<story><title>Open Sourcing Peloton, Uber’s Unified Resource Scheduler</title><url>https://eng.uber.com/open-sourcing-peloton/</url></story><parent_chain><item><author>warp_factor</author><text>I think you are right.&lt;p&gt;I think that what is going there is also a bit political. They started to grow their Engineering department so fast that they need to justify the headcounts now. So each team is trying to invent new projects all the time. Anecdotally, this was partially confirmed to me by a friend working there.&lt;p&gt;I said this before, but I still cannot understand why a service like Uber need so many engineers in the backend (multiple thousands). It is a complex distributed application, but nowhere near the scale or complexity of a Facebook or Google.</text></item><item><author>spyspy</author><text>Is it just me or is every big release from Uber just a custom rewrite of an existing technology? It seems their engineering department has a large not-invented-here attitude. I could be wrong - they&amp;#x27;re certainly large enough to have custom requirements that aren&amp;#x27;t met with what&amp;#x27;s on the market but the pattern is just becoming suspect.</text></item></parent_chain><comment><author>theon144</author><text>&amp;gt;I said this before, but I still cannot understand why a service like Uber need so many engineers in the backend (multiple thousands). It is a complex distributed application, but nowhere near the scale or complexity of a Facebook or Google.&lt;p&gt;Thank you so much, I thought I was going crazy. I understand the demands of running a service on the level Uber has, but well, for instance I can&amp;#x27;t imagine what kind of computational workload &amp;#x2F; infrastructure requirements would make developing your own resource scheduler a reasonable option - for a Taxi app? With non-essential (to the core product) machine learning?&lt;p&gt;Forgive me if I&amp;#x27;m ignorant, but what exactly does Uber engineering team do?&lt;p&gt;edit: On their blog I was able to find that they namely &amp;quot;forecast rider demand&amp;quot;, from a relatively small [0] article - that is, comapred to the article [1] about what essentially is &amp;quot;just&amp;quot; data visualization, which doesn&amp;#x27;t help my confusion much.&lt;p&gt;0 - &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;eng.uber.com&amp;#x2F;neural-networks&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;eng.uber.com&amp;#x2F;neural-networks&amp;#x2F;&lt;/a&gt;
1 - &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;eng.uber.com&amp;#x2F;maze&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;eng.uber.com&amp;#x2F;maze&amp;#x2F;&lt;/a&gt;</text></comment>
<story><title>Open Sourcing Peloton, Uber’s Unified Resource Scheduler</title><url>https://eng.uber.com/open-sourcing-peloton/</url></story><parent_chain><item><author>warp_factor</author><text>I think you are right.&lt;p&gt;I think that what is going there is also a bit political. They started to grow their Engineering department so fast that they need to justify the headcounts now. So each team is trying to invent new projects all the time. Anecdotally, this was partially confirmed to me by a friend working there.&lt;p&gt;I said this before, but I still cannot understand why a service like Uber need so many engineers in the backend (multiple thousands). It is a complex distributed application, but nowhere near the scale or complexity of a Facebook or Google.</text></item><item><author>spyspy</author><text>Is it just me or is every big release from Uber just a custom rewrite of an existing technology? It seems their engineering department has a large not-invented-here attitude. I could be wrong - they&amp;#x27;re certainly large enough to have custom requirements that aren&amp;#x27;t met with what&amp;#x27;s on the market but the pattern is just becoming suspect.</text></item></parent_chain><comment><author>chillacy</author><text>Maybe not at the same scale but imo their core system has a lot of tech challenges:&lt;p&gt;* Lots of realtime&lt;p&gt;* Resource scheduling problems&lt;p&gt;* Route optimization problems (especially with shared uber or shared lyft rides)</text></comment>