Cloud-native apps and why they’re important

When thinking about creating any type of application, automation code, or piece of software, there always needs to be some sort of standard. The thing is, there are many standards and there isn’t a one-size-fits-all solution. Sure, there are (what should be) mandatory standards for writing code such as storing the code in source control and running certain types of tests, but the workflows for each organization will be drastically different.

When it comes to cloud-native applications and applications running on Kubernetes, the thought process of workflows is the same as any other application, but there are true, standard processes that are automatically implemented for you. This includes things such as the following:

• Easy autoscaling
• Self-healing
• Networking out of the box
• And a lot more

In the upcoming section, we’ll build on what you learned previously and dive into what cloud-native apps do for organizations.

What cloud-native apps do for organizations

By definition, a cloud-native application gives you the ability to do the following:

• Easily scale
• Make highly available almost out of the box
• Deploy more efficiently
• Continuously make changes in a much easier fashion versus outside of Kubernetes in a bare-metal/data center environment

When thinking about cloud-native applications and the preceding list, microservices typically come to mind. The idea behind microservices, which is a big piece of the idea behind cloud-native, is the ability to make changes faster and more efficiently. When you’re dealing with a monolithic application, the application has many dependencies and is essentially tied together. You can’t update one piece of the application without bringing down the rest of the application. Blue/green and canary deployments are far more complicated because of the tightly coupled monolithic application. Self-healing and scalability mean scaling the entire application, not just the pieces that need to be scaled, which means more resources (RAM, CPU, and so on) are typically consumed than what’s needed.

Cloud-native and the microservice mindset aim to fix this problem. With microservices running inside Kubernetes, there are some extreme benefits. You can manage how many replicas (copies) of the application are running. That way, you can scale them out or scale them back when needed. Self-healing of Pods is far more efficient since if a piece of the application that’s running inside of a Pod goes down, it’s not a huge deal because it’ll come right back up automatically. The applications running inside of Pods, which have one or more containers running inside of the Pods, are loosely coupled, so updating/upgrading versions of the application in a blue/green or canary scenario utilizing a rolling update is far less likely to fail.

When it comes to teams, as in, individual engineers, microservices help a ton. With a monolithic application, there is a fair amount of coordination that has to happen between the team when changing anything in the code base. Although teamwork and communication are crucial, there shouldn’t be a reason to let everyone know about a code change in the development environment that you’re making to test a piece of functionality without breaking everyone else’s code. With how fast organizations want to move in today’s world, this process slows engineering teams down to a grinding halt. Not to mention, if an engineer wants to test how the functionality will work with the rest of the application, they shouldn’t have to worry about every piece of the application breaking. That’s really where microservices shine.

When the Kubernetes architecture was built, it was thought about in the same way as cloud-native applications – a loosely coupled architecture that is easily scalable and doesn’t have a ton of dependencies (hence, the microservice movement). Can you run monolithic applications on Kubernetes? Absolutely. Will they still self-heal and autoscale? Absolutely. The idea behind a cloud-native application environment and cloud-native Kubernetes is to use a microservice-style architecture, but you shouldn’t let that stop you from jumping into Kubernetes. The primary goal is to have independent services that can be accessed via an Application Programming Interface (API).

The final piece of the puzzle is containerized applications. Before even running an application inside Kubernetes, it must be containerized. When the idea of containers was thought about way before Docker was around, the idea was to have the ability to split an entire application into tiny micro-sized pieces. When containers are built, they’re built with the same mindset as the following aspects:

• Self-contained execution environments
• Virtualized OSes
• Microservice architecture with the ability to split up pieces of an entire application and consolidate it into a single container for the ability to easily scale, update, and swap out

The world is cloud-based

One of the worst things that an organization can do in today’s world, from an engineering perspective, is to get left behind. The last thing an organization wants is to realize 10 years later that the systems and dependencies that they have in place are so old that no organization or software company is even supporting them anymore. The golden rule before 2015/2016 was to ensure that the architecture and the people/engineers running the architecture were up to date every 5 to 10 years. Now, with how fast technology is moving, it’s more like every 2 to 5 years.

When looking at organizations such as Microsoft, Google, and AWS, they’re releasing huge changes and updates all the time. When attending a conference such as Microsoft Build or the AWS Summit, the keynotes are filled with game-changing technology with tons of new services coming to the cloud platforms all the time. The reality is that if organizations don’t want to be left behind, they can’t wait more than 5 years to start thinking about the newest technology.

With that being said, many organizations can’t simply upgrade systems every 6 months or every year because they’re too large and they don’t have enough people to make those migrations and updates. However, technology leaders need to start thinking about what this will look like because the future of the company will be on the line. For example, let’s look at the change in Windows Server over the past few years. Microsoft used to constantly talk about new Windows Server versions and features at every conference. Now, it’s all about Azure. The technology world is changing drastically.

Where Kubernetes fits in here is that it helps you make cloud-native and fast-moving decisions almost automatically. For example, let’s say (in a crazy world) Kubernetes goes away in 3 years. You still have your containerized applications and your code base that’s in source control and loosely coupled, which means you can run it anywhere else, such as in a serverless service or even a virtual machine if it comes down to it. With the way that the world is going, it’s not necessarily about always using Kubernetes to prevent an organization from going down. It’s about what Kubernetes does for engineers, which is that it allows you to manage infrastructure and applications at the API level.

Engineering talent is toward the cloud

One last small piece we will talk about is the future of engineers themselves. New technology professionals are all about learning the latest and greatest. Why? Because they want the ability to stay competitive and get jobs. They want to stay up to date so they can have a long and healthy career. What this means is that they aren’t interested in learning about how to run a data center, because the tech world is telling everyone to learn about the cloud.

As time goes on, it’s going to become increasingly difficult for organizations to find individuals that can manage and maintain legacy systems. With that being said, there’s no end in sight for legacy systems going away. That’s why organizations such as banks are still looking for COBOL developers. The thing is, no engineer wants to bet their career in their 20s on learning legacy pieces.