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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. Fission vs Knative

Fission vs Knative

OverviewComparisonAlternatives

Overview

Fission
Fission
Stacks27
Followers81
Votes3
GitHub Stars8.8K
Forks788
Knative
Knative
Stacks86
Followers342
Votes21
GitHub Stars5.9K
Forks1.2K

Fission vs Knative: What are the differences?

Key Differences between Fission and Knative

Fission and Knative are both serverless platforms designed to simplify application development and deployment. However, there are several key differences between them.

  1. Flexibility of Language Support: Fission offers greater flexibility when it comes to language support, as it allows developers to write functions in any programming language, including popular choices like Python, Node.js, and Go. On the other hand, while Knative provides support for multiple languages, it focuses primarily on Docker containers, limiting the language choices available.

  2. Deployment Mechanism: Fission uses a "hot function" model where functions are kept in a running state, ready to be executed when an event occurs. This allows for faster response times and lower latency. In contrast, Knative follows a "cold start" model where functions are scaled to zero when not in use and require some time to start up when an event triggers their execution.

  3. Scalability: Knative offers more advanced and flexible scaling capabilities compared to Fission. Knative's scaling is based on the number of incoming requests, allowing for horizontal scaling of functions as per demand. Fission, while it provides auto-scaling based on CPU usage, does not have the same level of granular control as Knative.

  4. Integration with Kubernetes: Both Fission and Knative are built on top of Kubernetes but have different levels of integration. Knative provides a more seamless integration with Kubernetes, making it easier to manage and deploy functions as Kubernetes resources. Fission, while it also runs on Kubernetes, has a separate controller and a custom resource definition to manage functions.

  5. Eventing and Messaging Support: Knative has built-in support for eventing and messaging through its eventing subsystem, which allows for easy integration with various event sources and messaging systems. Fission, on the other hand, lacks native eventing support and requires additional components or external tools to achieve similar functionality.

  6. Community Support and Maturity: Knative has a larger and more active community compared to Fission, which translates into better support, more frequent updates, and a wider range of available resources. Fission, while still actively maintained, may have a smaller community and fewer resources.

In summary, Fission and Knative differ in terms of language support, deployment mechanism, scalability, Kubernetes integration, eventing support, and community maturity. Choosing between the two depends on the specific requirements and priorities of the application being developed.

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Detailed Comparison

Fission
Fission
Knative
Knative

Write short-lived functions in any language, and map them to HTTP requests (or other event triggers). Deploy functions instantly with one command. There are no containers to build, and no Docker registries to manage.

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

-
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
8.8K
GitHub Stars
5.9K
GitHub Forks
788
GitHub Forks
1.2K
Stacks
27
Stacks
86
Followers
81
Followers
342
Votes
3
Votes
21
Pros & Cons
Pros
  • 1
    Open source
  • 1
    Portability
  • 1
    Any language
Pros
  • 5
    Portability
  • 4
    Autoscaling
  • 3
    Eventing
  • 3
    Secure Eventing
  • 3
    On top of Kubernetes
Integrations
Kubernetes
Kubernetes
Docker
Docker
Google Kubernetes Engine
Google Kubernetes Engine

What are some alternatives to Fission, Knative?

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

OpenFaaS

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

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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