Defining Conversations

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Even when we do have enough use-cases to make serverless computing a worthwhile effort, a more significant concern is lurking just around the corner.

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We are likely going to be locked into a vendor given that none of them implements any type of industry standard. That does not mean that there are no serverless frameworks that are not tied to a specific cloud provider. There are, but we'd need to maintain them ourselves, be it on-prem or inside clusters running in a public cloud, and that removes one of the most essential benefits of serverless concepts. At this point, I must make an assumption that you, dear reader, might disagree with.

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Most of the companies will run at least some if not all of their applications in Kubernetes. It is becoming or it already is a standard API that will be used by almost everyone. Why is that assumption important?

What is Serverless Computing?

If I am right, then almost everyone will have a Kubernetes cluster. Everyone will spend time maintaining it, and everyone will have some level of in-house knowledge of how it works. If that assumption is correct, it stands to reason that Kubernetes would be the best choice for a platform to run serverless applications as well. As an added bonus, that would avoid vendor lock-in since Kubernetes can run almost anywhere.

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  4. Kubernetes-based serverless computing would provide quite a few other benefits. We could be free to write our applications in any language, instead of being limited by those supported by function-as-a-service solutions offered by cloud vendors. Also, we would not be limited to writing only functions.

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    A microservice or even a monolith could run as a serverless application. We just need to find a solution to make that happen. After all, proprietary cloud-specific serverless solutions use containers of sorts as well, and the standard mechanism for running containers is Kubernetes. There is an increasing number of Kubernetes platforms that allow us to run serverless applications. We won't go into all of those but fast-track the conversation by me stating that Knative is likely going to become the de-facto standard how to deploy serverless load to Kubernetes.

    Or, maybe, it already is the most widely accepted standard by the time you read this. Knative is an open-source project that delivers components used to build and run serverless applications on Kubernetes. We can use it to scale-to-zero, to autoscale, for in-cluster builds, and as an eventing framework for applications on Kubernetes. The part of the project we're interested in right now is its ability to convert our applications into serverless deployments, and that means auto-scaling down until zero, and up to whatever an application needs.

    That should allow us both to save resources memory and CPU when our applications are idle, as well as to scale them fast when traffic increases. Now that we discussed what is serverless and that I made an outlandish statement that Kubernetes is the platform where your serverless applications should be running, let's talk which types of scenarios are a good fit for serverless deployments.

    Initially, the idea was to have only functions running as serverless loads. Those would be single-purpose pieces of code that contain only a small number of lines of code.

    Conversation: Definition and Examples

    A typical example of a serverless application would be an image processing function that responds to a single request and can run for a limited period. Restrictions like the size of applications functions and their maximum duration are imposed by implementations of serverless computing in cloud providers. But, if we adopt Kubernetes as the platform to run serverless deployments, those restrictions might not be valid anymore.

    We can say that any application that can be packaged into a container image can run as a serverless deployment in Kubernetes. That, however, does not mean that any container is as good of a candidate as any other. The smaller the application or, to be more precise, the faster its boot-up time, the better the candidate for serverless deployments. However, things are not as straight forward as they may seem. Not being a good candidate does not mean that one should not compete at all.

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    Knative, as many other serverless frameworks do allow us to fine-tune configurations. We can, for example, specify with Knative that there should never be less than one replica of an application. That would solve the problem of slow boot-up while still maintaining some of the benefits of serverless deployments. In such a case, there would always be at least one replica to handle requests, while we would benefit from having the elasticity of serverless providers.

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    The size and the boot-up time are not the only criteria we can use to decide whether an application should be serverless. We might want to consider traffic as well. If, for example, our app has high traffic and it receives requests throughout the whole day, we might never need to scale it down to zero replicas. Similarly, our application might not be designed in a way that every request is processed by a different replica. After all, most of the apps can handle a vast number of requests by a single replica. In such cases, serverless computing implemented by cloud vendors and based on function-as-a-service might not be the right choice.

    But, as we already discussed, there are other serverless platforms, and those based on Kubernetes do not follow those rules. Since we can run any container as a serverless, any type of applications can be deployed as such, and that means that a single replica can handle as many requests as the design of the app allows.

    Also, Knative and other platforms can be configured to have a minimum number of replicas, so they might be well suited even for the applications with a mostly constant flow of traffic since every application does or should need scaling sooner or later. The only way to avoid that need is to overprovision applications and give them as much memory and CPU as their peak loads require. All in all, if it can run in a container, it can be converted into a serverless deployment, as long as we understand that smaller applications with faster boot-up times are better candidates than others.

    However, boot-up time is not the only rule, nor it is the most important one. If there is a rule we should follow when deciding whether to run an application as serverless, it is related to the state. Feel free to like , comment , or share before you leave. For more, check out davidwangel. Become a member. Sign in. Get started. David W. Angel Follow.

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