Growing up, I was often reminded to turn off the lights. In my home, this was a way of saving on a key resource (electricity) that we had to pay for when not using it. It was a way of being a good steward with the family’s money and targeting it to run the lights and other things in our home. This allowed us to go about our daily tasks and get them done when we needed to.

These days I have the same goal in my own home, but I’ve automated the task. I have a voice assistant that, with a few select words, will turn off (or on) the lights in the rooms that I use most. The goal and the reasoning are the same, but the automation allows me to take it to another level.

In a similar way, automation today allows us to optimize the use of compute resources in a way that we haven’t been able to do in the past. The degree to which we can switch on and off the systems required to run our compute workloads in cloud environments, scale to use more, or fewer, resources depending on demand, and only pay for what we need, is a clear indicator of just how much infrastructure technology has evolved in recent years.

Like the basic utilities we rely on in our homes, SAS, with its analytics and modeling capabilities has become an essential utility for any business that wants to not only make sense of data but turn it into the power to get things done. And, like any utility necessary to do business, we want it working quickly at the flip of a switch, easily made available anywhere we need it, and helping us be good stewards of our resources.

Containers and the related technologies can help us achieve all of this in SAS

A container can most simply be thought of as a self-contained environment with all the programs, configuration, initial data, and other supporting pieces to run applications. This environment can be treated as a stand-alone unit, ready to turn on and run at any time, much in the way your laptop is a stand-alone system. In fact, this sort of “portable machine” analogy can be a good way to think about containers at a high level – a complete virtual system containing, and configured for running, one or more targeted application(s) – or components of an application.

Docker is one of the oldest, and most well-known, applications for defining and managing containers. Defining a container is done by first defining an image. The image is an immutable (static) set of the software, environment, configuration, etc. that serves as a template for containers to be created from it. Each image, in turn, is composed of layers that apply some setting, software, or data that a container based on the image will need.
Have you ever staged a new machine for yourself, your company, a friend or relative? If so, you can relate the “layering” of software you installed and configured to the layers that go into an image. And the image itself might be like the image of software you created on the disk of the system. The applications are stored there, fully configured and ready to go, whenever you turn the system on.

Turning an image into a container is mostly just adding another layer on top of the present image layers. The difference is this “container layer” can be modified as needed – have things written to it, updated, etc. If you think about the idea of creating a user profile along with its space on a system you staged, it’s a similar idea. Like that dedicated user space on the laptop or desktop, the layer that gets added to an image to make a container, is there for the running system to use and customize as needed. This is like how the user area is there to use and customize as needed when a PC is turned on and running.

Containers, Kubernetes, and cloud environments

It is rare that any corporate system today is managed with only a single PC. Likewise, in the world of cloud and containerized environments, it is rare that any software product is run with only a single container. More commonly, applications consist of many containers organized to address specific application areas (such as web interfaces, database management, etc.) and/or architectural designs to optimize resource use and communication paths in the system (microservices).

Having the advantages that are derived from either multiple PCs or multiple containers also requires a way to manage them and ensure reliability and robustness for our applications and customers. For the machines, enterprises typically rely on data centers. Data centers play a key role, ensuring systems are kept up and running, replaced when broken, and are centrally accessible. As well, they may be responsible for bringing more systems online to address increased loads or taking some systems offline to save costs.

For containers, we have applications that function much like a “data center for containers.” The most prominent one today is Kubernetes (also known as “K8S” for the eight letters between “K” and “S”). Kubernetes’ job is to simplify deployment and management of containers and containerized workloads. It does this by automating key needs around containers, such as deployment, scaling, scheduling, healing, monitoring, and more. All of this is managed in a “declarative” way where we no longer must tell the system “how” to get to the state we want – we instead tell it “what” state we want, and it ensures that state is met and preserved.

The combination of containers, Kubernetes, and cloud environments provides an evolutionary jump in being able to control and leverage the infrastructure and runtime environments that you run your applications in. And this gives your business a similar jump in being able to provide the business value targeted to meet the environments, scale, and reliability that your customers demand - while having the automatic optimization of resources and the automatic management of workloads that you need to be competitive.

Harness decades of expertise with SAS® Viya® 4.0

SAS Viya 4.0 provides this same evolutionary jump for SAS. Now, your SAS applications and workloads can be run in containers, Kubernetes, and cloud environments natively. SAS Viya 4 builds on the award-winning, best-in-class analytics to allow data scientists, business executives, and decision makers at all levels to harness the decades of SAS expertise running completely in containers, and tightly integrated with Kubernetes and the cloud.

SAS Viya 4.0 brings all the key SAS functionalities you’d expect – modeling, decision-making, forecasting, visualization, and more – to the cloud and enterprise cloud environments, along with the advantages of running in a containerized model. It also leverages the robust container management, monitoring, self-healing, scaling and other aspects of Kubernetes. This is all guaranteed to make you more in control and less reliant on being in your data center to manage these kinds of activities.

Just remember to turn the lights off.

LEARN MORE | AN INTRO TO SAS FOR CONTAINERS