Conceptually I think it's great for pipelines or use-cases like this, VMs are generally a terrible level of abstraction for a lot of problems, and the Lambda style promotes better architecture because of this.
The connectivity between Kinesis/SNS and friends is great. I'd agree that Lambda is not currently a good fit for "regular" apps, APIs should be fine now that the proxy stuff is in there, though there's slight latency.
No need to worry about gracefully stopping or restarting daemons, just push new code and the old stuff goes away, it really is a great abstraction that way. Basically replace anything you'd use a Go channel for, with more Lambda or SNS->Lambda if you need retries and backoff, it'll spare you a lot of code.
I find the workflow great as well, the slowest part for me is compiling the Go binaries, the rest is virtually instant. Especially now with all this needlessly complex Docker stuff it's refreshing to use something simple.
Cost is prohibitive for sustained use, so make sure you price things out properly, it sounds very cheap until you look at say a constant 100 requests/s behind API Gateway. It's easily 300-400% what you'd pay on EC2.
Cold-start is really a non-issue in most cases, it seems to take very little to keep a function warmed, so unless you get zero traffic (which would be dirt cheap on a t2.micro anyway) you'll be fine.
Edit: Feedback: Really like it. One feature that would be very nice would be the ability to trigger a ping on demand, e.g., for testing auth set up on a request. Runscope implements a similar feature. Otherwise great so far!
I had limited free plans originally but that went horribly wrong haha, free users only attract other free users, a few days later I had like 4000 free people. Maybe that works for startups, but not "real" companies.
Last I calculated, it's nearly 5x the cost of comparable t2 on-demand EC2 instances. That can be mitigated if you have spiky traffic where you'd need to turn on several EC2 instances for less than an hour but are stuck paying for the full hour, or if you can scale to zero for extended periods of time.
Critical to us: you don't have the ability to serve concurrent requests from a single lambda worker, so if you're waiting for async IO (e.g. downloading from S3) then you're wasting money you wouldn't be wasting with EC2. You end up with one file per lambda worker, whereas we could handle about five files concurrently on a normal VM because of async IO. -- For us lambda was prohibitively expensive at scale. I suspect a fair number of people reporting significant savings vs EC2 had over-provisioned instances.
Hm...
https://hearthsim.info/blog/how-we-process-replays/
TLDR: AWS Lambda is awesome if you have indeterminate-but-high amounts of small CPU-bound tasks you want to be able to do in parallel, as soon as they are needed. Awesome for file processing (eg. image resizing) for example.
But being stuck on Python 2.7 sucks. PLEASE Amazon, announce Python 3 support already.
Taking another look now on some side projects, to get a sense of if all the of the issues have been addressed.
But the big ones were lack of env variables, and the tooling was atrocious.
I really like the concept, and the current serverless (serverless.com) framework has been simplified, runs based on cloud formation, and also allows the project to be run as an express server, and potentially with additional plugins on a competing serverless architecture.
Recently, I've been using stdlib (https://stdlib.com) to do function-services since it's a lot easier to get started with it a bit more intuitive for newcomers to understand.
[1] www.bustle.com and www.romper.com do a combined XX million unique visitors per month.
That said, we use node. I have heard cold starts are worse for Python (I have no data). I have heard they are near unbearable for Java (JVM startup and all that). We try and minimize external calls outside the main handler. Previous to this update we were packing configs with webpack at deploy time. Some people read them from S3 or dynamo. I don't consider that a good solution. I'll be working this week on Shep 3.0 which will use the new ENV var features.
I have talked to other people who do various hacks to force their functions to be warm. I've looked at doing this and haven't found it necessary yet for our use case.
[1] https://github.com/fugue/credstash
[2] https://topics.arlingtonva.us/2016/11/voter-registration-sea...
I'm not using Apex or any of the other frameworks, just plain Go code wrapped by the JS function.
It's really awesome to work with, you just deploy a function and quit worrying about it.
Things like callbacks, message monitoring and stuff like that.
Example:
Monitor SNS messages for auto-scaling and send a message to slack when something fails. https://github.com/KensoDev/sns-lambda-notifier-golang
Wrote a blog post about it too: https://medium.com/@iotsky/how-we-built-the-iotsky-backend-u...
It's used in production for a few months now and we're really happy with it. It provides a negligible-cost replacement to Optimizely for us.
The main issue we've seen is, even at the "top" tier (1536mb) the CPU performance doesn't seem very good, it's difficult to tell as they abstract you away from what is actually going on under the hood.
Main advantages: easy to deploy, no infrastructure worries if your problem fits, event based triggers means you don't have to write any of that code, fits well in the AWS ecosystem.
I've seen people making serverless websites and things like that, but I'm not convinced Lambda is a good fit for such a thing (happy to be proven wrong)
My technical recommendation is as follows: "No".
My only gripe is that API Gateway (APIG) charges $3.5 per million requests and there is no other way to invoke lambda functions over HTTP. Had to scale back my micro-service ambitions because of this.
It seems like APIG has a boat load of features, which is great... but they are mostly unused.