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AWS Lambda vs Azure Functions vs Cloud Functions for Firebase: What are the differences?
Introduction:
AWS Lambda, Azure Functions, and Cloud Functions for Firebase are serverless compute services that allow developers to run code without managing servers. Here are some key differences between them:
1. **Programming Languages Support**: AWS Lambda supports a variety of programming languages including Node.js, Python, Ruby, Java, and C#. Azure Functions also supports multiple languages, including C#, F#, Node.js, Python, PHP, and TypeScript. On the other hand, Cloud Functions for Firebase primarily supports Node.js but can be extended to support other languages using a Node.js shim.
2. **Triggers and Events**: AWS Lambda can be triggered by various events such as API Gateway requests, S3 bucket events, and DynamoDB streams. Azure Functions also offer similar event triggers along with a wide range of services like GitHub, Azure Blob Storage, and more. Cloud Functions for Firebase are tightly integrated with Firebase services and can be triggered by HTTP requests, Firebase Realtime Database events, Firebase Authentication events, and Firebase Analytics events.
3. **Pricing Model**: AWS Lambda pricing is based on the number of requests and compute time, with a free tier for limited usage. Azure Functions have similar pricing based on the number of executions and resource consumption. Cloud Functions for Firebase are priced based on the number of invocations and the compute time required.
4. **Platform Integration**: AWS Lambda integrates seamlessly with other AWS services, allowing for easy scaling and management of resources within the AWS ecosystem. Azure Functions have tight integration with Azure services, enabling developers to leverage various cloud services easily. Cloud Functions for Firebase are specifically designed to work with Firebase ecosystem services, providing a streamlined development experience for mobile and web applications.
5. **Scaling**: AWS Lambda automatically scales based on the incoming load, ensuring that resources are provisioned as needed. Azure Functions also offer automatic scaling based on the number of incoming requests. Cloud Functions for Firebase also provide auto-scaling capabilities to handle varying workloads efficiently.
6. **Development Environment**: AWS Lambda offers a local development environment for testing functions before deployment. Azure Functions also provide a local development environment with debugging capabilities. Cloud Functions for Firebase can be tested locally using the Firebase CLI tools, enabling developers to simulate function triggers and responses before deploying to the cloud.
In Summary, AWS Lambda, Azure Functions, and Cloud Functions for Firebase differ in terms of programming language support, triggers and events, pricing model, platform integration, scaling capabilities, and development environment options.
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!
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
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.
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.
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
Pros of AWS Lambda
- No infrastructure129
- Cheap83
- Quick70
- Stateless59
- No deploy, no server, great sleep47
- AWS Lambda went down taking many sites with it12
- Event Driven Governance6
- Extensive API6
- Auto scale and cost effective6
- Easy to deploy6
- VPC Support5
- Integrated with various AWS services3
Pros of Azure Functions
- Pay only when invoked14
- Great developer experience for C#11
- Multiple languages supported9
- Great debugging support7
- Can be used as lightweight https service5
- Easy scalability4
- WebHooks3
- Costo3
- Event driven2
- Azure component events for Storage, services etc2
- Poor developer experience for C#2
Pros of Cloud Functions for Firebase
- Up and running4
- Multi-region1
- Affordable1
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Cons of AWS Lambda
- Cant execute ruby or go7
- Compute time limited3
- Can't execute PHP w/o significant effort1
Cons of Azure Functions
- No persistent (writable) file system available1
- Poor support for Linux environments1
- Sporadic server & language runtime issues1
- Not suited for long-running applications1
Cons of Cloud Functions for Firebase
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What is AWS Lambda?
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