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Serverless and Kubernetes: Key Differences and Using them Together

What Is Kubernetes? 

Kubernetes, often abbreviated as K8s, is an open-source container orchestration platform from Google. It automates the deployment, management, and scaling of container-based applications, enabling software developers to focus on writing their code without worrying about the underlying infrastructure. 

Kubernetes clusters consist of a control plane and worker nodes. The control plane manages cluster-wide configurations, while worker nodes run containers inside pods. Key features include load balancing, self-healing, and horizontal scaling. 

Kubernetes has become an industry standard, supported by major cloud providers and a large ecosystem of tools and services, making it a popular choice for managing containerized applications.

What Is Serverless?  

Serverless computing is a cloud computing paradigm that abstracts away server management and infrastructure provisioning, allowing developers to focus on writing code for individual functions. In this model, cloud providers automatically allocate resources, scale the application based on demand, and charge users only for the actual compute time consumed, rather than pre-allocated resources.

Serverless computing simplifies application development, deployment, and maintenance by reducing the operational overhead. Popular serverless platforms include AWS Lambda, Microsoft Azure Functions, and Google Cloud Functions. While serverless offers advantages, it may not suit all use cases due to potential latency, vendor lock-in, and limitations in customization.

This is part of a series of articles about serverless monitoring

Serverless vs. Kubernetes: Key Differences 

Serverless and Kubernetes are two popular technologies used for deploying and managing applications, but they are designed for different use cases and offer different advantages. Here’s a comparison of Serverless and Kubernetes:


Serverless computing is an event-driven, managed execution environment where cloud providers dynamically allocate resources to run your application code. With serverless, you don’t need to manage any underlying infrastructure. Azure Functions, AWS Lambda, and Google Cloud Functions are examples of serverless platforms.

Kubernetes is a container orchestration platform that automates the scaling, management, and deployment of containerized applications. Kubernetes manages the infrastructure by distributing containers across clusters of virtual or physical machines.


Serverless platforms automatically scale your applications based on demand. This means that as the number of requests or events increases, the platform will allocate more resources to handle the load without any manual intervention.

Kubernetes also supports scaling, but it requires manual configuration of auto-scaling rules or the use of custom metrics to determine when to scale the application.


Serverless platforms typically use a pay-per-use pricing model, where you are billed for the number of requests and the duration of execution time. This can lead to cost savings, especially for applications with variable or unpredictable workloads.

Kubernetes requires you to provision and manage the application’s underlying infrastructure, such as virtual machines or physical servers. This can result in higher costs, particularly for applications with low or sporadic workloads.

Flexibility and control

Serverless platforms abstract away the underlying infrastructure, which can limit the level of control and customization available to developers. This can be a disadvantage for applications with specific infrastructure requirements or complex networking configurations.

Kubernetes provides a high level of flexibility and control over the infrastructure, allowing you to customize networking, storage, and compute resources as needed.

Running Serverless Frameworks on Kubernetes  

Serverless frameworks are tools that simplify the development, deployment, and management of serverless applications. They enable serverless computing on Kubernetes by providing a layer of abstraction, handling the orchestration of containerized functions while leveraging Kubernetes’ scalability and robustness.


OpenFaaS (Open Function as a Service) is an open-source, community-driven project that provides a platform for running serverless functions on Kubernetes. OpenFaaS focuses on simplicity, ease of use, and developer experience.

OpenFaaS has a modular architecture, consisting of the following components:

  • Gateway: The API gateway acts as the entry point for invoking functions and managing the system. It exposes a RESTful API and handles authentication, scaling, and routing requests to functions.
  • Function Watchdog: A lightweight process that runs inside each function container, enabling it to be triggered via HTTP. It also handles timeouts and monitoring.
  • Provider: A component that integrates OpenFaaS with the underlying platform, such as Kubernetes or Docker Swarm.
  • PromQL and AlertManager: These components are used for monitoring and auto-scaling. Metrics are collected via the Prometheus time-series database, while AlertManager triggers auto-scaling based on predefined rules.

Functions in OpenFaaS are packaged as Docker images, making it easy to build, distribute, and run them on any platform that supports Docker containers.


Knative is a Kubernetes-based open-source platform that simplifies building, deploying, and managing serverless applications. It is developed by Google in collaboration with other industry leaders like IBM, Red Hat, and Pivotal. Knative focuses on providing a set of middleware components that enable developers to use familiar idioms, languages, and frameworks.

Knative’s modular architecture comprises the following components:

  • Serving: Handles deploying, scaling, and managing serverless applications. It offers features like traffic splitting, gradual rollouts, and automatic scaling based on request concurrency. Serving utilizes Kubernetes Custom Resource Definitions (CRDs) for configuration, allowing it to integrate seamlessly with the Kubernetes ecosystem.
  • Eventing: Provides a declarative model for event-driven applications, enabling developers to consume and produce events from various sources without being tied to a specific messaging system. It supports multiple event sources and sinks, allowing for flexibility and extensibility.
  • Build: Aims to simplify building container images from source code, enabling developers to define build pipelines using familiar tools and languages. (Note: Knative Build has been deprecated in favor of Tekton Pipelines.)

Knative functions are Kubernetes-native, running inside containers as standard Kubernetes deployments, ensuring compatibility with existing tooling and infrastructure.


Apache OpenWhisk is an open-source, distributed serverless platform developed by IBM, designed to execute functions in response to events. It supports a variety of languages and can be deployed on various platforms, including Kubernetes.

OpenWhisk’s architecture consists of the following components:

  • Controller: The central component responsible for managing and orchestrating system functions. It exposes a RESTful API for managing actions, triggers, and rules, and communicates with other components to execute functions and handle events.
  • Invoker: A pool of worker nodes responsible for running functions inside containers. Invokers receive requests from the Controller and manage the lifecycle of containers, ensuring efficient resource utilization.
  • Message Bus (Kafka): Facilitates communication between components, ensuring reliable and scalable message delivery.
  • CouchDB: A NoSQL database used for storing system metadata, such as action definitions, triggers, and rules.

Functions in OpenWhisk are packaged as Docker images or as platform-specific artifacts, allowing flexibility and portability across different platforms.


Fission is an open-source, Kubernetes-native serverless framework focused on providing a fast, simple, and efficient platform for running functions. Fission emphasizes a short cold-start time and seamless integration with the Kubernetes ecosystem.

Fission’s architecture comprises the following components:

  • Controller: Manages the function lifecycle, including creation, deletion, and updates. The controller communicates with other components and exposes a RESTful API for managing functions, triggers, and environments.
  • Executor: Handles function execution and manages the underlying resources, such as creating and recycling Kubernetes pods.
  • Router: Acts as an entry point for function invocations, forwarding HTTP requests to the appropriate function instances. It also handles function versioning and canary deployments.
  • Environment: Represents a runtime for a specific programming language or framework. Environments are container images with the necessary dependencies for running functions in a particular language.
  • Trigger: Associates events or requests with functions, enabling event-driven function execution. Fission supports various triggers, including HTTP, message queue, and time-based triggers.

Monitoring and troubleshooting for Microservices

Lumigo is a distributed tracing platform purpose-built for troubleshooting microservices in production. Developers building serverless apps with Kubernetes, Amazon ECS, AWS Lambda or other services use Lumigo to monitor, trace and troubleshoot their microservice-based applications. Deployed with no changes and automated in one-click, Lumigo stitches together every interaction between micro and managed services into end-to-end stack traces, giving complete visibility into serverless environments. Using Lumigo to monitor and troubleshoot their applications, developers get:

  • End-to-end virtual stack traces across every micro and managed service that makes up a serverless application, in context
  • API visibility that makes all the data passed between services available and accessible, making it possible to perform root cause analysis without digging through logs 
  • Distributed tracing that is deployed with no code and automated in one click 
  • Unified platform to explore and query across microservices, see a real-time view of applications, and optimize performance 

Learn more about Lumigo