In 10 years nobody will be talking about Kubernetes. Not because people stopped using it or because it fell out of favor, but because it became utility. Containers, Kubernetes, service meshes—they’ll all be there, the same way VMs, hypervisors, and switches will be. Compute is a commodity, and I don’t care how my workload runs so long as it meets my business’s SLOs and other requirements. Within AWS alone, there are now innumerable ways to run a compute workload.
This was the promise of Platform as a Service (PaaS): provide a pre-built runtime where you simply plug in your application and the rest—compute, networking, storage—is handled for you. Heroku (2007), Google App Engine (2008), OpenShift (2011), and Cloud Foundry (2011) all come to mind. But PaaS has, in many ways, become a sort of taboo in recent years. As a consultant working with companies either in the cloud or looking to move to the cloud, I’ve found PaaS to almost be a trigger word; the wince from clients upon its utterance is almost palpable. It’s hard to pin down exactly why this is the case, but I think there are a number of reasons which range from entirely legit to outright FUD.
There is often a funny cognitive dissonance with these companies who recoil at the mention of PaaS. After unequivocally rejecting the idea for reasons like vendor lock-in and runtime restrictions (again, some of these are legitimate concerns), they will describe, in piecemeal fashion, their own half-baked idea of a PaaS. “Well, we’ll use Kubernetes to handle compute, ELK stack for logging, Prometheus for metrics, OpenTracing for distributed tracing, Redis for caching…”, and so the list goes on. Not to mention there tends to be a bias on build over buy. And we need to somehow provide all of these things as a self-service platform to developers.
While there are ongoing efforts to democratize the cloud and provide reference architectures of sorts, the fact is there are no standards and the proliferation of tools and technologies continues to expand at a rapid pace. On the other hand, as certain tools emerge, such as Kubernetes, the patterns and practices around them have naturally lagged behind. The serverless movement bears this out further. Serverless is the microservice equivalent for PaaS but with a lot less tooling and operations maturity. This is an exciting time, but the cloud has become—without a doubt—an unnavigable wasteland. Even with all the things at your disposal today, it’s still a ton of work to build and operate what is essentially your own PaaS.
But technology is cyclical and the cloud is no different. This evolution, in some sense, parallels what happened with the NoSQL movement. Eric Brewer discusses this in his RICON 2012 talk. When you cut through the hype, NoSQL was about giving developers more control at the expense of less pre-packaged functionality, but it was not intended to be the end game or an alternative to SQL. It’s about two different, equally valid world views: top-down and bottom-up. The top-down view is looking at a model and its semantics and then figuring out what you need to do to implement it. With a relational database, this is using SQL to declaratively construct our model. The bottom-up view is about the layering of primitive components into something more complex. For example, modern databases like CockroachDB present a SQL abstraction on top of a transactional layer on top of a replication layer on top of a simple key-value-store layer. NoSQL gives us a reusable storage component with a lot of flexibility and, over time, as we add more and more pieces on top, we get something that looks more like a database. We start with low-level layers, but the end goal is still the same: nice, user-friendly semantics. I would argue the same thing is happening with PaaS.
What the major cloud providers are doing is unbundling the PaaS. We have our compute, our cluster scheduler, our databases and caches, our message queues, and other components. What’s missing is the glue—the standards and tools that tie these things together into a coherent, manageable unit—a PaaS. Everything old is new again. What we will see is the rebundling of these components gradually happen over time as those standards and tools emerge. Tools like AWS Fargate and Google App Engine Flexible Environment are a step in that direction (Google really screwed up by calling it App Engine Flex because of all the PaaS baggage associated with the App Engine name). The container is just the interface. However, that’s only the start.
In the future you'll be able write an application, define security and compute resource requirements, set pricing thresholds, then get back an URL and links to debug, view and analyze logs and metrics.
— Kelsey Hightower (@kelseyhightower) February 5, 2018
PaaS and serverless are great because they truly accelerate application development and reduce operations overhead. However, the trade-off is: we become constrained. For example, with App Engine, we were initially constrained to certain Google Cloud APIs, such as Cloud Datastore and Task Queues, and specific language runtimes. Over time, this has improved, notably, with Cloud SQL, and now today we can use custom runtimes. Similarly, PaaS gives us service autoscaling, high availability, and critical security patches for free, but we lose a degree of control over compute characteristics and workload-processing patterns.
In a sense, what a PaaS offers is an opinionated framework for running applications. Opinionated is good if you want to be productive, but it’s limiting once you have a mature product. What we want are the benefits of PaaS with a bit more flexibility. A PaaS provides us a top-down template from which we can start, but we want to be able to tweak that to our needs. Kubernetes is a key part of that template, but it’s ultimately just a means to an end.
This is why I think no one will be talking about Kubernetes in 10 years. Hopefully by then it’s just not that interesting. If it still is, we’re not done yet.Follow @tyler_treat