AWS Lambda vs Graphcool Framework

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AWS Lambda

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AWS Lambda vs Graphcool Framework: What are the differences?

AWS Lambda: Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB. 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; Graphcool Framework: ⚡️ Framework to develop & deploy serverless GraphQL backends. Graphcool is an open-source backend development framework to develop and deploy production-ready GraphQL microservices. The Graphcool Framework is a comprehensive collection of building blocks covering the entire spectrum of developing modern, data-centric GraphQL APIs.

AWS Lambda and Graphcool Framework can be primarily classified as "Serverless / Task Processing" tools.

Some of the features offered by AWS Lambda are:

  • Extend other AWS services with custom logic
  • Build custom back-end services
  • Completely Automated Administration

On the other hand, Graphcool Framework provides the following key features:

  • GraphQL database: A GraphQL database that allows you to query, mutate & stream data via the GraphQL CRUD API. It also contains a powerful database migration tool that lets you define and evolve your data model using GraphQL SDL.
  • Powerful permission system: Protects your GraphQL API with a powerful permission system based on rules you define in terms of simple GraphQL permission queries.
  • GraphQL subscription API: With the Graphcool Framework, realtime functionality (based on GraphQL subscriptions) comes for free. Your mutations automatically publish subscription events to the event gateway which forwards updates to all subscribed clients.q
Advice on AWS Lambda and Graphcool Framework

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 and Graphcool Framework
Cory Bell

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.

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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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Pros of AWS Lambda
Pros of Graphcool Framework
  • 126
    No infrastructure
  • 81
    Cheap
  • 68
    Quick
  • 57
    Stateless
  • 47
    No deploy, no server, great sleep
  • 9
    AWS Lambda went down taking many sites with it
  • 5
    Easy to deploy
  • 5
    Event Driven Governance
  • 5
    Extensive API
  • 4
    Auto scale and cost effective
  • 3
    VPC Support
  • 1
    Integrated with various AWS services
  • 1
    Fun and quick to get started. Great customer support

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Cons of AWS Lambda
Cons of Graphcool Framework
  • 5
    Cant execute ruby or go
  • 0
    Can't execute PHP w/o significant effort
    Be the first to leave a con

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    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 Graphcool Framework?

    Graphcool is an open-source backend development framework to develop and deploy production-ready GraphQL microservices. The Graphcool Framework is a comprehensive collection of building blocks covering the entire spectrum of developing modern, data-centric GraphQL APIs.

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

    What companies use AWS Lambda?
    What companies use Graphcool Framework?
    See which teams inside your own company are using AWS Lambda or Graphcool Framework.
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    What tools integrate with AWS Lambda?
    What tools integrate with Graphcool Framework?

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    What are some alternatives to AWS Lambda and Graphcool Framework?
    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.
    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.
    See all alternatives