Cache Incoming requests= The thing that I am always accused of. Use Edge 
Cache to make sure you don't need to serve people who are asking for the 
same thing.

Fault Tolerant writes is about determining how "race" your race conditions 
are, and being smart about your writes.

Common things I see, people want to increment something so they get count. 
Which is slow. Then they +1 and write. That is really slow.

I use Defer for a lot of writes when I know I wont have a read for a bit of 
time.  Google Bot just did something. Well Frak Google Bot, it's not a real 
user, delay that write until we have time for it. Defer. You have to look 
at your write types and determine the priority so you can decide how 
important it is to be fast, if you 100% need the write to complete, or if 
you are just doing something hoping people will use it later.

Write to a write Cache with the Marshall/pickle, if you need the data 
broken out as well, do a follow up and read the Serialized data and write 
the individual bits when you have more time.

Do reads in a similar way when ever possible use serialized data.



On Friday, July 20, 2012 9:39:43 PM UTC-7, Kyle Finley wrote:
>
> Hi Brandon,
>  
>
>> The people who don't know how to build APIs so that apps are task 
>> specific. Piss me off. Build modular. Dump frame works. Defer often. Be 
>> your own scheduler by shaping internal ops. Cache incoming. Cache reads 
>> cache writes. Manage threads. Use warmups. This is not rocket science.
>>
> OT, but how are you cacheing writes in a fault tolerant manner? Task 
> queue? I've been trying to develop a strategy for that. Also, what do you 
> mean by "Cache incoming"?
>
> Thanks,
>
> -Kyle
>  
>

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