With all this hype around Kubernetes, containerization and microservices architecture... you cannot help but wonder: “What are the primary Kubernetes use cases, more precisely?”
“And is it a good fit for large-scale applications?” Say you have this complex setup: an eCommerce app carrying an ecosystem of about 6 micro-services. You'd expect 2 of them, let's say, to be for internal-use-only and 4 of them to have external load balancers...
How would Kubernetes orchestrate such a large cluster? What makes it a top choice for automating the deployment of such complex and dynamic infrastructures?
Let's dig in for some solid arguments for this statement:
1. But First: What Is Kubernetes? How Does It Work?
A concise and comprehensive definition would be:
It's a platform for managing containerized applications — workflows and services — with scalability, automation and availability in mind...
“How does it work?” Kubernetes would build on top of the already set up containerization, helping your team to orchestrate how those containers should interact and, overall, how the whole structure should look like.
“And why should I put it on top of my list of choices? What makes Kubernetes such a popular system for managing containerized software components?”
For 2 key reasons:
- it provides unmatched scaling capabilities
- it comes bundled with a rich ecosystem
2. Kubernetes Use Cases: What Kind of Apps Can You Build With It?
Kubernetes makes the best choice for
- data analytics workflows
- cloud-native workloads
- high-throughput computing
… and still: its main role is NOT to build applications.
Think of it as a Containers Orchestration Engine, nothing more. It's not a new programming language for app development.
What it does is just deploy a pre-built image...
In other words:
- you have your team of developers write the code (in a YAML format)
- which then gets turned into an image built with dockerfile
- image that gets uploaded to the registry (Docker Hub)
“Not only that it's suitable, but it's the best-suited tool for automating the deployment of large-scale setups. To back up my statement, here's Kubernetes “in action”, from the standpoint of scalability:
- leveraging a declarative configuration, a Kubernetes system's built to automate the deployment of complex clusters of nodes in no time
- it distributes the fluxes of requests across the available web/core containers; in other words, as you scale up your application and you're faced with a spike in traffic, you only need to scale the core/web containers to help it withstand the incoming requests...
- since the separation of concerns is a critical issue with large-scale applications, in particular, it's no negligible “detail” that Kubernetes makes clear distinctions between application code, operating system, and application management; you get to have specialized teams for each section...
- it provides you with a system that minimizes downtime when you're running, upgrading and maintaining application services
- it shifts infrastructure to code, meaning that you can version control your whole structure; this translates into easily testable environments (production, development, staging...)
- it allows you to set up how precisely your system should adapt; Kubernetes will automatically scale the number of pods (instances of a microservice) so that the cluster can withstand unexpected fluxes of traffic
In short, orchestrating large-scale applications in cloud environments is one of the primary Kubernetes use cases. It's designed to efficiently load balance spikes of traffic and update large “ecosystems” of containers with minimal downtime.
4. Deploying Kubernetes at Scale: Main Challenges & Solutions
Now, don't think that deploying Kubernetes is a smooth process. Instead, expect it to be paved with challenges such as:
- keeping up with all the Kubernetes patches and updates that are being constantly released
- troubleshooting and closely monitoring your Kubernetes system (with all its open source components)
- handling a complex installation and configuration process of your whole infrastructure of services, plugins, components...
- administering clusters across multiple data centers and clouds (private, public, hybrid)
How do you overcome these predictable challenges so you can fully leverage Kubernetes' power?
- you get everything set for it: implement all the needed features for certificate management, log collection, network isolation, monitoring workloads, etc.
- you address all multi-tenancy issues: network isolation policies, grouping users into multiple teams, providing a single sign-on opportunity
- you keep downtime during updates at a minimum (a major challenge, considering that a new Kubernetes version gets released about every 3 months)
- you strive to maintain consistency when it comes to delivered experienced and SLA, whether you're deploying Kuberneres via a vendor or by your organization, whether in a public cloud or on-premise
In conclusion, managing large scale applications is, by far, one of the most common Kubernetes use cases. The one that its rich ecosystem and scalability features seem to have been designed for specifically.
The question is not whether it's a good fit for large-scale structures, but whether you're ready to accept that with its power come quite a few challenges that you'll need to address...Image by Gerd Altmann from Pixabay