Our main path business path gets about 60,000 reqs min. For that, sure AWS Lambda would never compete. Not only would it cost more but you'd probably hit the concurrency limit in AWS Lambda.
But we also have an admin UI that gets about 2500 visits a day. We're running that for about $4 a month - with virtually no operational burden whatsoever, and with a reassurance of resilience.
We worked out that the inflection point of value is at about 3 million requests a month. (that's an fag packet estimate, arbitrarily expensive 'request', your mileage may vary).
Its no silver bullet, but for some applications, particularly personal projects, low traffic and startup scenarios it can be ideal.
A managed app runtime can be great though: for those who tried Google AppEngine back in the day, it was amazing to work with.
I'm curious about this statement because I'm currently working on a project where the intent is to port a legacy app to AWS Lambda. The legacy app is currently distributed across 96 VMs and handles ~ 50K reqs/min during normal times but can run into ~ 3M reqs/min during high demand.
Are you saying AWS Lambda can not scale to handle this type of demand and if so can you point me to some resources/references that explain this?
For the record, I'm not the one that came up with the architecture.
But also there is a per account per region concurrency limit of 1000 parallel executions. That's shared across all lambdas. If you hit it, requests will not be for-filed, increasing this limit is entirely at Amazons discretion, and wont they necessarily do it. I stand corrected, see comment.
https://docs.aws.amazon.com/lambda/latest/dg/limits.html
In your case 3m reqs/min will be fine if each request can be completed in no more than 20 milliseconds, and then you'll be on the knife edge.
If you wanted to reap the benefits of Lambda on the development side, loose the limits and keep server costs low(er) you could deploy OpenFaaS or similar in ECS. However you then loose the operational benefits of a managed solution.
(Source: I work on Lambda at AWS)
1. start with docker (or dokku), on a single server, it's easy enough to get going, automate CI/CD. Make sure your backups are working and relatively frequent.
2. Break your lower environments on to a separate server.
3. Break out your database, and set up redundancy at that layer. Leverage DBaaS if you can.
4. Grow to multiple app/api instances for redundancy, and setup rolling deployments.
5. Scale Vertically (bigger servers/instances)
6. Migrate to Kubernetes and expand your automation and tooling.
7. Break apart your application into smaller pieces to scale individually. Possibly leveraging platform tools like Lambda/Functions.
8. Work towards redundant datacenter and application data sharding to deliver a closer experience.
By the time you get to 5-6, you should be making money or have a good investor strategy in place for capital. There's very little need to go all out when at concept or earlier release stages.
6-8 may take place in a different order, depending on your needs.. but again, you should have money or have raised capital by this point, or you have a relatively good problem to have otherwise.
IIRC Stack Overflow grew vertically pretty big on a single server, then two (db/application split).
Essentially, a good way to set something up that requires minimal maintenance.
[0] https://gist.github.com/shaunpud/35f77b542eaec7c7024bbb15c2e... [1] https://lowendbox.com