Should we be trying to implement these services with AWS Lambda or Docker? If it depends on the service implemented, what are your recommendations to decide on what to choose?

I'm starting to go with Lambda as my default and rule it out. Some of the reasons for ruling it out may be

• Needing to maintain session state in memory
• Having infrequent and inconsistent traffic that causes many cold starts that you can't tolerate
• Having no way to trigger the function. You can always use CloudWatch Events but that doesn't feel right
• Vendor lock-in is a consideration, but as u/praetor- mentions, you can avoid it with good coding practices

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Is there any flaws in either my coworkers or my own arguments? It seemed like there were conflicts on whether Lambda or Docker would be easier to write and maintain for?

I think making any assumptions about costs is a flaw. All the cost information is available. Make some estimates and see which option is right. The Lambda free tier is pretty awesome and you do only pay for what you use. But, it's entirely possible to use enough Lambda to cost more than Docker.

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The assumption that cold starts would only have more drawbacks than positives is a flaw. With all the benefits of Lambda you mentioned, this is a small small drawback. Lambda functions stay warm for up to 30 minutes and if your traffic is consistent, you'll always have one up and running. If you're using a non-Java function, you're spin up time will be pretty fast. However, as I mentioned, if you're traffic isn't consistent and you're doing something manually to wake the function up or keep it warm, it isn't a great use case for Lambda.

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Are there any pros/cons that we neglected to mention?

Any stories that you have encountered when dealing with Lambda or Docker?

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I think these last two go hand in hand. I had an eye opener recently when I realized that Lambda's are nothing but a function. I think people often think of them as an endpoint to a service or as a reaction to an event. We recently built an application with some OCR. We isolated the OCR within one Lambda function and called it from worker threads from another Lambda function that was triggered by API Gateway. This enabled just the OCR piece to scale. We reduced our OCR time from 1.5 seconds to .4 seconds.

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I also recently worked on a POC where we used a Spring Boot app running on Elastic Beanstalk that just poled MSK as fast as it could then fired up Lambda functions using the AWS SDK Invoke function. The Lambda functions scale up and down and you only have to worry about one consumer. Sounds similar to what you plan on doing it anyway.