Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.
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they are comprehensive they are constantly improving they srw well documents
1. Serverless AI services are awesome 2. Its nice to be able to point software engineers to AI services, so they dont have to be a data scientist. 3. Its nice that a lot of the AI services are trained with Amazon.com ground truth data and we dont have to bring that growth truth data to train the algorithms.
usability and blog post, documentation
sometimes oversold can be expensive oprational complexity
1. AWS Blog posts and cloudformation scripts associated with them dont work and are not kept up when the technology changes. 2. A number of the AI services arent fully baked. They are functional enough to demonstrate for reInvent purposes and simple use cases, but you find out there are a lot of restrictions/limits when you try to use them. 3. Limits are too restrictive for some services. For instance AWS Forecast has a 5GB input dataset limit. In my world that is nothing when dealing with 100s of TBs. The limits make it so that out of the box it wont work for my use case at times. 3.
complexity that comes with integration