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Serverless Kubernetes is a deployment model that completely abstracts the underlying infrastructure management from the users
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Serverless and Kubernetes are hot topics in the software industry. Serverless is a software architecture design that allows you to run your applications on servers without managing the underlying infrastructure running the application. In other words, you don’t have to provision, maintain, and scale the host servers in order to run your applications.
Kubernetes is a container orchestration tool for automating the deployment, scaling, and management of containerised applications. Prior to Kubernetes, containerizing applications meant that you had the ability to run your application on any operating system with the expectation that the application would run the same way. However, deploying, managing, and scaling multiple containerised applications turned out to be tedious, which is the problem Kubernetes was created to solve.
If you need help getting started with Kubernetes and implementing serverless functions, book a quick demo with our team of cloud experts.
In serverless architecture, the underlying servers are only invoked when an event triggers the application, and then the application stops running once it completes its process. This makes it possible to only pay for the computing resources your application uses.
With traditional computing, the hosting provider charges you whether your application is actively receiving requests or is idle. You don’t have to worry about purchasing or provisioning servers when using serverless architecture because the serverless vendor has now taken over that responsibility.
Serverless architecture provides many benefits for your applications, including the following:
Highly Scalable
Serverless architecture makes your applications highly scalable. As your application usage increases, the serverless vendor begins to spin more servers to accommodate the increase in usage. In comparison, with traditional Kubernetes hosting, the application has a fixed number of requests it can handle, unless you manually scale the application replicas or resources, or configure a cluster or pod autoscaler in your cluster.
In summary, serverless Kubernetes handles high availability in an easy and transparent way when compared to traditional Kubernetes hosting.
Easy to Update and Deploy
Serverless architecture makes it easy to update and deploy a new application version with lesser configurations compared to traditional Kubernetes hosting. You can easily upload recent changes in your application and release them to production. In addition, since the application combines different functions and is not monolithic, deploying parts of your applications without deploying the whole application becomes effortless.
No Server Management
When you use a serverless infrastructure for your applications, there are still underlying servers that run the applications. However, you don’t have to be concerned with the management of how your application interacts with the servers. The management is done by the vendor provider offering the serverless infrastructure. Since you are not in charge of managing the underlying infrastructure, you have more free time to focus on other important parts of your application.
Pay as You Go
With a serverless architecture, you’re only charged for the computing resources you use, which reduces costs. Your code only runs when it’s triggered, and it scales up when there is a spike in traffic and automatically scales down when the traffic returns to normal.
In traditional server architecture, you have to predict your application usage so that you can properly plan on the compute resources needed in order to save cost. If, later on, your application doesn’t receive the intended traffic as predicted, you’ll be wasting resources and be charged for it. While autoscaler solves the issue of autoscaling in traditional Kubernetes hosting, it isn’t possible to scale your deployments to zero which means that at zero traffic you will still be charged for your cluster resources. However, with serverless architecture, scaling to zero is possible, which makes it possible for you to only pay for the resources you consume.
Kubernetes doesn’t provide out-of-the-box functionalities in handling serverless workloads on your Kubernetes infrastructure. However, there are several Kubernetes tools that allow you to run serverless workloads on Kubernetes, including Knative, OpenFaas, and Apache OpenWhisk.
KNative
Knative, originally created by Google, is an open source platform for deploying and managing serverless applications on the cloud and premises. Knative was designed to let developers focus on developing their application while removing the burden of deploying, managing, and scaling their application on Kubernetes.
Knative has many notable features including scaling applications to zero, application triggers based on events, and handling events from multiple sources. Other features include caching artifacts for faster builds, progressive application rollouts, and connecting your own monitoring tools.
OpenFaas
Similar to KNative, OpenFaas allows developers to deploy serverless functions and applications on Kubernetes without the need for repetitive, boilerplate coding. One of the main purposes for the development of OpenFaas is to ensure that developers can deploy serverless applications with ease.
Some of the features in OpenFaas that allow for ease of deployment of serverless applications include a template store which contains different programming language templates for building Docker container images of your application. These images can run as serverless applications on Kubernetes. In addition to that, OpenFaas has a functions store that lets you share and reuse other developers’ functions.
Other notable features and benefits of OpenFaas include scaling idle functions to zero replicas, triggering functions/applications via HTTP request, Apache Kafka messages and AWS SQS queues, and enabling authentication via OpenID Connect and OAuth2.
OpenWhisk
Developed by Apache, OpenWhisk is another serverless platform that takes care of managing and provisioning servers for your application while you focus on developing and maintaining your application. You can write your application in any programming language, and then your functions can be triggered via HTTP request or other triggers using hooks and polling.
OpenWhisk provides a feature called `packages` that allows you to integrate and reuse other developer functions with your functions. Additionally, some packages can also be used to trigger your own functions, such as the Alarm Package. You can use this package to trigger your functions at intervals.
Other notable features include system limits on the memory a function uses per minute, number of functions invocations per minute, and composing multiple functions developed with different languages to form a sequence.
Knative, OpenFass, and OpenWhisk provide many benefits for deploying serverless applications on Kubernetes, including the following:
- Autoscaling: Application workloads can be scaled up from zero when there is an increased traffic request on your application and can be reduced to zero when no request hits your application.
- Progressive rollouts: You can configure your application deployment strategy when there are new releases or versions, such as configuring blue-green deployments and canary deployments.
- Events: You can handle events from many sources and trigger workloads from specific events.
- Cloud deployment: You have the ability to deploy your application on any cloud infrastructure.
To deploy traditional workloads in Kubernetes, you need to create a YAML file that describes the deployment. This deployment file contains information such as the container image, the number of pod replicas, a service that matches the labels of the pods in order to expose the application on the Kubernetes network, and so on. Following is an example of a deployment file:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
labels:
app: nginx
spec:
replicas: 3
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.14.2
ports:
- containerPort: 80
However, serverless workloads have a different approach to deployment. In serverless, you don’t have to worry about the underlying infrastructure, which means that you run your container image on your cluster using any of the Kubernetes serverless tools mentioned previously, and everything is taken care of for you. This approach comes with a lot of benefits. For instance, once you deploy the application, the serverless tool automatically creates the required resources to run your application, which includes deployments and services.
Deciding when to use serverless workloads in Kubernetes is dependent on your needs. If you want to reduce the time it takes for your application to be deployed to the market, then a serverless workload is a good option compared to managing multiple deployments in traditional workloads.
If your application isn’t going to experience constant usage, then a serverless workload may be right for you because of the cost savings. With traditional workloads, you are consistently using compute resources, which your service provider will charge for at the end of the month whether you had incoming requests into your application or not.
Additionally, serverless architecture is platform agnostic, which means there is no vendor lock-in to any of the Kubernetes platform providers including Amazon EKS and Azure Kubernetes Service (AKS).
Before switching to a serverless workload, it’s also important to consider some of the disadvantages of using serverless workloads on Kubernetes. One of the major limitations is that the response time of the first request is higher than the subsequent requests because of the time it takes to create the first deployment and for the pod to respond. This phenomenon is known as cold start. Cold start can affect the performance of your app and reduce your application’s adoption rate.
Additionally, if you have a large application with a predictable workload, traditional servers might be better off than going with serverless computing because, in the long run, you save cost by setting up and optimizing your servers to the expected workload.
The point of building an application for Kubernetes is all about setting up your application for success. If you build it properly, Kubernetes can interact with the application without needing any workarounds.
If you need help with Kubernetes and implementing serverless functions, book a quick demo with our team of cloud experts.
