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aws
aws-sam-cli
Python2017–2021
aws / aws-sam-cli

aws-sam-cli

CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM

13Distinct people
15Mentions
0Explicit recommenders
6.7KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 6:01:08 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year15 dated mentions

Observed mentions: 2017-08-11 17:50:30 UTC to 2021-08-04 15:45:53 UTC.

024682017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2021

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC110
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC808
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC202
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC211
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC202

What Hacker News says

2 sources
I can't really speak for large companies, but I believe my answers apply, no matter what's the company size. > How do you tie in to version control? You're probably talking about the infrastructure definition? Infrastructure-as-Code (e.g. AWS CloudFormation) works quite well and can easily be put under version control. > How do you QA this? (Can it be QA'd locally?) For AWS there are projects like the AWS SAM CLI (https://github.com/awslabs/aws-sam-cli) which try to offer the ability to run your serverless application locally, but I believe such approaches are fundamentelly flawed once your application reaches a certain complexity, as I believe such projects will never be able to re-implement all features and services made available by the Cloud provider. What works well for us is to simply have QA environments spun up in addition to the
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productive ones. Once you got the infrastructure codified properly that's quite easy. The biggest downside is that it, depending on your architecture, might take some time to provision, so it's not as instant as if you'd run it locally. And you need internet access of course. > Would you have unit tests for serverless code? E2E tests? Yes and yes. Actually I see no reason why you'd want to handle test coverage differently from traditional applications. > How would you catch/diagnose a more junior engineer making an infinite loop of events? Would this potentially bring down production or eat the budget? Running code during development should never be able to affect production. For AWS the way to go is to use separate AWS accounts for production and testing/QA. You could even go so far to give each engineer his own account. Regarding catching and diagnosing infinite loops, it all comes down to monitoring: Monitor how the cost evolves and other metrics of interest (e.g. the number of invocations of your serverless functions) and have automatic notifications once certain thresholds are crossed. Additionally limiting the maximum concurrency of serverless functions for non-production accounts might help to avoid things getting out of control too fast.
In Traits of Serverless Architecture

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