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Bezos, who is planning a transition to Executive Chairman of the company in Q3 2021, shouldn’t have anything to hide. AWS is a major contributor to the American economy in several significant respects (one notable exception being federal taxes), partly due to its being bonded to a company with colossal revenue from e-commerce. In February, veteran financial analyst Justin Fox estimated that, in 2020, AWS invested close to two-thirds of its annual technology expenditure into its own research and development efforts — some $26.7 billion, by Fox’s calculations. That would make research projects alone a measurable component of the nation’s gross domestic product, the sudden absence of which would trigger an economic meltdown. LEARN MORE: Jeff Bezos explained his company’s basic philosophy in clear and indisputable terms, in a 2010 letter to company shareholders: Bezos likes to adorn his biographical presentations with veritable fountains of fabulous phrases, along with boasts that may warrant a bit of suspicion. For example, in this letter, he gave AWS credit for essentially inventing service-oriented architecture (SOA) — he was, at best, a teenager when SOA was first being put to practical use. So let’s try to explain what this AWS thing does, in terms even a CEO could understand.
AWS’ principal innovation was commoditizing software services
Up until the mid-2000s, software was a thing you installed on your hard drive. It was intellectual property that you were granted the license to use, and either the entirety of that license was paid for up front, or it was subscribed to on an annual “per-seat” basis. A corporate network (a LAN) introduced the astounding technical innovation of moving that hard drive into a room full of other hard drives; otherwise, the principal idea was not much different. (Microsoft thrived in this market.) The first truly brilliant idea that ever happened in corporate LANs was this: An entire computer, including its processor and installed devices, could be rendered as software. Sure, this software would still run on hardware, but being rendered as software made it expendable if something went irreparably wrong. You simply restored a backup copy of the software, and resumed. This was the first virtual machine (VM). LEARN MORE:
How AWS’ cloud business model works today
While AWS still hosts VM-based Web sites, its modern business model is centered around delivering functionality to individuals and organizations, using the Web as its transit medium. Here, we mean “the Web” in its technical sense: the servers that use HTTP and HTTPS protocols to transact, and to exchange data packets. Folks often talk about the Web as the place where ZDNet is published. But modern software communicates with its user through the Web. That software is hosted in what we lackadaisically refer to as “the cloud.” The AWS cloud is the collection of all network-connected servers on which its service platform is hosted. You’ve already read more definitions of “cloud” than there are clouds (in the sky), but here, we’re talking about the operating system that reformulates multiple servers into a cohesive unit. For a group of computers anywhere in the world to be one cloud, the following things have to be made feasible:
They must be able to utilize virtualization (the ability for software to perform like hardware) to pool together the computing capability of multiple processors and multiple storage devices, along with those components’ network connectivity, into single, contiguous units. In other words, they must collect their resources so they can be perceived as one big computer rather than several little ones.
The workloads that run on these resource pools must not be rooted to any physical location. That is to say, their memory, databases, and processes — however they may be contained — must be completely portable throughout the cloud.
The resource pools that run these workloads must be capable of being provisioned through a self-service portal. This way, any customer who needs to run a process on a server may provision the virtual infrastructure (the pooled resources for processing and other functions) needed to host and support that process, by ordering it through the Web.
All services must be made available on a per-use basis, usually in intervals of time consumed in the actual functioning of the service, as opposed to a one-time or renewable license.
The US National Institute of Standards and Technology (NIST) declared that any CSP to which the US Government would subscribe, must at a minimum provide these four capabilities. If NIST had the opportunity to add a fifth component, given the vast amount of history that has taken place in the few short years of the public cloud’s prominence, it would probably be support. AWS may be a public cloud, but it is also a managed service. That means it’s administered to deliver particular service levels which are explicitly spelled out in the company’s service-level agreements (SLA). LEARN MORE:
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What is AWS’ place in a multicloud environment?
There is one element of the software economy that has not changed since back when folks were fathoming the “threat potential” of Microsoft Windows: The dominant players have the luxury of channeling functionality through their portals, their devices, and their service agreements. AWS uses the concept of “democratization” selectively, typically using it to mean increasing availability to a service that usually has a higher barrier to entry. For example, an AWS white paper co-produced with Intel, entitled “Democratizing High-Performance Computing,” includes this statement: Of course, each organization understands its own needs best, but translating those needs into real-world compute resources does not need to be a cumbersome process. Smaller organizations would rather have their expensive engineering or research talent focus on what they do best, instead of figuring out their infrastructure needs. Recently, AWS began producing management services for multicloud computing options, where enterprises pick-and-choose services from multiple cloud providers (there aren’t all that many now anyway). But these services are management consoles that install AWS as their gateways, channeling even the use of Azure or Google Cloud services through AWS’ monitoring. LEARN MORE:
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How do you get started with AWS?
Where can you learn how to use AWS?
AWS convenes its own online conference, sometimes live but always recorded, called AWSome Day, whose intent is to teach newcomers about how its services work. That conference may give you a shove in the general direction of what you think you might need to know. If you have a particular business goal in mind, and you’re looking for professional instruction, AWS typically sponsors instructional courses worldwide that are conducted in training centers with professional instructors, and streamed to registered students. For example:
Migrating to AWS teaches the principles that organizations would need to know to develop a staged migration from its existing business applications and software, to their cloud-based counterparts.
AWS Security Fundamentals introduces the best practices, methodologies, and protocols that AWS uses to secure its services, in order that organizations that may be following specific security regimens can incorporate those practices into their own methods.
These conferences are, in normal times, delivered live and in-person. AWS suspended this program in 2020 due to the pandemic, although listings are available for virtual sessions that were recorded before that time. How affordable is AWS really? AWS’ business model was designed to shift expenses for business computing from capital expenditures to operational expenditures. Theoretically, a commodity whose costs are incurred monthly, or at least more gradually, is more sustainable. But unlike a regular expense such as electricity or insurance, public cloud services tend to spawn more public cloud services. Although AWS clearly divides expenses into categories pertaining to storage, bandwidth usage, and compute cycle time, these categories are not the services themselves. Rather, they are the product of the services you choose, and by choosing more and incorporating more of these components into the cloud-based assets you build on the AWS platform, you “consume” these commodities at a more rapid rate. AWS has a clear plan in mind: It draws you into an account with a tier of no-cost service with which you can comfortably experiment with building a Web server, or launching a database, prior to taking those services live. Ironically, it’s through this strategy of starting small and building gradually, that many organizations are discovering they hadn’t accounted for just how great an operational expense the public cloud could become — particularly with respect to data consumption. The no-cost service is AWS’ free tier, where all of its principal services are made available at a level where individuals — especially developers — are able to learn how to use them without incurring charges. Cost control is feasible, if you take the time to thoroughly train yourself on the proper and strategic use of the components of the AWS platform, before you begin provisioning services on that platform. And the resources for that cost control training do exist, even on the platform itself. LEARN MORE:
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AWS basic services
Back in the days when software was manufactured, stored in inventory, and placed on retailers’ shelves for display, the “platform” was the dependency that was pre-engineered into a product that made it dependent upon others, or made others dependent upon it. MS-DOS was the first truly successful commercial software platform, mostly because of the dependencies it created, and which Microsoft would later exploit more deeply with Windows.
Elastic Compute Cloud
Originally, the configurations of EC2 instances mimicked those of real-world, physical servers. You chose an instance that best suited the characteristics of the server that you’d normally have purchased, installed, and maintained on your own corporate premises, to run the application you intended for it. Today, an EC2 instance can be almost fanciful, configured like no server ever manufactured anywhere in the world. Since virtual servers comprise essentially the entire Web services industry now, it doesn’t matter that there’s no correspondence with reality. You peruse AWS’ very extensive catalog, and choose the number of processors, local storage, local memory, connectivity, and bandwidth that your applications require. And if that’s more than in any real server ever manufactured, so what? You then pay for the resources that instance uses, literally on a per-second basis. If the application you’ve planned is very extensive, like a multi-player game, then you can reasonably estimate what your AWS costs would be for delivering that game to each player, and calculate a subscription fee you can charge that player that earns you a respectable profit. LEARN MORE:
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Elastic Container Service
Virtual machines gave organizations a way to deliver functionality through the Internet without having to change the way their applications were architected. They still “believe” they’re running in a manufactured server. In recent years, a new vehicle for packaging functionality has come about that is far better suited to cloud-based delivery. It was called the “Docker container,” after the company that first developed an automated mechanism for deploying it on a cloud platform (even though its name at the time was dotCloud). Today, since so many parties have a vested interest in its success, and also because the English language has run out of words, this package is just called a container. AWS’ way to deliver applications through containers rather than virtual machines is Elastic Container Service (ECS). Here, the business model can be completely different than for EC2. LEARN MORE:
Simple Cloud Storage Service (S3)
AWS does not charge customers by the storage volume, or in any fraction of a physical device consumed by data. Instead, it creates a virtual construct called a bucket, and assigns that to an account. Essentially, this bucket is bottomless; it provides database tools and other services with a means to address the data contained within it. By default, each account may operate up to 100 buckets, though that limit may be increased upon request. Once data is stored in one of these buckets, the way AWS monetizes its output from the bucket depends upon how that data is used. If a small amount of data is stored and retrieved not very often, AWS is happy not to charge anything at all. But if you’ve already deployed a Web app that has multiple users, and in the course of using this app, these users all access data stored in an S3 bucket, that’s likely to incur some charges. Database queries, such as retrieving billing information or statistics, will be charged very differently from downloading a video or media file. If AWS were to charge one flat fee for data retrieval — say, per megabyte downloaded — then with the huge difference in scale between a spreadsheet’s worth of tabular data and a 1080p video, no one would want to use AWS for media. So S3 assumes that the types of objects that you’ll store in buckets will determine the way those objects will be used (“consumed”) by others, and AWS establishes a fee for the method of use. LEARN MORE:
AWS database services
For relational data — the kind that’s stored in tables and queried using SQL language — AWS offers a variety of options, including MariaDB (open source), Microsoft SQL Server, MySQL (open source), Oracle DB, PostgreSQL (open source). Any application that can interface with a database in one of these formats, even if it wasn’t written for the cloud to begin with, can be made to run with one of these services. Since data is always being reconstructed as a matter of course, any loss of data is almost instantaneously patched, without the need for a comprehensive recovery plan. In the case of severe loss, such as an entire volume or “protection group,” repairs are accomplished by way of instructions gleaned from all the other groups in the database, or what Vogels calls the “fleet.” LEARN MORE:
AWS starts gluing the gaps between its databases
Standing up a “big data” system, such as one based on the Apache Hadoop or Apache Spark framework, is typically a concentrated effort on the part of any organization. Though they both refrain from invoking the phrase, both Spark and Hadoop are operating systems, enabling servers to support clusters of coordinated data providers as their core functionality. So any effort to leverage the cloud for a big data platform must involve configuring the applications running on these platforms to recognize the cloud as their storage center. AWS Redshift approaches this issue by enabling S3 to serve as what Hadoop and Spark engineers call a data lake — a massive pool of not-necessarily-structured, unprocessed, unrefined data. Originally, data lakes were “formatted,” to borrow an old phrase, using Hadoop’s HDFS file system. Some engineers have since found S3 actually preferable to HDFS, and some go so far as to argue S3 is more cost-effective. Apache Hadoop now ships with its own S3 connector, enabling organizations that run Hadoop on-premises to leverage cloud-based S3 instead of their own on-premises storage. LEARN MORE: Kinesis leverages AWS’ data lake components to stand up an analytics service — one that evaluates the underlying patterns within a data stream or a time series, make respectable forecasts, and draw apparent correlations as close to real-time as possible. So if you have a data source such as a server log, machines on a manufacturing or assembly line, a financial trading system, or in the most extensive example, a video stream, Kinesis can be programmed to generate alerts and analytical messages in response to conditions that you specify. The word “programmed” is meant rather intentionally here. Using components such as Kinesis Streams, you do write custom logic code to specify those conditions that are worthy of attention or examination. By contrast, Kinesis Data Firehose can be set up with easier-to-explain filters that can divert certain data from the main stream, based on conditions or parameters, into a location such as another S3 bucket for later analysis. LEARN MORE: In addition, AWS offers the following:
DynamoDB for use with less structured key/value stores
DocumentDB for working with long-form text data such as in a content management system
Athena as a “serverless” service that enables independent queries on S3-based data stores using SQL
ElastiCache for dealing with high volumes of data in-memory.
AWS advanced and scientific services
One very important service that emerges from the system that makes ECS possible is called Lambda, and for many classes of industry and academia, it’s already significantly changing the way applications are being conceived. Lambda advances a principle called the serverless model, in which the cloud server delivers the functions that an application may require on a per-use basis only, without the need for pre-provisioning. LEARN MORE:
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As Microsoft so often demonstrated during its reign as the king of the operating system, if you own the underlying platform, you can give away parts of the territory that floats on top of it, secure in the knowledge that you own the kingdom to which those islands belong. This way, EKS can provide management services over the infrastructure supporting a customer’s Kubernetes deployment, comparable to what Google Cloud and Azure offer. The provisioning of clusters can happen automatically. That last sentence doesn’t have much meaning unless you’ve read tens of thousands of pages of Kubernetes documentation, the most important sentence from which is this: You can pick a containerized application, tell EKS to run it, then EKS will configure the resources that application requires, you sign off on them, and it runs the app. So if you have, say, an open source content management system compiled to run in containers, you just point EKS to the repository where those containers are located and say “Go.” If all the world’s applications could be automated in exactly this way, we would be living in a very different world. LEARN MORE:
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