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  3. Knative vs Kubernetes

Knative vs Kubernetes

OverviewDecisionsComparisonAlternatives

Overview

Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685
Knative
Knative
Stacks87
Followers342
Votes21
GitHub Stars5.9K
Forks1.2K

Knative vs Kubernetes: What are the differences?

Key Differences between Knative and Kubernetes

Knative and Kubernetes are both popular open-source platforms used for managing containerized applications and services. While they share some similarities, there are key differences between the two platforms that set them apart.

  1. Abstraction Level: Kubernetes is a container orchestration platform that provides a robust infrastructure for managing and scaling containerized applications. It focuses on providing a scalable and reliable infrastructure layer for containers, allowing developers to deploy, manage, and scale applications. On the other hand, Knative is built on top of Kubernetes and adds a higher-level abstraction specifically for serverless workloads. Knative abstracts away the infrastructure concerns and provides developers with a serverless experience, enabling them to focus solely on writing code without worrying about the underlying infrastructure.

  2. Serverless Support: One of the key differences between Knative and Kubernetes is their support for serverless computing. While Kubernetes can run serverless workloads using custom configurations or external tools like Kubeless or OpenFaaS, Knative is specifically designed for serverless applications. Knative provides a set of building blocks for event-driven, auto-scaling, and managed container workloads, making it easier to develop, deploy, and manage serverless applications.

  3. Auto-scaling and Event-driven Scaling: Knative offers built-in auto-scaling capabilities for serverless workloads. It can automatically scale up or down based on the incoming traffic or events. This makes Knative well-suited for handling variable workloads and bursty traffic patterns. In contrast, while Kubernetes also has auto-scaling capabilities, it requires additional setup and configuration to achieve the same level of auto-scaling and event-driven scaling as offered by Knative.

  4. Workload Abstraction and Portability: Kubernetes provides a generic platform for managing containerized workloads and has a highly flexible and extensible architecture. It allows running various types of workloads, including stateful and stateless applications and provides a wide range of options for customization and portability. Knative, on the other hand, focuses specifically on serverless workloads and provides a higher-level abstraction for building serverless applications. While Knative uses Kubernetes under the hood, its abstraction is more tailored towards serverless use cases and provides additional abstractions and APIs specifically for serverless development.

  5. Ease of Use and Developer Experience: Kubernetes can have a steep learning curve, especially for developers new to container orchestration. It requires understanding various concepts, such as pods, services, deployments, and networking, to effectively deploy and manage applications. Knative, being a higher-level abstraction built on top of Kubernetes, provides a simpler and more intuitive developer experience for serverless workloads. It offers a higher-level API and abstracts away most of the infrastructure concerns, allowing developers to focus more on writing code and less on managing infrastructure.

  6. Community and Maturity: Kubernetes has been around for a longer time and has a larger community and ecosystem compared to Knative. It has become the de facto standard for container orchestration and has widespread adoption in the industry. Knative, being a relatively newer project, has a smaller but growing community. While it is gaining popularity, it may not have the same breadth of community-contributed tools and integrations as Kubernetes.

In summary, Knative provides a higher-level abstraction for serverless workloads on top of Kubernetes, offering built-in serverless support, auto-scaling capabilities, simplified developer experience, and tailored abstractions for serverless development. Kubernetes, on the other hand, provides a more generic platform for managing containerized workloads with a larger community and ecosystem.

Advice on Kubernetes, Knative

Simon
Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

DecidedonGitHubGitHubGitHub PagesGitHub PagesMarkdownMarkdown

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
12.8M views12.8M
Comments

Detailed Comparison

Kubernetes
Kubernetes
Knative
Knative

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

Lightweight, simple and accessible;Built for a multi-cloud world, public, private or hybrid;Highly modular, designed so that all of its components are easily swappable
Serving - Scale to zero, request-driven compute model; Build - Cloud-native source to container orchestration; Events - Universal subscription, delivery and management of events; Serverless add-on on GKE - Enable GCP managed serverless stack on Kubernetes
Statistics
GitHub Stars
-
GitHub Stars
5.9K
GitHub Forks
-
GitHub Forks
1.2K
Stacks
61.2K
Stacks
87
Followers
52.8K
Followers
342
Votes
685
Votes
21
Pros & Cons
Pros
  • 166
    Leading docker container management solution
  • 130
    Simple and powerful
  • 108
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
Cons
  • 16
    Steep learning curve
  • 15
    Poor workflow for development
  • 8
    Orchestrates only infrastructure
  • 4
    High resource requirements for on-prem clusters
  • 2
    Too heavy for simple systems
Pros
  • 5
    Portability
  • 4
    Autoscaling
  • 3
    On top of Kubernetes
  • 3
    Secure Eventing
  • 3
    Eventing
Integrations
Vagrant
Vagrant
Docker
Docker
Rackspace Cloud Servers
Rackspace Cloud Servers
Microsoft Azure
Microsoft Azure
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Google Kubernetes Engine
Google Kubernetes Engine
Google Kubernetes Engine
Google Kubernetes Engine

What are some alternatives to Kubernetes, Knative?

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

AWS Lambda

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Azure Functions

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

Serverless

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

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