libaws VS aws-nuke

i print the error along with file and line number every time i return it. clunky, but it works.

in fact i print file and line with every log message.

https://github.com/nathants/libaws/blob/87fb45b4cae20abd1bb1...

cloud is so good now it’s hard to justify not doing something bespoke. ec2 spot is insanely cheaper than turnkey cicd, and better in almost every way.

i’m delighted to pay 30% over infra cost for convenience, but not 500%. and it better actually be convenient, not just have a good landing page and sales team.

this month i learned localzones have even better spot prices. losangeles-1 is half the spot price of us-west-2.

for a runner, do something like this, but react to an http call instead of a s3 put[1].

for a web ui do something like this[2].

s3, lambda, and ec2 spot are a perfect fit for cicd and a lot more.

1. https://github.com/nathants/libaws/tree/91b1c27fc947e067ed46...

2. https://github.com/nathants/aws-exec/tree/e68769126b5aae0e35...

like linux, cloud is a lot to learn, but worth it.

like linux, cloud is best kept simple, or it can become brittle and confusing.

like linux, cloud has a lot of cool things like zfs, that should be appreciated but rarely used.

like linux, using go makes your life a lot easier. the aws go sdk is the documentation.

like linux, you have to learn a lot and then find the core utility you actually care about. for me it is:

https://github.com/nathants/libaws

the good new is, for the 95% of projects that can tolerate it, aws the good parts are actually both simple and easy[1].

it’s hard to find things you can’t build on s3, dynamo, lambda, and ec2.

if either compliance or a 5% project demand it, complicated solutions should be explored.

1. https://github.com/nathants/libaws

i also wanted a good cli for aws, and built one:

https://github.com/nathants/libaws

companies like fly are fantastic.

they provide a good service, and they put market pressure on aws.

cool transition and fun writeup!

for low, intermittent traffic sites, go on lambda might be a better comparison:

https://github.com/nathants/libaws/tree/master/examples/simp...

lambda + s3. add ec2 spot if you need it.

just make sure you understand how billing works. mostly it’s just egress bandwidth is expensive.

do something like this:

https://github.com/nathants/aws-gocljs

or with less opinions:

https://github.com/nathants/libaws/tree/master/examples/simp...

welcome to cloud, glhf!

aws ux for retaining both hair and sanity.

https://github.com/nathants/libaws

build and scale systems with artificial load on aws! scaling the load testing will be just as interesting as scaling the system under test.

start with low bottlenecks, ie a cluster of c6i.large ec2 spot. how fast can you do this? have fast can you scale that? ec2 and s3 is all you need to build anything.

use ec2 spot, avoid network egress, avoid cross region/zone traffic, create and destroy ec2 instances as needed instead of letting them sit idle. you could grow system scaling intution for the price of your streaming subscriptions.

start with something like this:

https://github.com/nathants/libaws/tree/master/examples/comp...

maybe mess around with public datasets on aws, just make sure to be in the correct region to avoid data egress.

welcome systems friend. one accurate measurement is worth a thousand expert opinions. scaling is fun!

aws has too many knobs, presumably to satisfy the union of the needs of all the enterprise customers. that said, lambda+s3+dynamodb+ec2 are pretty good once you tape over all the knobs that aren't needed. i work with them like this[1].

these days i build on aws and r2. aws for the nuts and bolts, r2 for high bandwidth egress. it's a perfect match.

1. https://github.com/nathants/libaws

To give this a slightly different spin:

--> "The best optimization is simply not spinning things up."

At least for local development and testing, as made possible by LocalStack (https://localstack.cloud), among other local testing solutions and emulators.

We've seen so many teams fall into the trap of "someone forgot to shut down dev resource X for a week and now we've racked up a $$$ bill on AWS".

What is everyone's strategy to avoid this kind of situation? Tools like `aws-nuke` (https://github.com/rebuy-de/aws-nuke) are awesome (!) to clean up unused resources, but frankly they should not be necessary in the first place.

We use nuke aws at work to remove any leftovers: https://github.com/rebuy-de/aws-nuke

You can use this tool on github to nuke all resources.

There's this. I haven't used it myself, but it looks to be pretty effective: https://github.com/rebuy-de/aws-nuke

At this scale, operations can take a lot of time, because there are multiple operational tasks that we need to do when AWS accounts are leaving the AWS Organization or Teams are nuking the AWS account, StackSets Instances get drifted, because not all required resources for compliance can be secured ( SCP Limitations ), existing AWS accounts are joining the AWS Organization and all mandatory StackSets needs to be deployed, and manual steps should be reduced to a minimum. Furthermore, there is no feature from the Service itself to gain an overview of the status of drifted Instances and the general health of your StackSet health and compliance.

Since you're using CDK already, have a way to configure the deployment of the whole thing to a per-developer test account; that's still gonna cost you, but you can bundle everything in an organization / organizational unit for billing purposes, and you can also schedule https://github.com/rebuy-de/aws-nuke to run nightly to clean these accounts from longer-running resources.

And by extension, https://github.com/rebuy-de/aws-nuke as well.

I can also recommend aws-nuke which is an easy to way to destroy in your account.

nothing blew up accidentally this week, but our team at kubefirst is falling more and more in love with aws-nuke. it's an open source command line tool that lets you basically reset an aws account back to an empty state. if you have an environment where you regularly practice your platform provisioning, you probably know that failed destroys while iterating on orchestration can leave junk behind pretty easily. aws-nuke has been so nice to be able to blow away everything in an aws account - and then we just run terraform in the account to get all our core infra back afterward. nice allowlist filters and dryrun detail work too. check them out.