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Google Cloud Architect
Image: coursera.org
#1034 overall

Google Cloud Architect

Coursera

1 recommender · 1 thread · recommended in 1 year, 2018 · score 0.7

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A Coursera course series from Google Cloud aimed at learning how to design and architect solutions on Google Cloud Platform. Commenters point to it as a structured path alongside Google's free documentation and codelabs.

One commenter recommends it alongside the data engineering course as a way into Google Cloud for individual learners.

Web & Mobile Developmentintermediatefreemiuminteractive MOOC#google cloud#cloud architecture#gcp#coursera#cloud certification

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What commenters said (1)

  1. Recommendsfunkjunky2018in “Ask HN: Which cloud behemoth is best for individual learning?”

    I'll say this in GCP's favor: it has an extremely generous free tier and a $300 credit for signing up, a ton of fantastic tutorials and walkthroughs at https://codelabs.developers.google.com, and they seem to be at the forefront of most major R&D advances in cloud computing over the last couple of decades, so you'll probably see new things there first (managed kubernetes, Spanner, and a wealth of fancy machine learning shit just to start).

    I also recommend going through the "Google cloud architect" and "data engineering on Google cloud" courses on Coursera: https://www.coursera.org/googlecloud.

    The docs have gotten much better over the years, but you have to put in the time to really dive into them. They are essential reading, so put in the time.

    Also the developer tools, (web dashboards, CLI tools, APIs, code libraries, etc.) seem to be light years better than what I've experienced with AWS and Azure.

    Disclaimer: I used to work Platinum support for Google cloud. Now I'm an SRE at a company that uses AWS, and I play around with Azure here and there to see what's what

    Whatever you decide to do, I recommend coming up with one idea for an application that can start simple but grow into something complex, start from the bottom with a simple deployment, and add pieces as you learn them so you can understand how everything fits together in the grand scheme of things. I picked election/voting software, which is good because it starts at just simple vote counting over an API, then grew to teach me auto scaling, data pipelines, machine learning analysis, etc.

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