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AWS Lambda

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Advice on AWS Lambda, Azure Functions, and Knative

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, Azure Functions, and Knative

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 Azure Functions
Pros of Knative
  • 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
  • 12
    Pay only when invoked
  • 8
    Great developer experience for C#
  • 6
    Multiple languages supported
  • 5
    Great debugging support
  • 2
    Can be used as lightweight https service
  • 2
    Poor developer experience for C#
  • 2
    Easy scalability
  • 1
    Event driven
  • 1
    WebHooks
  • 1
    Azure component events for Storage, services etc
  • 4
    Portability
  • 3
    On top of Kubernetes
  • 3
    Autoscaling
  • 2
    Eventing
  • 2
    Open source
  • 1
    Secure Eventing

Sign up to add or upvote prosMake informed product decisions

Cons of AWS Lambda
Cons of Azure Functions
Cons of Knative
  • 5
    Cant execute ruby or go
  • 0
    Can't execute PHP w/o significant effort
  • 1
    No persistent (writable) file system available
  • 1
    Poor support for Linux environments
  • 1
    Sporadic server & language runtime issues
  • 1
    Not suited for long-running applications
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -
    - 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 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.

    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

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    What companies use AWS Lambda?
    What companies use Azure Functions?
    What companies use Knative?

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    What tools integrate with AWS Lambda?
    What tools integrate with Azure Functions?
    What tools integrate with Knative?

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    Blog Posts

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    What are some alternatives to AWS Lambda, Azure Functions, and Knative?
    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.
    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