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.
$NaN
Per 1 ms
Azure App Service
Score 8.6 out of 10
N/A
The Microsoft Azure App Service is a PaaS that enables users to build, deploy, and scale web apps and APIs, a fully managed service with built-in infrastructure maintenance, security patching, and scaling. Includes Azure Web Apps, Azure Mobile Apps, Azure API Apps, allowing developers to use popular frameworks including .NET, .NET Core, Java, Node.js, Python, PHP, and Ruby.
$9.49
per month
Pricing
AWS Lambda
Azure App Service
Editions & Modules
128 MB
$0.0000000021
Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
Shared Environment for dev/test
$9.49
per month
Basic Dedicated environment for dev/test
$54.75
per month
Standard Run production workloads
$73
per month
Premium Enhanced performance and scale
$146
per month
Offerings
Pricing Offerings
AWS Lambda
Azure App Service
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Free and Shared (preview) plans are ideal for testing applications in a managed Azure environment. Basic, Standard and Premium plans are for production workloads and run on dedicated Virtual Machine instances. Each instance can support multiple applications and domains.
More Pricing Information
Community Pulse
AWS Lambda
Azure App Service
Considered Both Products
AWS Lambda
Verified User
Engineer
Chose AWS Lambda
AWS is great product and a close match our expectations. It is close to Azure in function but more feature rich with API and support documents. From my experience, it is cheaper compared with our competitors and provides better interface. Overall our dev engineers prefer AWS …
I've worked previously with Azure Functions which seems to be the direct competitor to AWS Lambda and while Azure Functions worked just fine there seemed to be more configuration and "magic" behind the scenes to it compared to AWS Lambda which is very straight forward. I …
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
You may easily deploy your apps to Azure App Service if they were written in Visual Studio IDE (typically.NET applications). With a few clicks of the mouse, you may already deploy your application to a remote server using the Visual Studio IDE. As a result of the portal's bulk and complexity, I propose Heroku for less-experienced developers.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
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.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
We had an issue where we deployed too large of a resource and didn't notice until the bill came through. They were very understanding and saw we weren't utilizing the resources so they issued a generous refund in about 4 hours. Very fast, friendly, and understanding support reps from my experience.
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
Azure has many data center, their services are more reliable. Azure has way more features than both Linode and DigitalOcean. If someone wants a complete reliable service, he/she must go to Azure instead of Linode and DigitalOcean because even though azure charges more, it is worth the money you pay there.
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.
