AWS Lambda vs. Google Cloud Functions

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.

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Any sort of transaction or complex logic that is going to take longer than 250ms or accesses resources that are protected by permissions, secrets, etc. is a great use case for a GCF. Some sort of "helper function" associated strictly with the UI inside browser would not be a good application of a GCF. It would not be crazy to create/debug some fairly complicated logic inside the browser/IDE and when perfected package it up as a Google Cloud Function. I have done that many times.

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• No provisioning required - we don't have to pay anything upfront
• Serverless deployment - it gets executed only when request comes and we pay only for the time the request is getting executed
• Integrates well with AWS CloudWatch triggers so it is easy to setup scheduled tasks like cron jobs

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• integration with oAuth
• integration with Firebase
• integration with React Frontend

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• 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.

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• Needing a zip file is problematic (when wanting to automate deployment for example).
• Requires another solution to execute automatically (ex. cloud scheduler).

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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.

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The console UI is pretty nasty. Managing various authentication/permissions configurations is just a nightmare. On the other hand, once you are over the hump it's not so bad. AWS Lambda is no better.

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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.

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Documentation is provided and clear for this service. Although GCP support is included in the current contract we didn't get to use it since the process is pretty straightforward.

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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

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It is easier to keep everything in house when we are using GCP or AWS. To mix Lambda with google cloud is not a best practice and will cause problems ahead. The segmentation is clear, if you are using google, you use Google Cloud Functions. if you are on Amazon, you use all AWS tools. You can't mix them. The price is set.

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• 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.

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• For training purposes, it is free
• Budgeting makes it cap the use
• monitoring makes it predictable

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