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  1. Stackups
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  3. Kubeless vs OpenFaaS

Kubeless vs OpenFaaS

OverviewComparisonAlternatives

Overview

Kubeless
Kubeless
Stacks39
Followers195
Votes0
OpenFaaS
OpenFaaS
Stacks56
Followers234
Votes17
GitHub Stars26.0K
Forks2.0K

Kubeless vs OpenFaaS: What are the differences?

Introduction:

Kubeless and OpenFaaS are both serverless frameworks that allow developers to deploy and run functions in a containerized environment. While they share similar goals, there are several key differences between the two platforms that set them apart.

  1. Language Support: Kubeless supports a wider range of programming languages compared to OpenFaaS. With Kubeless, developers can write functions in languages such as Python, Node.js, Ruby, PHP, and more. In contrast, OpenFaaS primarily focuses on supporting functions written in Go and also provides support for other languages through community-contributed templates.

  2. Deployment Options: Kubeless is tightly integrated with Kubernetes and relies on it for deployment and scaling. This means that Kubeless functions are deployed as Kubernetes deployments and benefit from features like scaling, auto-healing, and rolling deployments. On the other hand, OpenFaaS provides more deployment flexibility as it can be deployed on any Kubernetes cluster, as well as other container orchestration platforms like Docker Swarm and Kubernetes in managed cloud services.

  3. Event Sources: Kubeless has a built-in event source mechanism that allows functions to be triggered by various events such as HTTP requests, message queues, or cron jobs. It provides out-of-the-box integrations with popular event sources like Kafka, NATS, RabbitMQ, and more. OpenFaaS, on the other hand, doesn't offer a native event source mechanism. Developers need to rely on external tools or services to trigger functions based on events.

  4. Scalability: Kubeless leverages the scalability features of Kubernetes to scale functions automatically based on demand. It supports both horizontal and vertical scaling, allowing functions to handle increased traffic or workload. OpenFaaS also provides scalability through worker nodes that can be added or removed to handle varying workloads, but it doesn't have the same level of integration with Kubernetes for automatic scaling.

  5. Community and Ecosystem: OpenFaaS has a larger and more active community compared to Kubeless. It has a wide range of community-contributed templates and plugins that extend its functionality and make it easier to integrate with popular tools and services. Kubeless, while still having an active community, doesn't have the same level of ecosystem maturity as OpenFaaS.

  6. Ease of Use: OpenFaaS provides a more user-friendly and intuitive user interface (UI) called the Gateway UI. The Gateway UI allows users to manage and deploy functions without the need for writing YAML files directly. Kubeless, on the other hand, requires users to interact with Kubernetes resources directly, which can be more complex and intimidating for beginners.

In summary, Kubeless and OpenFaaS differ in terms of language support, deployment options, event sources, scalability mechanisms, community and ecosystem support, as well as ease of use.

Detailed Comparison

Kubeless
Kubeless
OpenFaaS
OpenFaaS

Kubeless is a Kubernetes native serverless Framework. Kubeless supports both HTTP and event based functions triggers. It has a serverless plugin, a graphical user interface and multiple runtimes, including Python and Node.js.

Serverless Functions Made Simple for Docker and Kubernetes

Statistics
GitHub Stars
-
GitHub Stars
26.0K
GitHub Forks
-
GitHub Forks
2.0K
Stacks
39
Stacks
56
Followers
195
Followers
234
Votes
0
Votes
17
Pros & Cons
No community feedback yet
Pros
  • 5
    Open source
  • 4
    Ease
  • 3
    Autoscaling
  • 2
    Documentation
  • 2
    Community
Integrations
Docker
Docker
Kafka
Kafka
Zookeeper
Zookeeper
Serverless
Serverless
Kubernetes
Kubernetes
Kubernetes
Kubernetes
Docker
Docker

What are some alternatives to Kubeless, OpenFaaS?

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.

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.

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.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative

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

Nuclio

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Apache OpenWhisk

Apache OpenWhisk

OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.

Cloud Functions for Firebase

Cloud Functions for Firebase

Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.

AWS Batch

AWS Batch

It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.

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