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I had been using WordPress for well over a decade. It is a great product and has a lot of capabilities.
It is also heavy, and complex if you really only need a simple blog. I generally write very technical content
that makes using something like markdown preferable over a WYSIWYG or even HTML. I had still been hosting my blog and my domain names on GoDaddy,
back when that was the preferable choice. Having had a great deal of experience over the past number of years with AWS, I decided to look for a solution
that would be easy and utilizing AWS.
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For large complex application system communication between services as well as from the external world is the backbone of your system infrastructure. I can go on for a while going into the various options for these types of systems and my many experiences with each of them. However, I want to focus on the managed services that AWS offers for this purpose. I’m going to run through SQS/SNS, Amazon MQ, and Kinesis. Each of these deserve their own in-depth analysis and all truly have great merit on their own.
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I’m not going to talk about politics, but I do want to talk about this article I found on one of my many feeds. I will summarize this extremely briefly. This guy was so baffled by the election outcome and the poor pollster statistics and generally how this wasn’t predicted with machine learning and the sort.
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Recently I have been heavily using Apache Spark. For those of you who don’t know Spark is a very powerful system for working with data and parallel that is written in the Scala language. Scala is not new, but certainly on the “newer” end of the spectrum. Today new languages are coming out all the time so 12 years is fairly long. What many people find attractive about Scala, at least I do is the fact that it runs on the popular JVM. In fact a developer may be able to write code in Java and interact with code that was written in Scala. The challenge is striking the balance between closeness to Java and still providing whatever it is that the creators of the language hope to achieve.
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Right now AWS is the leader in cloud-computing, without a question. With DELL’s recent acquisition of EMC, which happens to own roughly 80% of the eminent virtualization company Vmware one can imagine they have their sights set on competing for a piece of the action as well. AWS is so popular that I recently saw companies such a Rackspace who used to be a real competitor to AWS now offers premier managed hosting of AWS. That is the kind of smart attitude shift that companies such as Microsoft have started doing. Now under the tutelage of Satya Nadella Microsoft has been making many wise moves all recognizing that they need to play nicely with other companies and recognize that big bad Redmond isn’t the only company in the ecosystem anymore. With that said most companies I speak to still treat AWS as being synonymous to the cloud, or at least the defacto cloud provider solution. There isn’t anything wrong with that, as long as you recognize what that really means.
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I am not a data scientist or expert in machine learning. However, I strongly believe the modern approaches to machine learning has been neither “intelligent” or “learning”. I am not the first person to point out this but perhaps I will have a novel approach that may add additional insight. An infant who has seen a dog and a cat a few times would likely be able to point to the correct animal when inquired which one is the dog. The same sort of task takes an incredible amount of samples to “learn” which is which. You see clear examples of just how unintelligent these systems are with big mistakes like this from Google identifying people with darker skin color as gorillas. In order to omit that result they had to make an exception. This isn’t the same as a child who ran across the street would be scolded by a parent. When a child is scolded the hope is that they understand the severe danger they can put themselves and therefore take additional caution. A neural network doesn’t make such a distinction, its merely a directive with a higher priority, since it really doesn’t “know” what its looking at.