Singularity Prosperity

Singularity Prosperity

Hi, thanks for tuning into Singularity Prosperity. This post is the tenth in a multi-part series discussing computing. In this post, we’ll be discussing what cloud computing is and the fundamental change it brings in how we view and think about computing. To better understand the massive revolution, cloud computing will bring and is bringing to the field of computing, let’s first go back in time and view a similar revolution with electricity. Before the height of the industrial revolution, electricity had to be generated in the house. This had many downsides:

every worker lost to generating electricity was one less to make the factory more productive, and scalability was a significant issue, at times when production of the factory went up, there wouldn’t be enough generated electricity, causing power outages and a loss of production. Thus, often more electricity that needed was produced, which was quite costly.

Then in the 1880s, Thomas Edison, founded the Edison Illuminating Company, turning electricity into a utility. In other words, something that could be switched on and off whenever desired, delivering the exact amount of power needed at a cost per unit, in the case of electricity, watts. Electricity as utility allowed for mass productivity increases. It sparked further exponential growth in the industrial revolution, referred to as the second industrial revolution, this because power as utility lowered the barrier to starting and maintaining a business, thus leading to more innovation.

Coming back to the present day, this analogy has strong correlations to transformations seen in computing. When running a website or application in the pre-cloud computing days, every individual business with an online presence had to maintain servers that allowed users to access their site, and this is referred to as hosting.

Like with electricity, sometimes more users will access the site, and sometimes there will be little to no users on the site. To prevent website crashes on periods of high traffic which therefore equated to lost users and customers, more servers than needed often had to be purchased. These servers are very costly, racking up bills even when they aren’t used to full capacity. Also like the electricity analogy, having a large team of sysadmins, network engineers, etc. takes away productivity from the real goal a business is trying to achieve, therefore making the barrier to a scalable business high and costly.

Now, with cloud computing, we are witnessing a revolution in how computing power is allocated; in other words, viewing computing as a utility. Cloud computing has seen an incremental evolution over the past decade, in large part due to the exponential increase in computing performance, with cloud computing currently growing at a rate of 23 percent per year.

Before discussing the primary types of cloud hosting or computing, what exactly is it? Well, the best way to think about it is to think about actual clouds. A cloud is formed via a dense cluster of water molecules that appear as a single object from a distance, thus taking this concept, cloud computing refers to a dense cluster of computers working together that appear as a single computing resource.

There are many companies in the cloud computing race now, to list some of the biggest cloud providers: Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud – the list can go on and on. Mostly, the cloud services these companies provide are

through vast data centers made for public use. As discussed previously, for a business to manage its online presence, in-house servers and maintenance was required, which racked up costly bills and was counterproductive to the true goals of the business.

This is where the first type of cloud computing came into play: Infrastructure-as-a-Service, IaaS, where the hardware, in other words, the hosting environment was abstracted away. Like with an electricity meter, businesses only pay the cloud provider for the exact amount of computing power used. So, when there is a heavy load on a cloud-hosted site, more is charged due to increased computing demand, and with less traffic, significantly less is charged.

The next type of cloud computing is, Platform-as-a-Service, PaaS, this is where the operating system and software backend is abstracted away. While IaaS provides the infrastructure for hosting an application, everything else involved in backend development is not covered.

This is the role PaaS fills, backend services, including data management in the form of databases and middleware, which is the plumbing between the components of an application to make sure everything works together.

The last type of cloud computing we’ll discuss is, Software-as-a-Service, SaaS, this is where the software runtime is abstracted away, essentially a layer in the cloud for program execution. This part of the cloud affects us, the consumers, the most, allowing our devices to do minimal processing when running an application because processing is instead done in the cloud and results deliver to our devices.

The best analogy for these 3 layers is a cake: IaaS is the large base of a cake, PaaS is the frosting that covers the cake and SaaS is the eye-catching candle on top that people see first. Over the years, the boundaries between these layers are becoming more and more muddled, with the industry heading towards a serverless future, also called, Functions-as-a- Service, FaaS.

This is the combination of all three types of cloud computing we’ve discussed, more on this in the next section. A serverless future provided through cloud computing is the new paradigm; this further exemplified by the fact that the price of cloud computing is decreasing due to increasing computing power.

This is referred to as Bezo’s Law, where the CEO and founder of Amazon stated: a unit of computing power price is reduced by approximately 50% every 3 years. The unit of measurement for the allocation of computing power varies by provider due to the types of cloud computing they provide, for example, per gigabyte of RAM used, per gigabyte of storage, kilowatt-hours of computing used,

etc.

When electricity became a utility, the barrier to entry of a scalable business dropped and led to innovation at an exponential rate, computing as the utility does this once again. This is easily observable by startup culture today, where anyone with a vision or idea can

immediately establish an online presence and proof of concept of their application or website.

Whereas in the past, expensive servers would have to be maintained and overhead of extra staff, now with cloud computing and serverless architecture all of that is taken care of at a bare minimal cost. As the application starts to become more popular, all you have to do now is increase your cloud plan through your cloud service provider.

There are many services offered by cloud providers to accelerate development and innovation, to list a few: Amazon Lumberyard for game development, Salesforce for e-commerce applications, Amazon Web Services for all-encompassing serverless architecture and many more. As a side note, our site https://waystomakemoneyonlineguide.com is hosted on AWS. Amazon Web Services offers

comprehensive big data services that enable retailers to perform sophisticated analytics at lightning-fast speeds, allowing for real-time analysis and insights that drive your business. With Amazon Kinesis, you can quickly ingest different data streams from mobile and web purchases, POS transactions and customer data. Store this data in an Amazon S3 data lake and use Amazon Athena to run ad-hoc analysis and interactive queries like customer shopping patterns and product preferences.

With AWS Lambda you can set up code that responds to certain triggers and events, like querying Amazon DynamoDB, a NoSQL database, to respond to customer questions about product assortment and availability or to generate sentiment analysis from social

media. Storing it in a fully managed data warehouse like Amazon Redshift and then visualizing an identifying customer sentiment over time with Amazon Quicksight.

Amazon EMR provides retailers with a managed Hadoop analytics framework that makes it easy fast and cost effective to process vast amounts of transaction data, online browsing behavior, in-store shopping trends and product preferences which can guide

inventory and pricing strategies. With the broadest and most advanced set of analytic services supporting every workload imaginable, AWS provides everything a retailer needs to collect, store, process, analyze and visualize big data in the cloud.

Beyond the impact to business and startups, cloud computing is beginning to have a major impact on us, the consumers as well due to cloud services and service architecture. Cloud services for consumers used to be about storage such as Dropbox and Google

Drive.

Now, however, they are beginning to expand to every industry, to list some examples: cloud music like Apple Music and Spotify and cloud gaming that Nvidia is working on with GeForce Now. These services are now extending towards virtual desktops as well, where any application can be run in the cloud. An example of this is Amazon Workspaces, where any Windows application can be run in the cloud.

From intensive programs like After Effects and Cinema 4D to productivity applications like Microsoft Office and everything in between. In terms of the impact of serverless architecture on consumers, it essentially means our devices will be able to do

more with less processing power, since the most computationally intensive tasks will be computed in the cloud.

Let me explain this and extrapolate the future of cloud computing. There are three layers: cloud data centres, fog nodes and edge devices. Cloud data centers are the giant facilities that companies such as Amazon and Google have, the scale of them globally are in the thousands. Fog nodes are small-scale data centers or servers that can be installed anywhere, from the floor of a building, inside a railcar – the list can go on and on.

Put, any device with computing, storage and networking is a fog node, and their scale will be in the millions. Edge devices are simply any internet-connected device, from our mobile phones, self-driving cars, sensors and the countless IoT devices that are

coming to market, their scale will be in the billions. With the growth of machine learning and artificial intelligence, more and more edge devices will require instantaneous big data insights, such an example is self-driving cars that are constantly learning and

adapting to their environments.

It is impractical to have edge devices themselves be powerful enough to compute these analytics, but what they can do is

make inferences based on current machine learning models they have and acquire large amounts of data. This newly acquired data is then sent to the cloud so updated machine learning models can be made and then sent back to the edge device.

The purpose of fog nodes is to reduce the latency of access to the cloud due to the vast amounts of devices that will need connectivity. Instead of connecting to a data center far away, the fog acts as an intermediary that stores analytics closer to the edge.