The actual cost is now $206 and over $1000 forecasted, it makes me think twice about using pay-per-use services in the future. One little mistake can cost a lot of money, the budget notifications were very late so there was very little I could do against it.
Right now I’m continuously refreshing the billing page on Amazon, hoping it wont go any higher – I probably wont be sleeping much tonight.
I’m not saying serverless is bad, but you should be very careful with it. Keep an eye on your logs, test everything again and again. Set up a budget alarm, even though I still ended up with $206 costs, it could have been much much worse without one.
.. This is probably the most stupid thing I ever did. One missing
return;ended up costing me $206.
- You get a 30-second notice before getting evicted. Save your stuff and move to another instance.
- Managed Instance Groups reclaim your instances after they’ve been preempted for you.
If Amazon wanted to stimulate creativity among its developers, it shouldn’t try to guess what kind of services they might want; such guesses would be based on patterns of the past. Instead, it should be creating primitives — the building blocks of computing — and then getting out of the way.
.. GOOGLE IS A PRODUCT COMPANY
Google, meanwhile, has never really been a platform company; in fact, while Google is often cast as Apple’s opposite — the latter is called a product company, and the former a services one — that only makes sense if you presume that only hardware can be a product. A more expansive definition of “product” — a fully realized solution presented to end users — would show the two companies are in fact quite similar.
.. this is the exact opposite of the model employed by not just Amazon but also Microsoft, the pre-eminent platform company of the IT era: instead of integrating pieces to deliver a product AWS went in the opposite direction, breaking down all of the pieces that go into building back-end services into fully modular parts; Microsoft did the same with its Win32 API. Yes, this meant that Windows was by design a worse platform in terms of the end user experience than, say, Mac OS, but it was far more powerful and extensible, an approach that paid off with millions of line of business apps that even today keep Windows at the center of business. AWS has done the exact same thing for back-end services, and the flexibility and modularity of AWS is the chief reason why it crushed Google’s initial cloud offering, Google App Engine, which launched back in 2008. Using App Engine entailed accepting a lot of decisions that Google made on your behalf; AWS let you build exactly what you needed.
.. Where Kubernetes differs from Borg is that it is fully portable: it runs on AWS, it runs on Azure, it runs on the Google Cloud Platform, it runs on on-premise infrastructure, you can even run it in your house.
.. the potential impact of Kubernetes specifically and container-based development broadly is to make irrelevant which infrastructure provider you use. No wonder it is one of the fastest growing open-source projects of all time: there is no lock-in.
.. its reliance on links instead of simply page content — meant that as the web got bigger Google, unlike its competitors, got better.
.. when you can access any service, whether that be news or car-sharing or hotels or video or search etc., the one that is the best will not only win initially but will see its advantages compound.
.. Kubernetes was Google’s attempt to effectively build a browser on top of cloud infrastructure and thus decrease switching costs
.. superior machine learning offerings can not only be a differentiator but a sustainable one: being better will attract more customers and thus more data, and data is the fuel by which machine learning improvement comes about. And it is because of data that Google is AWS’ biggest threat in the cloud.
.. in TensorFlow and Monetizing Intellectual Property Google’s willingness to share its approach was an implicit admission that its superior data and processing infrastructure was a sustainable advantage.
.. the creation of the Google Cloud Machine Learning group .. they are tasked with productizing Google’s machine learning capabilities.
.. it’s often easier to change the rules of competition than to change your fundamental nature as a company.
.. a new business model — sales versus ads — and build up the sort of organization that is necessary for not just sales but also enterprise support.
.. Microsoft is likely to prove particularly formidable in this regard: not only has the company engaged in years of research, but the company also has experience productizing technology for business specifically; Google’s longstanding consumer focus may at times be a handicap. And as popular as Kubernetes may be broadly, it’s concerning that Google is not yet eating its own dog food.