ryan_sb

I also was on SEDaily a while back on the same topic http://softwareengineeringdaily.com/2016/06/20/serverless-co...

No reason it can't check any hostname, but all my custom SSL certs are on CloudFront.

Not quite, they announced it would exist: "This feature will be available later this year." (from the post).

But when it is available, it'll be a huge step ahead.

There's a warmup time when a function is first executed in a container that can be up to 2 seconds depending on what libraries you include (you pay for this time [1]). After the first execution, your function environment will stay "warm" for 10-15 minutes and it will only take 10-150ms to execute your function on a new event.

The other big downside is every time your function goes "cold" you pay the cost of all the extra (anything not in standard lib, ImageMagick, or the AWS Nodejs SDK) libraries you need.

The upside is that you only pay for the time your code actually runs. I've replaced a cronjob server and saved ~90% on the bill to run my jobs. Mostly they were scheduled backups and other misc integrity checks on AWS and 3rd-party infra, so nothing that intense.

More limits/downsides: http://serverlesscode.com/post/aws-lambda-limitations/

1: the cost for 2 seconds of execution time on a 512-MB execution environment is 0.00001668 USD, so it's not likely to break the bank. If you have a high-traffic function it's likely to stay "warm" pretty much all the time. And if your function is low-traffic, it's likely you fit inside the free tier.

+1 one of the draws for Lambda is that it has easy integration with other AWS tools (Kinesis, DynamoDB, SNS, even CloudFormation) and is really low-cost since you only pay for execution time.

True, but in this particular case, the cost to time going (temporarily) backwards would only be connecting to a potentially-suboptimal disque node, and that would be remedied after the subjective-machine-time caught up with the previous subjective time.

Python makes it easy to do lots of things -- including very inefficient ones. Profiling your existing stuff and trying to optimize in pure Python often gets you pretty far.