AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
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Azure Functions
Score 9.2 out of 10
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Azure Functions enables users to execute event-driven serverless code functions with an end-to-end development experience.
[AWS Lambda] is very well suited for the projects that doesn't have any infra but needs it where short running processes are required. But if your application need to run continuously than this might not be the very apt tool for you.
They're great to embed logic and code in a medium-small, cloud-native application, but they can become quite limiting for complex, enterprise applications.
Lambda provides multiple methods for triggering functions, this includes AWS resources and services and external triggers like APIs and CLI calls.
The compute provided my Lambda is largely hands off for operations teams. Once the function is deployed, the management overhead is minimal since there are no servers to maintain.
Lambda's pricing can be very cost effective given that users are only charged for the time the function runs and associated costs like network or storage if those are used. A function that executes quickly and is not called often can cost next to nothing.
They natively integrate with many triggers from other Azure services, like Blob Storage or Event Grid, which is super handy when creating cloud-native applications on Azure (data wrangling pipelines, business process automation, data ingestion for IoT, ...)
They natively support many common languages and frameworks, which makes them easily approachable by teams with a diverse background
They are cheap solutions for low-usage or "seasonal" applications that exhibits a recurring usage/non-usage pattern (batch processing, montly reports, ...)
Putting a significant portion of your codebase into AWS Lambda and taking advantage of the high level of integration with other AWS services comes with the risk of vendor lock-in.
While the AWS Lambda environment is "not your problem," it's also not at your disposal to extend or modify, nor does it preserve state between function executions.
AWS Lambda functions are subject to strict time limitations, and will be aborted if they exceed five minutes of execution time. This can be a problem for some longer-running tasks that are otherwise well-suited to serverless delivery.
My biggest complaint is that they promote a development model that tightly couples the infrastructure with the app logic. This can be fine in many scenarios, but it can take some time to build the right abstractions if you want to decouple you application from this deployment model. This is true at least using .NET functions.
In some points, they "leak" their abstraction and - from what I understood - they're actually based on the App Service/Web App "WebJob SDK" infrastructure. This makes sense, since they also share some legacy behavior from their ancestor.
For larger projects, their mixing of logic, code and infrastructure can become difficult to manage. In these situations, good App Services or brand new Container Apps could be a better fit.
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
I have not needed support for AWS Lambda, since it is already using Python, which has resources all over the internet. AWS blog posts have information about how to install some libraries, which is necessary for some more complex operations, but this is available online and didn't require specific customer support for.
Azure Functions is another product that provides lambda functionality, but the documentation for some of Azure's products is quite hard to read. Additionally, AWS Lambda was one of the first cloud computing products on a large cloud service that implemented lambda functions, so they have had the most time to develop the product, increase the quality of service, and extend functionality to more languages. Amazon, by far, has the best service for Lambda that I know.
This is the most straightforward and easy-to-implement server less solution. App Service is great, but it's designed for websites, and it cannot scale automatically as easily as Azure Functions. Container Apps is a robust and scalable choice, but they need much more planning, development and general work to implement. Container Instances are the same as Container Apps, but they are extremely more limited in termos of capacity. Kubernetes Service si the classic pod container on Azure, but it requires highly skilled professional, and there are not many scenario where it should be used, especially in smaller teams.
I was able to perform a lot of processing on data delivered from my website and little or no cost. This was a big plus to me.
Programming AWS Lambda is quite easy once you understand the time limits to the functions.
AWS Lambda has really good integration with the AWS S3 storage system. This a very good method of delivering data to be processed and a good place to pick it up after processing.
They allowed me to create solutions with low TCO for the customer, which loves the result and the low price, that helped me create solutions for more clients in less time.
You can save up to 100% of your compute bill, if you stay under a certain tenant conditions.
