpenStack was being written entirely in Python, this is where I got my actual initiation into Python. Over time, I have come to enjoy Python, come to learn it deeply, been featured in a book on it and never looked back! |
| Q: What’s your experience with building large scale systems? |
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