Kubernetes and Serverless architecture are significantly reshaping modern application development and deployment practices. Despite some commonalities, both solutions fit different business models and application requirements.

While Serverless architecture provides a logical abstraction of application components, it is not preferable for all applications. Similarly, organizations turning to containerization for scalability would have to invest in infrastructure and resource management, which is not feasible in all cases. Therefore, it counters the common perception that the two technologies are replaceable. 

This post will analyze Kubernetes vs. Serverless computing debate, explore their differences and similarities, and discover which of the two best meets your business needs.

Kubernetes is an open-source container orchestration framework for provisioning and managing containerized applications. Kubernetes automates deployment workloads and scales applications as per requirements. With Kubernetes, the developers have complete control over network, deployment, and containerization infrastructure like nodes, pods, and clusters.

Serverless is the cloud-based software deployment architecture that allows developers to build and run small, self-contained services known as serverless functions with managed internal infrastructure. It is important to clarify that serverless functions do run on servers, but the development or DevOps team does not manage them. 

Users simply purchase computing time for their functions and provide their code to the serverless management system. The cloud provider handles resource allocation and dependency issues behind the scenes.

At times, software development teams use the two technologies together by building Serverless solutions on top of Kubernetes containers. This combination provides Serverless prototyping speed and Kubernetes performance and scalability for building robust applications with a quicker time to market. However, this combination is only implemented depending on the project's requirements.

Kubernetes and Serverless are different technologies with overlapping properties and use cases, exhibiting some high-level similarities.

With Kubernetes and Serverless, organizations can:

• apply microservice architecture
  
• launch web-based and software applications in the cloud
  
• reduce the operational complexity of the production environment
  
• scale applications on demand
  
• work via third-party tools or APIs
  
• execute applications without delay
  
• save virtual machine overhead
  
• automate deployment workloads with DevOps practices to release consistent application code
  
• provide compartmentalized environments for the host operating system and software applications
  

As mentioned above, Kubernetes and Serverless technologies seem identical in their properties and are often considered substitutes. However, the two platforms serve distinct organizational needs. Therefore, it's important to note the differences between these frameworks. 

Let’s compare the differentiating features of Kubernetes and Serverless architecture below.

• Cost: Every major cloud provider offers managed Kubernetes system and serverless architecture as a cloud service at different costs.In a serverless platform, users pay on the go–only for the services or resources consumed, such as computing power to execute serverless functions, optimizing huge infrastructure costs for resource-intensive workloads.Kubernetes providers charge users for provisioning and managing clusters which typically includes container runtime cost per container per hour.
  
• Environment: In a serverless environment, the cloud provider controls the underlying infrastructure management. Users can’t select infrastructure or install server software of their choice.In a Kubernetes setup, the DevOps team can manage the underlying infrastructure with complete control, decide the operating system, and perform custom software configurations for their containerized applications.
  
• Runtime: Serverless functions are set to run for a short duration. They shut down immediately after event completion.Kubernetes containers have no runtime-based time constraints. These containers can run for longer durations.
  
• Integration: Serverless models have native integration with several other cloud services. Containers support integration with relatively fewer cloud services.
  
• Development: In a serverless architecture, moving processes outside the cloud is complex. In comparison, Kubernetes containers can run and deploy code in a local data center or migrate to other cloud providers and still work in the same manner. 
  
• Complexity: Serverless computing has no operational complexities. While working on Kubernetes containers, the DevOps team would have to handle system settings, libraries, dependencies, etc. 
  
• Scalability: The serverless architecture scales automatically on usage without requiring additional configurations. But, in a Kubernetes deployment model, containers need Horizontal Pod Autoscaling or Cluster Autoscaling configuration to scale nodes and pods. 
  
• Resource Allocation: A Serverless system allocates memory and CPU resources proportionally. Based on workload, the Kubernetes structure allows users to perform CPU allocation and select underlying infrastructure types.
  

More businesses are shifting to containers and microservices-based development models. As a result, the need for container management tools has increased. Almost half of the organizations using container environments employ Kubernetes for container orchestration. 

To advance the Kubernetes vs. Serverless debate, let’s highlight the use cases where Kubernetes can be the best deployment option.

• Resource Management and Environment Control: Kubernetes containers are ideal if you prefer complete control over the underlying infrastructure or the application hosting environment. Kubernetes allows you to select the root operating system, run applications in the language of your choice, and manage software and dependencies. This flexibility allows legacy or monolithic applications to be migrated to the containerization model effectively.
  
• Lengthy Job Execution: Serverless (such as AWS Lambda) runs for a fixed duration (15 minutes per execution), terminating the function under execution regardless of the state. If you have long batch tasks, Kubernetes lets you divide them into small, more manageable chunks to execute seamlessly. 
  
• Consistent and Predictable Traffic: Kubernetes infrastructure is a cost-effective and reliable solution for an even predictable application load. Moreover, Kubernetes load balancing distributes network traffic evenly among deployed clusters.
  
• Stateful Components Architecture: If your architecture comprises stateful components like in-memory caches relying on the internal application state or persistent storage, consider Kubernetes and containerization because they favor stateful applications.
  
• Development: In a serverless architecture, moving processes outside the cloud is complex. In comparison, Kubernetes containers can run and deploy code in a local data center or migrate to other cloud providers and still work in the same manner. 
  
• Complexity: Serverless computing has no operational complexities. While working on Kubernetes containers, the DevOps team would have to handle system settings, libraries, dependencies, etc. 
  
• Scalability: The serverless architecture scales automatically on usage without requiring additional configurations. But, in a Kubernetes deployment model, containers need Horizontal Pod Autoscaling or Cluster Autoscaling configuration to scale nodes and pods. 
  
• Resource Allocation: A Serverless system allocates memory and CPU resources proportionally. Based on workload, the Kubernetes structure allows users to perform CPU allocation and select underlying infrastructure types.
  

After AWS Serverless architecture gained momentum, Azure and Google also launched their Serverless architecture versions. As a result, the serverless ecosystem has matured significantly. Over half of the cloud organizations have recently adopted serverless technologies due to the growing cloud options and promising features. 

Serverless architecture can be a good option for the following cases:

• Reduce Operational Effort: If you want to avoid the provisioning and management of infrastructure, resources, servers, or networks, you can just provide code to the Serverless service provider, and it handles the rest.
  
• Optimize Time-to-Market: When organizations want to focus on quick code development and deployment, Serverless architecture lets them prioritize and optimize delivery rather than worrying about dependencies and infrastructure management.
  
• Pay-on-Use Low-Cost Model: For startups and companies with newly launched products, Serverless saves cost overhead when there’s no traffic, scales on a surge, and charges for only the compute used.
  
• Unpredictable Load: Capacity planning or traffic prediction is not feasible in every case. Serverless computing offers unlimited scalability with optimized infrastructure provisioning, which is way better than resizing Kubernetes clusters, pods, or disks.
  
• Build Applications with Function as a Service (FaaS): Serverless systems prefer models with stateless functions using an event-driven approach that favors edge computing and microservices design. FaaS allows developers to write, update, and execute small chunks of code on the fly. 
  

The rise of Serverless computing is not an indicator of Kubernetes' decline. With defined roles, both technologies are equally important in modern application development and deployment. 

In the future, the distinction between Kubernetes and Serverless is expected to fade, as the demand for both is expected to increase side by side. So, the Kubernetes vs. Serverless debate should be laid to rest. 

Instead, the software development community should focus on delivering high-quality applications aligned with their business requirements, regardless of which deployment method is employed. We can use each model individually or together, enjoying the best of both worlds.

harpoon’s no-code Kubernetes deployment tool can seamlessly automate, autoscale, and deploy code to your preferred environment using top-industry practices. To learn more about harpoon, book a demo or just try it for free.