В этом видео мы погружаемся в мир микросервисной архитектуры и сравниваем её с монолитом, используя примеры из культовой игры Factorio.
*https://www.youtube.com/watch?v=vPzBiQc44i4
**https://300.ya.ru/v_FQp7f02D
таймкоды
00:00:03 Введение в микросервисы
- Микросервисы — это архитектурный стиль, при котором приложение разбивается на маленькие независимые модули.
- Каждый сервис выполняет свою задачу и взаимодействует с другими через понятные точки соединения.
00:00:23 Пример из Factorio
- Вместо одного огромного завода строятся небольшие специализированные комплексы.
- Каждый комплекс работает автономно, что позволяет гибко управлять системой.
- Пример: если одна плавильня остановилась из-за нехватки угля, другие заводы продолжают работу.
00:01:36 Преимущества микросервисов
- Гибкость, устойчивость и лёгкость масштабирования.
- Возможность добавления новых сервисов без влияния на существующие.
- Разные команды могут работать над своими сервисами независимо.
00:03:25 Проблемы монолитной архитектуры
- Сложность масштабирования: требуется перенастройка всей системы.
- Сложность обновлений: любое изменение требует перенастройки всей системы.
- Зависимость компонентов: сбой одного элемента может парализовать всю систему.
00:04:51 Преимущества монолитов
- Подходят для небольших баз или приложений с предсказуемым объёмом работ.
- Требуют меньше ресурсов для настройки.
- Идеальны для начинающих или ограниченных по времени проектов.
00:06:34 Взаимодействие микросервисов
- Основные способы связи между модулями: конвейеры, логистические дроны, поезда.
- Конвейеры: простой, но медленный способ связи.
- Логистические дроны: гибкий, но требует больше ресурсов.
- Поезда: быстрый и точный способ связи, подходит для высоконагруженных систем.
00:09:20 Недостатки микросервисов
- Сложность настройки и управления.
- Высокая зависимость от сетевой инфраструктуры.
- Сложности мониторинга и отладки.
- Потребление ресурсов: каждый сервис требует больше ресурсов для запуска и поддержки.
- Высокая квалификация команд.
00:11:46 Когда использовать микросервисы
- Микросервисы — мощный инструмент, но их нужно использовать с умом.
- Не каждая задача требует сложной распределённой архитектуры.
- Важно задать себе вопросы, чтобы понять, подходят ли микросервисы вашему проекту.
00:12:22 Микросервисы для сложных проектов
- Микросервисы подходят для проектов с множеством функций, которые можно разделить на независимые модули.
- Пример из «Фактории»: разделение производства на отдельные блоки для масштабирования.
- Разделение работы между командами помогает избежать конфликтов и ускорить разработку.
00:13:02 Устойчивость микросервисов
- Сбой одного компонента в микросервисах не влияет на остальные.
- Пример: сбой одной шахты в «Фактории» не остановит весь процесс при грамотной логистике.
00:13:32 Микросервисы и рост проекта
- Микросервисы проще обновлять и масштабировать, что делает их отличным выбором для стартапов и быстро развивающихся приложений.
- Для небольших проектов монолит может быть более рациональным выбором: проще в настройке, требует меньше ресурсов и меньше подвержен сетевым сбоям.
00:14:07 Заключение
- Микросервисы помогают строить гибкие масштабируемые системы, но требуют вложений в инфраструктуру, мониторинг и управление.
- Выбор между монолитом и микросервисами зависит от задач и ресурсов проекта.
- Для долгосрочного развития и готовности к вложениям микросервисы станут отличным решением.
- Для начинающих или небольших проектов монолит может быть более удобным и экономичным.
In this video
Intro: What are microservices?
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Hello, factory friends! York is with you. Today we will discuss microservices using
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our favorite Factorio as an example. What are they, why are they needed,
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why are they better than a monolith, and how do microservices interact with each other? Let’s look at all this
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using examples from the game. Make yourself comfortable, pour some coffee, brew some noodles and let’s go!
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So, what are microservices?
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Microservices is an architectural style in which an application is broken down into small,
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independent modules or services. Each service performs its own task.
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Let’s see how it works in Factorio!
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Imagine that you are building a base, but instead of one huge plant
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, you are making small specialized complexes, also called city blocks:
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one produces iron plates, another produces copper wires, and the third assembles electronic
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circuits. Together they form an integral system, but each works autonomously.
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Now imagine the situation: if one smelter stops due to a shortage of coal,
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other plants continue to operate. You only need to fix the problem with coal,
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and the rest of the base works as if nothing had happened. This approach provides flexibility and ease of management.
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🛠 Key point: Each plant (or microservice) strictly performs its own task
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and interacts with others through clear connection points, without interfering with someone else’s work.
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How are microservices useful?
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Have you ever wondered why in Factorio it is much more convenient to build several small factories
Why are microservices convenient?
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than one giant one? The answer is simple: it gives flexibility, stability and ease of scaling.
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Imagine that your iron plate plant is overloaded and you urgently need to increase its
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capacity. Instead of redoing the entire base, you simply add a few more
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smelters. Thus, only the required part of the system is scaled, without affecting others.
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In Factorio, you can build completely different factories: one for the production of copper wires,
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another for circuits, a third for assembling rockets. In programming, microservices provide the same
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freedom. Different teams can work on their services independently. For example,
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one service can be written in Python and another in Go, and this does not create problems.
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Even if one plant, say, one that makes wires, shuts down due to a copper shortage, the rest—those
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that produce iron plates, gears, or other things—will continue to operate. This means
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that the failure of one microservice does not paralyze the entire system.
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Similar to Factorio, where you can update part of the system by replacing slow pipelines with fast ones,
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in programming you can update only one microservice,
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leaving the rest unchanged. This reduces update time and
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reduces risks. For example, if in a game you want to create a new plastic factory,
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you simply add it. In microservices, this is done in a similar way: the new service
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is integrated with the others through standard interfaces, without breaking the already working system.
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These features make microservices an ideal choice for large systems
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where flexibility, reliability, and ease of scaling are important. This is why this
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architecture is so popular in modern programming.
Problems of a monolith
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What’s wrong with a monolith?
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Let’s look at why a monolithic structure can be inconvenient in some cases.
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The monolith is one huge plant where everything is connected to each other. If something
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breaks or there are not enough resources, the entire process suffers. Remember
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when you spent a long time building a large plant with many crafting chains and forgot to install
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the manipulator or turned the conveyor in the wrong direction. It is much more difficult to track this in a large system.
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Monolithic architecture, like Factorio, where the entire plant operates as a single unit,
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often leads to serious problems. For example, the difficulty of scaling. Imagine that
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you have one long conveyor that connects the entire base. At some point you realize
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that this is not enough for production. To increase the output of gears,
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it is necessary to reconfigure and expand the entire process, affecting many nodes. Sometimes
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this requires a complete rework of the entire database, which is inconvenient and takes a huge amount of time.
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Another problem is the complexity of updates. Let’s say you only want to improve wafer production.
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This is difficult in a monolith, because any change requires rebuilding the entire
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systems. It’s like trying to update one part on a huge line — everything stops
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while you make changes. In addition, any tests and checks must be carried out
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on the entire system, even if the change affects only one part of it.
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Another serious difficulty is the dependence of the components. If one element breaks down,
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for example a coal conveyor, the entire process will stop. This is reminiscent of a situation
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where, due to one error in the code, the application completely stops working. Each part
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of the plant depends on the others, and this makes the system less stable. This is especially acute
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in large-scale projects, where one failure can paralyze the entire work.
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However, monoliths also have advantages. They are better suited for small databases or applications
When to use a monolith?
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where the amount of work is predictable and changes are minimal. Monolithic architecture also
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requires fewer resources to set up, making it an ideal choice for beginners
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or time-constrained projects. For example, for databases where the volumes are small and
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constant modification is not required, a monolith may be the most rational choice.
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This approach allows developers to focus on
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system performance and stability rather than configuring complex interactions between components.
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As an example, consider the new planets in Factorio. They are required to have extremely
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minimal functionality: production of cans, basic factories and transportation
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of resources through conveyors. In such conditions, creating microservices or complex city blocks
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becomes redundant and impractical. It is much more profitable to use a monolith
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that can simultaneously produce banks, additional resources and
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send it all into space. This approach provides simplicity and time savings,
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especially when scaling or major changes to a given base are not planned.
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How do microservices communicate with each other?
How do microservices communicate?
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In Factorio, as in microservices, modules must communicate with each other
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in order for the entire framework to work coherently and efficiently. The methods of such interaction are varied,
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and each of them is suitable for certain tasks.
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The main methods of communication between modules:
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Conveyors (analogous to HTTP/REST API): Imagine that each factory puts its
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products on a conveyor, and other factories take from it what they need. For example, a smelter lays down
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iron plates, and an assembly plant takes them to produce gears. It’s simple:
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each module has a clear area of responsibility, and communication is carried out through a conveyor.
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📮 In real development, this is a REST API: one service provides data through a certain interface,
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and another uses this data. This approach is easy to implement, but can be slow.
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If the conveyor is too long or overloaded, the transfer speed drops. In programming,
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this is analogous to long chains of requests that slow down the entire system.
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Logistics Drones (similar to Message Queue): Logistics drones work differently. They
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pick up resources from one warehouse and deliver them to another, for example, moving wafers from
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a central warehouse to a wire manufacturing plant. This is a more complex and flexible
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delivery method, but it requires settings. 📦 In real life, these are message brokers such
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as RabbitMQ or Kafka. One service sends a message, and another receives and processes it.
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This is an asynchronous communication method that allows the system to operate even in the event of delays or
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temporary failures. This flexibility makes drones an excellent choice for distributed missions.
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Trains (similar to gRPC): Trains are ideal
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for transporting large volumes of resources over long distances. For example, iron
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ore is delivered from a remote mine to a central warehouse. Trains are fast, accurate and can
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serve multiple destinations at once. gRPC works similarly in programming. It is
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a faster and more efficient way of communicating between modules compared to REST. It is
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especially good for high-load systems where minimal latency is important. In Factorio, it’s
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like a well-thought-out railway network that helps the base operate as efficiently as possible.
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Each of these communication methods has its own strengths and weaknesses. Conveyors are the easiest to set up,
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but are limited by speed. Drones are flexible, but require more resources.
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And trains are difficult to operate, but provide maximum productivity. Choice
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The method depends on the goals of your base, whether in Factorio or in a real microservices system.
Disadvantages of microservices
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What are the disadvantages of microservices?
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Microservices are not a magic wand that will solve all your problems. They have
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their drawbacks that are worth considering before choosing this architecture.
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Let’s look at the main disadvantages so that you can assess their impact on your projects.
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The first and most obvious drawback is the complexity of setup and management. Imagine
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that in Factorio you have hundreds of small factories, each with its own task. Setting up
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their interaction is not an easy task, especially if one of the modules suddenly stops working. In
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real-world development, this means that you will need to configure connections between microservices,
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ensure that interfaces work correctly, and create mechanisms to track and resolve
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errors. And in Factorio, you must admit, when you don’t see why resources stopped flowing
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to the station, it turns into a real puzzle that requires time and patience.
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The second disadvantage is the high dependence on network infrastructure. Microservices often
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communicate with each other over a network, be it a REST API, gRPC, or message queues. Any delay
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or failure in the network can lead to system performance degradation. Imagine
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that in Factorio, bugs have destroyed the railway section — resources stop flowing
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and production lines stop. This is similar to the real world of microservices,
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where unstable connections can cause a chain of failures that affects the entire system.
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The third drawback is the difficulty of monitoring and debugging. In monolithic applications, you can
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trace a chain of calls within a single system. In microservices, each module operates
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independently, and monitoring them requires a complex system that tracks all
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interactions. Imagine that you needed to view a list of all completed
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actions in one of the city blocks, who performed what at what time and where this resource went. Without
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observability tools like Grafana or Prometheus, it’s easy to get lost in the logs.
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Another important aspect is resource consumption. Microservices require more resources to run and
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maintain. Each service runs as a separate application, which increases the costs of servers,
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databases and logging systems. It’s like choosing to build dozens of
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small bases instead of one large one, each requiring separate power
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and management. If your resources are limited, this division can be a problem.
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Finally, working with microservices requires a highly skilled team. You need to make sure
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that developers, DevOps engineers, and other specialists understand how to build
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and maintain such systems. For small teams, this can be an overwhelming task.
When to use microservices?
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When to use microservices?
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Microservices are a powerful tool, but they need to be used wisely. Not every task
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requires a complex distributed architecture. To understand
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whether they are suitable for your project, ask yourself a few questions:
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Is your project complex and requires scale? If your application includes many functions
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that can be divided into independent modules, microservices are your choice. For example,
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if in Factorio your base takes up the entire screen, and you plan to expand it,
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it is logical to divide production into separate blocks. This will allow you to scale only
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those areas that are truly congested. 2. Do you work in a large team? Microservices
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allow you to divide work between different teams, each of which is responsible for its own
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module. It’s as if you put one player in charge of logistics, another in charge of resource extraction,
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and a third in charge of production. This approach helps avoid conflicts and speeds up development.
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Do you need high stability? If your project is critical and the failure
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of one component should not affect the others, microservices will provide this resilience. For example,
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the failure of one mine in Factorio will not stop the entire process if the logistics are built correctly. It’s the
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same in microservices — the failure of one module should not affect the operation of the others.
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Is your project growing? Microservices are easier to update and scale, making them a great choice
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for startups and fast-growing applications. If you are constantly adding new features and
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improvements, this architecture will allow you to work faster and with less risk.
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However, if your project is small and doesn’t plan to grow anytime soon,
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a monolith may be a smarter choice. It is easier to set up,
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requires fewer resources and is less susceptible to network failures. For example, for a small base
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in Factorio, a monolith will be the best solution — less complexity, more time to play.
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Conclusion So, today we looked at how microservices help build flexible, scalable systems
Conclusion: Which to choose?
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using examples from Factorio. This architecture allows you to divide a project into independent parts
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that are easy to maintain and develop. However, it is important to remember
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that microservices are not suitable for all tasks. They require investment in infrastructure,
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monitoring and management, which is not always justified for small projects.
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The choice between monolith and microservices depends on your goals and resources. If you are planning
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long-term development and are willing to invest in support, microservices are a great solution.
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But if you’re just starting out or the project is small, a monolith may be more convenient and cost-effective.
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If you liked the video, don’t forget to like and subscribe! If you have any questions
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or want to learn more about specific technologies, write in the comments. Thanks
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for watching this video and see you in the next episode. York was with you, bye!