What I mean by "programming the machine" is doing technical tasks that relates to making the cloud work in the way you want.
I've worked on projects in which tha vast majority of the work seems to be endless "programming the machine".
This repeats constantly because the underlying problem is a broken social environment where people aren’t aligned with what their users really need and that’s rewarded.
Can you be specific because that does not sound right to me.
I know both pretty well and seems to me there is vastly more things that need to be tuned and managed and configured in cloud.
I think it would be interesting to do a systematic study of the time required for each.
What about running code? If I deploy, say, Python Lambdas behind an API Gateway or CloudFront, they’ll run for years without any need to touch them. I don’t need to patch servers, schedule downtime, provision new servers for high load or turn them off when load is low, care that the EL7 generation servers need to be upgraded to EL8, nobody is thinking about load balancer or HTTPS certificate rotation, etc. What you’re paying for, and giving up customization for, is having someone else handle all of that.
So said Gary Bernhardt of WAT fame in 2015 https://x.com/garybernhardt/status/600783770925420546
> Consulting service: you bring your big data problems to me, I say "your data set fits in RAM", you pay me $10,000 for saving you $500,000.
Which, in turn, have inspired https://yourdatafitsinram.net/
Writing and maintaining code that sets up and configures S3, SQS, SNS, DynamoDB, and Lambda is a non-zero cost, but if it then reduces the amount of code I have to write and maintain to "write the application," that's often a good thing. These services are typically solving the hard and/or tedious parts of the application, so it's actually quite valuable to just focus on developing the core differentiating points of the application instead of solving / maintaining highly available object storage or message queues.
Indeed, I had to learn it ! Just as I had to learn how to code in Python (which makes me far more effective now), just as I had to learn LVM2 or iproute2 or C or whatever.
Once the learning curve is processed, AWS allows you to increase your productivity. Of course, and this is very important, you shall still use the right tool for the right job !
A lot of web apps are just boring CRUD APIs. The business logic behind these is nothing special. The differentiating factor for a lot of them is how they scale, or how they integrate with other applications, or their performance, or how fast they are to iterate on, etc. The “machine” offers a lot of possibilities these days that can be taken advantage of, so customizing “the machine” to get what you need out of it is a big focus for many devs.
Our approach to lambdas is to delegate all the real work to a "library" and just write a very thin adapter around it dealing with the Lambda details (event format etc.). Hopefully this can take care of as much of the wrapper as possible?
I take a different perspective.
When using a cloud, i need to design my application to work within my selected clouds constraints.
A lot of the extra work then comes down to if using a cloud, not just a single VPS on a cloud provider, you are dealing with distributed computing and have to deal with all the issues of distributed computing. Consensus, error handling, etc.
I agree though, more often than not it's a lot of extra work but mostly due to dealing with distributed architecture/designing for being cost effective.
On personal projects I find designing to be cost effective has me jumping through a lot of hoops and doing novel things. It means I can run multi-region apps with performance better than most webapps for cents/dollars. The equivalent apps I work on in my day job can be costing tens to hundreds of thousands of dollars as they don't jump through the hoops I do. "It's not worth it", "let's look at it later", "we'll just do this, it's good enough for now". As it's someone else's money i just think "meh" and move on as isn't my fight when the majority of people don't want to do it.