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After raising $18 million, social networking startup Yubl made a series of costly mistakes. Yubl hired an army of expensive contractors to build out its iOS and Android apps. Drama at the executive level hurt morale for the full-time employees. Most problematic, the company was bleeding cash due to a massive over-investment in cloud services.
This was the environment in which Yan Cui joined Yubl. The startup did have traction. There were social media stars who would announce on Twitter that they were about to go on Yubl, and Yubl would be hit by an avalanche of traffic. 50,000 users suddenly logging on to interact with their favorite celebrity was a significant traffic spike.
How do you deal with a traffic pattern like that? Serverless computing. AWS Lambda allowed the company to scale up quickly in a cost efficient manner. Yan began refactoring the entire backend infrastructure to be more cost efficient, heavily leveraging AWS Lambda.
Unfortunately, Yan’s valiant effort was not enough to save the company. But there are some incredible engineering lessons from this episode–how to build cost-effective, scalable infrastructure. It’s also a case study worth looking at if you work at a startup, whether or not you are an engineer.
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On a server less AWS lambda function, do you define what kind of hardware supports that lambda function? Like HPC machine or CPU machine, etc
No. You can only define the amount a memory the machine gets: 128MB to 1.5GB. CPU is proportional to memory; a 256MB function has double the CPU of a 128MB function.
Thanks. What are the number of CPU assigned to 128MB memory?
No clue. Read the docs.
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