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System Design: Background Job-Processing Workers! Basic application setups fail when executing long-running tasks like email delivery sequentially inside the user request loop. Slow downstream services cause high latency, while API timeouts trigger immediate request failures for the end user. Never risk data drift by pushing straight to a message queue after a database save, because a crash between those two actions drops the task completely. Instead, implement the Transactional Outbox pattern t
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System Design: Background Job-Processing Workers! Basic application setups fail when executing long-running tasks like email delivery sequentially inside the user request loop. Slow downstream services cause high latency, while API timeouts trigger immediate request failures for the end user. Never risk data drift by pushing straight to a message queue after a database save, because a crash between those two actions drops the task completely. Instead, implement the Transactional Outbox pattern t
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Part 1 ~ Microservices Will Finally Makes Sense After This Video In this video, Cloud X Berry explains microservices in a simple and beginner-friendly way. Amazon, Netflix, Uber and Spotify ship software updates every single day — and millions of people keep using those apps without ever noticing. That is not luck. It comes down to how the backend is put together, and one of the most popular patterns behind it is called microservices. We start where every application starts: one project, one cod
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What is Microservices Architecture 🤯 Guys! Microservices architecture is a system design where an application is split into many small, independent services that each handle a specific business capability. Each service runs independently, communicates through APIs, and can be developed or deployed without affecting the others. This allows teams to scale, update, and maintain parts of the system separately instead of managing one large codebase. In short, microservices break a big application in
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Day 12/31-365 follow for more such content. . -In our microservices architecture we used Apache Kafka for event-driven communication between services. For example, when a user completes a transaction, the Order service publishes an event to Kafka. Multiple services like Notification, Analytics, and Audit consume the same event asynchronously without impacting the main transaction flow. . Interviewer: Why not use MQ? . You: Traditional MQ systems like RabbitMQ or IBM MQ follow a queue-based model
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