안전한 소프트웨어 배포: 프로덕션 환경 배포와 관련된 두려움과 혐오 극복하기

Mark Porter
October 20, 2021 | Updated: November 8, 2021

저는 지금껏 제 직책 덕분에 다양한 유형의 소프트웨어를 배포할 수 있는 특권을 누렸습니다. CD를 발송했고, 웹을 통해 고객 소프트웨어를 배포했으며, 데이터베이스 인스턴스와 제어 평면을 업데이트했습니다. 그리고 실행 중인 대규모 미션 크리티컬 시스템을 실시간으로 업데이트했습니다.

제가 이것을 특권이라고 부르는 이유는 최종 사용자에게 소프트웨어를 제공하는 것이 소프트웨어 엔지니어가 가장 좋아하는 일이기 때문입니다. 그러나 배포가 게임처럼 재미있기만 한 것은 아닙니다. 그리고 배포를 할 때마다 고유한 문제가 발생하지만, 모든 배포 과정에서 한 가지 공통된 것이 있는데, 바로 두려움입니다.

중요한 소프트웨어의 배포를 담당하는 분이라면 제가 무슨 말을 하는지 잘 아실 것입니다. 배포 담당자는 소프트웨어를 개발하고, 준비하고, 테스트합니다. 그리고 마침내 소프트웨어가 출항하는 날이 오면 프로덕션 환경이라는 바다에서 순조롭게 항해할 수 있기를 바라고 또 기도합니다. 대부분의 회사에서 프로덕션 환경은 개발 및 스테이징 환경과 현저히 다르기 때문에 스테이징 환경에서 작동한 코드가 프로덕션 환경에서도 성공적으로 작동할 것인지는 알 길이 없습니다. 그러나 한 가지 분명한 점은 소프트웨어에 문제가 발생할 경우 모두가 이에 대해 알게 된다는 것입니다. 그래서 두려운 것입니다.

이러한 두려움이 개발자에게 미치는 영향을 가장 잘 이해할 수 있는 말이 있습니다. SF 소설 Dune의 저자인 Frank Herbert는 "두려움은 정신을 집어 삼킨다"고 했습니다. 두려움은 실험적이고 도전적인 정신을 약화시킵니다. 위험을 감수할 의지를 꺾고, 배포를 몇 달씩 미루는 등 나쁜 습관을 가져옵니다. 무엇보다 혁신의 속도를 느리게 만듭니다 (많은 기업들이 지불하고 있는 혁신세에 대한 게시물 참조).

프로덕션 환경에 배포하는 것는 분명 두려운 일입니다. 하지만 저는 지난 30년간 동료들과 협력하여 안전하고 자신 있는 배포 환경을 만들 수 있는 몇 가지 방법을 개발했습니다. 다음에 나오는 이 시리즈의 4개 블로그 게시물에서 각각에 대해 차례로 살펴보겠습니다.

· 180 규칙 - 쉽고 빠르게 롤백이 가능한 자동화된 배포 지원

· Z 배포 - 롤백 실패로 인한 다운타임 제한

· Goldilocks Gauge - 배포의 규모와 빈도를 적절하게 조정

. 거울을 통한 조율 - 개발 환경, 스테이징 환경 및 프로덕션 환경 간의 조율

이러한 방법들은 완벽하지 않으며 배포에 버그가 발생하지 않는다는 것을 보장하지 않습니다. 하지만 제 경험상 최고의 전략입니다. 그리고 의미 있는 혁신이 가능하도록 엔지니어링 팀 내에 자신감 있는 문화를 구축하는 데 도움이 됩니다.

시작을 위해 다음 블로그 게시물에서는 프로덕션 환경에서의 다운타임(분)을 줄이는 데 도움이 되는 "180가지 규칙"에 대해 소개하겠습니다. 그동안 @MarkLovesTech를 통해 안전한 배포를 위한 나만의 팁과 기법을 자유롭게 공유해보세요.

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Safe Software Deployments: The 180 Rule

In my last post , I talked about the anxiety developers feel when they deploy software, and the negative impact that fear has on innovation. Today, I’m offering the first of four methods I’ve used to help teams overcome that fear: The 180 Rule. Developers need to be able to get software into production, and if it doesn’t work, back it out of production as quickly as possible and return the system to its prior working state. If they have confidence that they can detect problems and fix them, they can feel more confident about deploying. All deployments have the same overall stages: Deployment: You roll the software from staging to production, either in pieces -- by directing more and more transactions to it -- or by flipping a switch. This involves getting binaries or configuration files reliably to production and having the system start using them. Monitoring: How does the system behave under live load? Do we have signals that the software is behaving correctly and performantly? It’s essential that this monitoring focuses more on the existing functionality than just the “Happy Path” of the new functionality. In other words, did we damage the system through the rollout? Rollback: If there is any hint that the system is not working correctly, the change needs to be quickly rolled back from production. In a sense, a rollback is a kind of deployment, because you’re making another change to the live system: returning it to a prior state. The “180” in the name of the rule has a double meaning. Of course, we’re referring here to the “180 degree” about-face of a rollback. But it’s also a reference to an achievable goal of any deployment. I believe that any environment should be able to deploy software to production and roll it back if it doesn’t work in three minutes, or 180 seconds. This gives 60 seconds to roll binaries to the fleet and point your customers to them, 60 seconds to see if the transaction loads or your canaries see problems, and then 60 seconds to roll back the binaries or configurations if needed. Of course, in your industry or for your product, you might need this to be shorter. But the bottom line is that a failed software deployment should not live in production for more than three minutes. Developers follow these three stages all the time, and they often do it manually. I know what you’re thinking: “How can any human being deploy, monitor, and roll back software that fast?” And that is the hidden beauty of the 180 Rule. The only way to meet this requirement is by automating the process. Instead of making the decisions, we must teach the computers how to gather the information and make the decisions themselves. Sadly, this is a fundamental change for many companies. But it’s a necessary change. Because the alternative is hoping things will work while fearing that they will not. And that makes developers loath to deploy software. Sure, there are a lot of tools out there that help with deployments. But this is not an off-the-shelf, set-it-and-forget-it scenario. You, as the developer, must provide those tools with the right metrics to monitor and the right scripts to both deploy the software and possibly roll it back. The 180 Rule does not specify which tools to use. Instead it forces developers to create rigorous scripts and metrics, and ensure they can reliably detect and fix problems quickly. There’s a gotcha that many of you are thinking of: The 180 Rule is not applicable if the deployment is not reversible. For example, deploying a refactored relational schema can be a big problem, because a new schema might introduce information loss that prevents a roll-back. Or the deployment might delete some old config files that aren’t used by the new software. I’ll talk more about how to avoid wicked problems like these in my subsequent posts. But for now, I’m interested to hear what you think of The 180 Rule, and whether you’re using any similar heuristics in your approach to safe deployment.

October 20, 2021
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MongoDB’s 2024 Year in Review

It’s hard to believe that another year is almost over! 2024 was a transformative year for MongoDB, and it was marked by both innovation and releases that further our commitment to empowering customers, developers, and partners worldwide. So without further ado, let’s dive into MongoDB’s 2024 highlights. We’ll also share our executive team’s predictions of what 2025 might have in store. A look back at 2024 MongoDB 8.0: The most performant version of MongoDB ever In October we released MongoDB 8.0 , the fastest, most resilient, secure, and reliable version of MongoDB yet. Architectural optimizations in MongoDB 8.0 have significantly improved the database’s performance, with 36% faster reads and 59% higher throughput for updates. Our new architecture also makes horizontal scaling cheaper and faster. Finally, working with encrypted data is easier than ever, thanks to the addition of range queries in Queryable Encryption (which allows customers to encrypt, store, and perform queries directly on data). Whether you’re a startup building your first app, or you’re a global enterprise managing mission-critical workloads, MongoDB 8.0 offers unmatched power and flexibility, solidifying MongoDB’s place as the world’s most popular document database. Learn more about what makes 8.0 the best version of MongoDB ever on the MongoDB 8.0 page . Delivering customer value with the MongoDB AI Applications Program AI applications have become a cornerstone of modern software, and MongoDB is committed to equipping customers with the technology, tools, and support they need to succeed on their AI journey. That’s why we launched the MongoDB AI Applications Program (MAAP) in 2024, a comprehensive program designed to accelerate the development of AI applications. By offering customers resources like access to AI specialists, an ecosystem of leading AI and tech companies, and AI architectural best practices supported by integrated services, MAAP helps solve customers’ most pressing business challenges, unlocks competitive advantages, and accelerates time to value for AI investments. Overall, MAAP’s aim is to set customers on the path to AI success. Visit the MongoDB AI Applications Program page or watch our session from AWS re:Invent to learn more! Advancing AI with MongoDB Atlas Vector Search In 2024, MongoDB further cemented its role in the AI space with enhancements to MongoDB Atlas Vector Search . Recognized in 2024 (for the second consecutive year!) as one of the most loved vector databases , MongoDB continues to provide a scalable, unified, and secure platform for building cutting-edge AI use cases. Recent advancements like vector quantization in Atlas Vector Search help deliver even more value to our customers, enabling them to scale applications to billions of vectors at a lower cost. Head over to our Atlas Vector Search quick start guide to get started with Atlas Vector Search today, or visit our AI resources hub to learn more about how MongoDB can power AI applications. Search Nodes: Performance at scale Search functionality is indispensable in modern applications, and with Atlas Search Nodes, organizations can now optimize their search workloads like never before. By providing dedicated infrastructure for Atlas Search and Vector Search workloads, Search Nodes ensure high performance (e.g., a 40–60% decrease in query times), scalability, and reliability, even for the most demanding use cases. As of this year , Search Nodes are generally available across AWS, Google Cloud, and Microsoft Azure. This milestone underscores MongoDB’s commitment to delivering powerful solutions that scale alongside our customers’ needs. To learn more about Search Nodes, check out our documentation or watch our tutorial . Looking ahead: MongoDB’s 2025 predictions After the excitement of the past few years, 2025 will be defined by ensuring that technology investments deliver tangible value. Organizations remain excited about the potential AI and emerging technologies hold to solve real business challenges, but are increasingly focused on maintaining a return on investment. “Enterprises need to innovate faster than ever, but speed is no longer the only measure of success. Increasingly, organizations are laser-focused on ensuring that their technology investments directly address critical business challenges and provide clear ROI and competitive advantage—whether it’s optimizing supply chains, delivering hyper-personalized customer experiences, or scaling operations efficiently,” said Sahir Azam, Chief Product Officer at MongoDB. “In 2025, I expect to see organizations make significant strides in driving this innovation and efficiency by applying AI to more production use cases and by maturing the way they leverage their data to build compelling and differentiated customer experiences.” Indeed, we expect to see organizations make more strategic investments in emerging technologies like gen AI—innovating with a sharp focus on solving business challenges. “In 2025, we can expect the focus to shift from ‘what AI can do’ to ‘what AI should do,’ moving beyond the hype to a clearer understanding of where AI can provide real value and where human judgment is still irreplaceable,” said Tara Hernandez, VP of Developer Productivity at MongoDB. “As we advance, I think we’ll see organizations begin to adopt more selective, careful applications of AI, particularly in areas where stakes are high, such as healthcare, finance, and public safety. A refined approach to AI development will be essential—not only for producing quality results but also to build trust, ensuring these tools genuinely support human goals rather than undermining them.” With more capable, accessible application development tools and customer-focused programs like MAAP at developers’ fingertips, 2025 is an opportunity to make a data-driven impact faster than ever before. "Right now, organizations have an opportunity to leverage their data to reimagine how they do business, to more effectively adapt to a changing world, and to revolutionize our quality of life,” said Andrew Davidson, SVP of Products at MongoDB. “By harnessing our latest technologies, developers can build a foundation for a transformative future." Head over to our updates page to learn more about the new releases and updates from MongoDB in 2024. Keep an eye on our events page to learn what's to come from MongoDB in 2025!

December 19, 2024