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AWS Lambda

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18.6K
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Knative

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Serverless

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AWS Lambda vs Knative vs Serverless: What are the differences?

Introduction

AWS Lambda, Knative, and Serverless are all cloud computing services that allow developers to build and deploy applications without the need to provision or manage servers. However, there are key differences between these three services that make them unique in their own ways.

  1. Deployment Options: AWS Lambda allows you to deploy your code as a function in the AWS Lambda service, which is fully managed by Amazon Web Services. Knative, on the other hand, provides a Kubernetes-based platform that enables you to deploy your code as containers, allowing for more flexibility and portability. Serverless provides a framework that abstracts away the infrastructure layer and allows you to deploy your code as functions in a variety of cloud providers, including AWS Lambda, Google Cloud Functions, and Microsoft Azure Functions.

  2. Event Sources: AWS Lambda supports a wide range of event sources, including HTTP requests, S3 bucket events, DynamoDB streams, and more. Knative provides a similar event-driven architecture, but it is primarily designed to work with Kubernetes-native events. Serverless, being a framework, allows you to define event sources based on the cloud provider you are using, giving you the flexibility to choose from a wide range of options.

  3. Managed Services Integration: AWS Lambda integrates seamlessly with other AWS services, such as API Gateway, S3, DynamoDB, and more. Knative provides a similar level of integration with Kubernetes-native services and resources. Serverless, being a framework, offers integrations with multiple cloud providers, allowing you to leverage the managed services provided by each platform.

  4. Scaling: AWS Lambda and Knative both provide automatic scaling capabilities, allowing your code to scale up or down based on the incoming workload. AWS Lambda has a default limit of 1,000 concurrent executions per region, which can be increased upon request. Knative, being built on Kubernetes, leverages the Kubernetes Horizontal Pod Autoscaler to scale your containers based on the defined metrics. Serverless, being a framework, abstracts away the scaling mechanism, allowing you to focus on writing your code without worrying about the scaling implementation.

  5. Pricing Model: AWS Lambda charges you based on the number of invocations and the duration of the function executions. Knative, being an open-source project, does not have any direct pricing model, but you would incur costs for the underlying resources, such as Kubernetes clusters. Serverless, being a framework, allows you to choose from multiple cloud providers, each with its own pricing model. It provides cost optimization features, such as cold start reduction and request pooling, to help reduce costs.

  6. Vendor Lock-In: AWS Lambda and Knative both tie you to their respective cloud platforms, AWS and Kubernetes. Serverless, being a framework that supports multiple cloud providers, allows you to write serverless applications that are vendor-agnostic, giving you the flexibility to switch between cloud providers without significant code changes.

In summary, AWS Lambda, Knative, and Serverless are all powerful tools for building and deploying serverless applications, but they differ in their deployment options, event sources, managed services integration, scaling mechanisms, pricing models, and vendor lock-in.

Advice on AWS Lambda, Knative, and Serverless

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!

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Replies (2)
Anis Zehani

I recommend this : -Spring reactive for back end : the fact it's reactive (async) it consumes half of the resources that a sync platform needs (so less CPU -> less money). -Angular : Web Front end ; it's gives you the possibility to use PWA which is a cheap replacement for a mobile app (but more less popular). -Docker images. -Kubernetes to orchestrate all the containers. -I Use Jenkins / blueocean, ansible for my CI/CD (with Github of course) -AWS of course : u can run a K8S cluster there, make it multi AZ (availability zones) to be highly available, use a load balancer and an auto scaler and ur good to go. -You can store data by taking any managed DB or u can deploy ur own (cheap but risky).

You pay less money, but u need some technical 2 - 3 guys to make that done.

Good luck

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My advice will be Front end: React Backend: Language: Java, Kotlin. Database: SQL: Postgres, MySQL, Aurora NOSQL: Mongo db. Caching: Redis. Public : Spring Webflux for async public facing operation. Admin api: Spring boot, Hibrernate, Rest API. Build Container image. Kuberenetes: AWS EKS, AWS ECS, Google GKE. Use Jenkins for CI/CD pipeline. Buddy works is good for AWS. Static content: Host on AWS S3 bucket, Use Cloudfront or Cloudflare as CDN.

Serverless Solution: Api gateway Lambda, Serveless Aurora (SQL). AWS S3 bucket.

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Decisions about AWS Lambda, Knative, and Serverless

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

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Manage your open source components, licenses, and vulnerabilities
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Pros of AWS Lambda
Pros of Knative
Pros of Serverless
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
  • 12
    AWS Lambda went down taking many sites with it
  • 6
    Event Driven Governance
  • 6
    Extensive API
  • 6
    Auto scale and cost effective
  • 6
    Easy to deploy
  • 5
    VPC Support
  • 3
    Integrated with various AWS services
  • 5
    Portability
  • 4
    Autoscaling
  • 3
    Open source
  • 3
    Eventing
  • 3
    Secure Eventing
  • 3
    On top of Kubernetes
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    Auto scale
  • 1
    Openwhisk

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Cons of AWS Lambda
Cons of Knative
Cons of Serverless
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort
    Be the first to leave a con
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      - No public GitHub repository available -

      What is 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.

      What is 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

      What is 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.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use AWS Lambda?
      What companies use Knative?
      What companies use Serverless?

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      What tools integrate with AWS Lambda?
      What tools integrate with Knative?
      What tools integrate with Serverless?

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      What are some alternatives to AWS Lambda, Knative, and Serverless?
      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.
      AWS Elastic Beanstalk
      Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
      AWS Step Functions
      AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
      Google App Engine
      Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
      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.
      See all alternatives