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

AWS Lambda vs Knative

OverviewDecisionsComparisonAlternatives

Overview

AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432
Knative
Knative
Stacks86
Followers342
Votes21
GitHub Stars5.9K
Forks1.2K

AWS Lambda vs Knative: What are the differences?

Introduction AWS Lambda and Knative are two popular serverless computing platforms that allow developers to run code without having to provision or manage servers. While both platforms provide similar functionality, there are several key differences between them. This article will explore these differences in detail.

  1. Deployment Model: AWS Lambda follows a fully managed approach, where developers simply have to upload their code and the platform takes care of the rest. On the other hand, Knative is a Kubernetes-based platform that provides a more flexible and portable deployment model. It allows developers to leverage features of Kubernetes and deploy their functions anywhere, giving them more control over their infrastructure.

  2. Vendor Lock-in: AWS Lambda operates within the AWS ecosystem, which means that developers are tied to the AWS infrastructure and services provided by Amazon. In contrast, Knative is an open-source project that can run on any Kubernetes distribution, providing developers with more options and avoiding vendor lock-in. This makes Knative a more attractive choice for organizations looking for multi-cloud or hybrid-cloud deployments.

  3. Scaling: While both platforms support auto-scaling, AWS Lambda has a more fine-grained approach to scaling. It can scale individual functions independently based on the incoming workload, allowing for more efficient resource utilization. Knative, on the other hand, scales at the level of the entire container, which may result in over-provisioning or under-provisioning of resources depending on the workload.

  4. Pricing Model: AWS Lambda charges based on the number of requests and the duration of execution, with different pricing tiers for different regions. Knative, being an open-source project, does not have its own pricing model. Instead, the cost of running Knative functions depends on the underlying infrastructure on which it is deployed, such as Kubernetes clusters, which may incur additional costs.

  5. Event Sources: AWS Lambda provides a wide range of event sources, including HTTP requests, database updates, and file uploads, allowing developers to easily trigger their functions based on various inputs. Knative, being built on Kubernetes, also supports a variety of event sources but may require additional configuration to integrate with certain third-party services.

  6. Maturity and Ecosystem: AWS Lambda is a mature and well-established service that has been widely adopted by organizations of all sizes. It has a robust ecosystem of tools, integrations, and community support. Knative, on the other hand, is a relatively newer project and may not have the same level of maturity or community adoption. However, it benefits from being built on Kubernetes, which itself has a large and active community.

In Summary, AWS Lambda and Knative differ in their deployment model, vendor lock-in, scaling approach, pricing model, event sources, and maturity/ ecosystem. These differences make each platform more suitable for specific use cases and requirements.

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Advice on AWS Lambda, Knative

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

357k views357k
Comments
Mark
Mark

Nov 2, 2020

Needs adviceonMicrosoft AzureMicrosoft Azure

Need advice on what platform, systems and tools to use.

Evaluating whether to start a new digital business for which we will need to build a website that handles all traffic. Website only right now. May add smartphone apps later. No desktop app will ever be added. Website to serve various countries and languages. B2B and B2C type customers. Need to handle heavy traffic, be low cost, and scale well.

We are open to either build it on AWS or on Microsoft Azure.

Apologies if I'm leaving out some info. My first post. :) Thanks in advance!

133k views133k
Comments
Cory
Cory

Mar 28, 2021

Decided

Netlfiy Functions uses AWS Lambda under the hood, but Netlify adds some nice sugar. The biggest advantage is the local development experience with netlify-cli. This allows you to run your functions locally with local configuration or pull configs from the Netlify dashboard. I built a health-check endpoint in about 2 minutes, and my send-email function in less than an hour.

28.2k views28.2k
Comments

Detailed Comparison

AWS Lambda
AWS Lambda
Knative
Knative

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.

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

Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
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
26.0K
Stacks
86
Followers
18.8K
Followers
342
Votes
432
Votes
21
Pros & Cons
Pros
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
Cons
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort
Pros
  • 5
    Portability
  • 4
    Autoscaling
  • 3
    On top of Kubernetes
  • 3
    Eventing
  • 3
    Secure Eventing
Integrations
No integrations available
Google Kubernetes Engine
Google Kubernetes Engine

What are some alternatives to AWS Lambda, Knative?

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.

Fission

Fission

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.

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