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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Google Cloud Platform
Score9 out of 10
N/A
Google Cloud Platform is a suite of cloud computing services used to build apps or take advantage of cloud infrastructural services, achieve legacy infrastructure modernization, or manage enterprise data and analytic needs.
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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When most of our stuff is in Google Cloud Platform, it works great to integrate and cross/share data that is all in Google Cloud Platform or BigQuery. It has simplified things from a permissions perspective as well. I'd say it is less appropriate when trying to test something quickly locally, or when half your stuff is in AWS or another provider.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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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The UI is so confusing. The console is good, but it is like a maze. There are too many menus and settings, and things do not work as expected. It takes time to get friendly, and it is not friendly for new users.
Support experience: Sometimes, you get a great engineer, but other times, it's very difficult to talk with them as they are unable to respond as expected and solve issues late.
Region and zone are issues, as not all services are available in all regions, which is lacking when deploying something in the same region or zone.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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 Google Cloud Platform console is pretty slick for BigQuery especially. I have liked the visibility I get from using that and the way to integrate and see what's in our data lake. The logging console for tracking GKE jobs isn't quite as great, which is why it doesn't get a full 10.
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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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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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Google Cloud Platform is release later than Amazon web service, I think that why Google Cloud Platform can learned and optimized the Dashboard and some features that make it easy to use and can be cheaper than amazon web service.
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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It allows us to focus our efforts on other, more important items at hand
It gives us an affordable option letting me know it's available to all users, not just the largest scale ones out there
The customer service is always helpful and reliable, along with the service itself which lets me focus on my work instead of worrying about the service.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
