fl-aws VS awslogs

Living in my team's bubble i thought everyone runs or tries to run parallel environments: prod, staging, dev, but also an individual (person) or feature env. Why? Because there's no emulator or documentation that will teach you real behavior. Like others have said, AWS seems out of this world. Just like GCP and Azure i might add. Some things you don't expect and they mesmerize you how smart they are. Some you expect and you can't fathom how come you're the "only" one screaming. Random thought: this is how i ended up logging all I bumped into into "Fl-aws" https://github.com/andreineculau/fl-aws

Back to the point: reality is that many build their AWS environment (prod) manually, maybe they duplicate once (dev) also manually, maybe they use some automation for their "code" (lambda) but that's it. This implies it's practically impossible to run end-to-end tests. You can't do that in prod for obvious reasons and you can't do it in dev either - you have many devs queueing, maybe dev is not in sync with prod etc.

My team ran cloudformation end-to-end. We actually orchestrated and wrapped cloudformation (this is yet another topic for not using terraform etc) so that if smth couldn't be done in CFN, it would still be automated and reproducible. Long story short, in 30 minutes (it was this long because we had to wait for cloudfront etc) we had a new environment, ready to play with. A total sandbox. Every dev had their own and it was easy to deploy from a release artifact or a git branch to this environment. Similarly you could create a separate env for more elaborate changes to the architecture. And test in a live environment.

Finally to your question: how do you test end-to-end?

If we talk about lambdas because that's where the business logic lies in a "serverless" architecture, then the answer is by calling the system which will eventually call your lambda/s along the way. If your lambda ia sitting behind AWS gateway, then fire an http request. Is it triggered when objects land on S3? Then push some object to S3. How do you assert? Just the same - http response, S3 changes etc. Not to mention you can also check cloudwatch for specific log entries (though they are not instant).

With this type of a setup, which sounds complex, but it is not since it is 100% reproducible (also from project to project - I had several), adding this proxy-to-my-dev-machine lambda would mean I can make local changes and then fire unit AND end-to-end tests without any changes pushed to AWS, which is the main time/energy consumer imo.

PS: sorry for the wall of text. Like i said i recently realized that the development realities have huge discrepancies, so i tried to summarize my reality :)

Using the official CLI (aws logs get-log-events) or https://github.com/jorgebastida/awslogs is pretty close to SSH-ing and grepping.

cw is a native executable targeting your OS, and not needed external dependencies such as pip and npm. Compared to awslogs which is famous helpful tool for CloudWatch Logs1, cw is written in golang and faster.

Its a command line tool but some people I know also use awslogs

Not a full solution, but when I was doing this I really got to love the awslogs utility:

https://github.com/jorgebastida/awslogs

It allows you to stream Cloudwatch logs from the command line, so you can grep them, save them to files, etc... (The web based Cloudwatch interface is terrible.)

Another suggestion is to try to modularize the core business logic in your lambda such that you separate the lambda-centric stuff from the rest of it. Obviously, though, if "the rest of it" is hitting other AWS services, you're going to hit the same testing roadblock.

Or you can try mocking, which may or may not provide much value for you. There's a python library for that, (moto), but it's not 100% up to date wrt AWS services/interfaces, last I had checked. Might be worth a try though.

https://github.com/spulec/moto

Cloudwatch Logs is pretty meh visually, but awslogs can give you a pretty good `tail -f`-like experience, and Insights is pretty good. Cloudwatch Metric Filters give you a 'StatsD'-like experience, in that you can log out a certain message or code and then use its appearance as a metric.

Check out https://github.com/jorgebastida/awslogs , you can define a `--start`, and it also has a `--watch`, and can be piped the `grep` or whatever you want. It's a pretty flexible tool.

📖 awslogs - a simple command-line tool for querying groups, streams, and events from Amazon CloudWatch logs.