AWS Lambda vs Red Hat OpenShift

• 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.

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• The same as many similar K8 vendor solutions, OpenShift provides a managed Kubernetes environment with advanced facilitative components built-in.
• It provides the life cycle management/monitoring toolset to help users better visualize and understand both the application and infrastructure environment.
• Provides the scaling and recovering mechanism to ensure the high resilience of the application.
• CI/CD pipeline integration following the DevOps concept.

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• 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.

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• The shift from v2 to v3 was a huge transition, and Red Hat [OpenShift] really failed at making this step easy for users - their documentation at the time was fairly lacking
• When things go wrong it can be hard to diagnose

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• 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.

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• Reduce [the] friction of monitoring environments. This leads to [a] quicker troubleshooting process.
• Completely remove the need to authenticate each and every time you want to check on a specific environment.
• Faster deployment workflow increases [the] efficiency of developers when testing in lower environment containers.

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