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.
It's fine, it works as the others would have, except EC2. We are migrating back to EC2 for dedicated compute because we have scaled to a point where we have consistent traffic. The tradeoff of maintaining infrastructure in-house outweighs the benefits of moving quickly through …
We use AWS as our primary cloud provider due to the overall availability of services, AWS Lambda is just one of the services we use with AWS which allows a more seamless integration for our microservices. AWS Lambda gives us much more flexibility and can be invoked by more …
AWS Lambda is much easier to use than the near alternatives. It is so straightforward and lightweight it is my primary service for handling small transactions or triggers. The other services require more setup time and are more complex to use. AWS Lambda takes your code snippet …
We also use Google Cloud Functions because we use GCP in addition to AWS. AWS Lambda is comparable to Google Cloud Functions in its functionality. The main advantage of going with one or the other has to do with what resources it will interact with--we use AWS Lambda to …
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 …
When we use Lambda, we do not need to worry about the infrastructure and costs. AWS can handle it all on its own. For an optimum use case, one can always use AWS Lambda along with API Gateway and Route 53 for the best use case. Cloudwatch can help you identify any issues and …
I have used Azure Functions and Google Cloud Functions. In comparison, AWS Lambda is a bit more difficult to configure out of the gate. But in most cases once the function is in place and running the operation becomes completely hands-off. While I've used Azure Functions and …
Each service has its purpose. With EC2 you can provision servers for customers and internal projects. With EBs you can optimize what you need in performance with what you can afford. With AWS Lambda you can integrate several of these tools to work together or acomplish …
I've used Google Cloud Functions to create apps for Google Home devices. My students find this more difficult to use than AWS Lambda, especially when it comes to setting permissions.
We really did not evaluate them against other products except a little Google research, we are a centralized AWS customer so it was a smooth and simple (even if blind) decision for us.
Jenkins is a solution for CD/CI pipelines. We can leverage this tool to run code automatically. Long-lived applications and jobs can also be run through it.
AWS is a much more mature platform than Microsoft Azure but is a lot more rigid in the portability perspective. If you are in it for the long run then Lambda is great and the best choice.
Since our company heavily relies on AWS already, my team did not consider any other serverless platforms when building our applications. Lambda was chosen by "default", but it's also such a popular platform that we felt we couldn't go wrong.
These are all AWS sister products, so I wouldn't say they are competitors but tools in the same box. They all work quite well together and I would say combined they are greater than the sum of their parts. Cloudformation (and SAM) templates make tying them together pretty …
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 …
But other similar things I've used are Azure Functions and GCP Google Cloud Functions. Like all services like this, the support is pretty much the same. AWS Lambda supports enough popular languages, and behaves pretty much the same as all of these similar services. It does it's …
We considered using application deploy in EC2 with Auto Scale but ended up with AWS Lambda as it helps us to simplify our development and deployment process. It allows us to quickly create instances in a short time for processing data when the source application uploads data …
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Chose AWS Lambda
While AWS Lambda doesn't have the UI or the predefined functions that these other services provide, what was apparent to us is the cost saving and flexibility we have with AWS Lambda once we have it set up.
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.
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.
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
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.