We’ve talked about image optimization before, but this episode is different. First of all, Jack Levin was Google’s very first Network Engineer and hearing his stories on that alone is worth it. Second, he’s built an impressive cloud engine which he says can process images in 25ms. This speed, obviously, has a lot of benefits, but how is it possible? That’s the main topic of this episode.
As you’ll see, this engine actually isn’t even a service! It’s an AMI image you can install on AWS EC2 machines. So on top of the technical details, we can also learn a valuable business lesson. Overall, a super interesting interview.
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6:50 – Can you tell us about your background? You worked at Google as a first network engineer?
9:20 – Did you have a lot of experience before working there?
11:40 – Did you found ImageShack after leaving Google?
15:50 – You saw the imgix interview and you reached out to me to talk about your new company. Why did you contact me about this new product?
21:53 – What instance type is required to run this?
22:07 – So you went to Amazon and optimized this transformation for their CPUs, hardware, and machine types. Is that why you have to start with a minimum of M3?
22:35 – So that makes a huge difference in speed?
24:00 – Did you learn about all this from ImageShack or from Google?
29:15 – As an example, is the image processed on the fly and saved in a bucket that you specify or is it always processed on the fly?
30:58 – Are you talking about the machine cache…the same machine that transcoded the image will hold it into memory or on disc? Is that what you’re calling the cache?
33:20 – How do you tell Imagizer what image you need?
34:20 – So you’re just storing the largest resolution that you want…so you have, for example, a mobile device or retina display comes in, you can tell Imagizer which image or format and resolution you need and it spits it out to the client?
35:20 – I know that now you don’t have infrastructure. Will it make sense at one point to have a central location that customers can plug into instead of spinning up their own EC2 machines? Are you more interested in staying a software company without the headache of scaling infrastructure?
37:10 – You mentioned using the Google Cloud Compute Engine or Azure, or Digital Ocean or software. Do you plan on adding that on in the future?
38:40 – How do you measure this kind of performance? What kinds of tools measure the beginning and end of processing?
40:25 – If you have someone that is interested in learning more about images as you have, how would you recommend they get started?
43:25 – You were at CES announcing the product weren’t you? Did you see some crazy things?
43:55 – That goes back to recognition and autopilots for vehicles, recognizing objects, animals, people, roads. That’s huge isn’t it?
45:15 – Are you setting up Ambrella to be ready for these kinds of recognitions. You’re really intimate with image processing and recognition. Could that potentially be part of your future?
46:24 – Where did you get this great interest in performance? Was it the culture at Google or has it progressively grown by being a user and seeing the need for really fast websites or really fast apps?
49:04 – If you could give advice to anyone that’s trying to start a career or take their established career to the next level, what would you say to them?
50:25 – When you first started your career, did you see the work at Google and ImageShack as really interesting or did you work on it because you thought it was going to be big?
52:40 – If people want to reach out to you, or check out your products under Ambrella or Imagizer, how do you recommend they do that?
Thanks for watching :). Please leave me a comment and let me know what you thought!
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