AWS re:Invent 2021

[longfin]

[longfin]

데브옵스 엔지니어 채용 공고가 아직이긴 한데, 그 전에 내용 먼저 봐주시면 좋을 것 같습니다. 🙇 @planetarium/libplanet @planetarium/nine-chronicles-engineers @planetarium/9c-backend

[Junyong-Suh]

@longfin 짧은 생각이지만 내가 데브옵스라면 어떤 커리어를 갖길 원하고, 그 길 위에서 플라네타리움에서의 경험이 어떻게 도움이 될까? 라는 질문에 대한 저희의 답이 있으면 좋을 것 같습니다. "얼마나 큰 트래픽과 스케일을 감당해야 하는가" 가 일반적인 매력 포인트인데, 우리는 데브옵스가 다른 문제를 풀어야 한다면 그 문제가 무엇이고 그 문제를 데브옵스가 와서 푼다면 저희한테 얼마나 큰 기여가 될지 감을 잡을 수 있으면 좋지 않을까 합니다. 제가 댓글을 달면서도 어떻게 풀어야 할지 딱 감은 안 오네요. ^^;

[longfin]

@longfin 짧은 생각이지만 내가 데브옵스라면 어떤 커리어를 갖길 원하고, 그 길 위에서 플라네타리움에서의 경험이 어떻게 도움이 될까? 라는 질문에 대한 저희의 답이 있으면 좋을 것 같습니다. "얼마나 큰 트래픽과 스케일을 감당해야 하는가" 가 일반적인 매력 포인트인데, 우리는 데브옵스가 다른 문제를 풀어야 한다면 그 문제가 무엇이고 그 문제를 데브옵스가 와서 푼다면 저희한테 얼마나 큰 기여가 될지 감을 잡을 수 있으면 좋지 않을까 합니다. 제가 댓글을 달면서도 어떻게 풀어야 할지 딱 감은 안 오네요. ^^;

조금 생각해봤는데, 이 글에서는 저희가 탈중앙 게임을 만든다고 함에도 왜 클라우드 IaaS(i.e. AWS)를 쓰고 있는지, 그 동기나 생각하고 있는 점에 대해서만 먼저 설명하고 저희가 다루고 있는 스케일에 대해서는 다른 글로 푸는 게 좋을 것 같아요.

[pull-request-quantifier-deprecated[bot]]

This PR has 68 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

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Quantification details

``` Label : Small Size : +68 -0 Percentile : 27.2% Total files changed: 1 Change summary by file extension: .md : +68 -0 ``` > Change counts above are quantified counts, based on the [PullRequestQuantifier customizations](https://github.com/microsoft/PullRequestQuantifier/blob/main/docs/prquantifier-yaml.md).

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a balance between between PR complexity and PR review overhead. PRs within the optimal size (typical small, or medium sized PRs) mean: - Fast and predictable releases to production: - Optimal size changes are more likely to be reviewed faster with fewer iterations. - Similarity in low PR complexity drives similar review times. - Review quality is likely higher as complexity is lower: - Bugs are more likely to be detected. - Code inconsistencies are more likely to be detetcted. - Knowledge sharing is improved within the participants: - Small portions can be assimilated better. - Better engineering practices are exercised: - Solving big problems by dividing them in well contained, smaller problems. - Exercising separation of concerns within the code changes. #### What can I do to optimize my changes - Use the PullRequestQuantifier to quantify your PR accurately - Create a context profile for your repo using the [context generator](https://github.com/microsoft/PullRequestQuantifier/releases) - Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the `Excluded` section from your `prquantifier.yaml` context profile. - Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your `prquantifier.yaml` context profile. - Only use the labels that matter to you, [see context specification](./docs/prquantifier-yaml.md) to customize your `prquantifier.yaml` context profile. - Change your engineering behaviors - For PRs that fall outside of the desired spectrum, review the details and check if: - Your PR could be split in smaller, self-contained PRs instead - Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR). #### How to interpret the change counts in git diff output - One line was added: `+1 -0` - One line was deleted: `+0 -1` - One line was modified: `+1 -1` (git diff doesn't know about modified, it will interpret that line like one addition plus one deletion) - Change percentiles: Change characteristics (addition, deletion, modification) of this PR in relation to all other PRs within the repository.

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