@yasminemblz: J’ai reçu mon compoudrier 💫 #unboxing #martinecosmetics #totallyspies

YASMINE 🥥🌴🌸
YASMINE 🥥🌴🌸
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Thursday 08 October 2026 11:33:25 GMT
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Monolith vs microservices, in one sentence: it's the same app either way. Same five things. Users. Products. Orders. Payments. Notifications. The only thing that changes is where you draw the boundary around them. In a monolith they sit inside one box → 1 codebase, 1 deploy, 1 database, 0 network hops. Calling another part of the app is just a function call. 0.2ms. Simple — and that simplicity is a real advantage. Then you grow. 50 engineers in one merge queue. One line changed means redeploying the entire backend. One bug takes down the whole app. One hot feature and you're scaling all five. So you move the line. Five services. Five deploys. Scale checkout without scaling notifications. Payments ships without asking the search team. But that function call is now a network request. And networks fail. Retries. Timeouts. Service discovery. Load balancing. Distributed tracing. Auth between services. Monitoring. Events. Queues. Idempotency. Eventual consistency. Eleven things you now have to run — before you ship a single feature. Then the payment succeeds and the order service crashes before recording it. And now you're debugging a request that travelled through six services instead of reading one log. Microservices don't remove complexity. They move it. You trade codebase complexity for distributed systems complexity — which is why the answer depends on scale. Five engineers splitting into 30 services on day one is a disaster. A well-structured monolith takes you surprisingly far. Then you extract the painful part. Payments first. Then search. Then notifications. The goal was never more services. It's putting complexity where your team can actually handle it. Which side are you on right now? 👇 #systemdesign #microservices #softwareengineering #backenddev #codingreels
Monolith vs microservices, in one sentence: it's the same app either way. Same five things. Users. Products. Orders. Payments. Notifications. The only thing that changes is where you draw the boundary around them. In a monolith they sit inside one box → 1 codebase, 1 deploy, 1 database, 0 network hops. Calling another part of the app is just a function call. 0.2ms. Simple — and that simplicity is a real advantage. Then you grow. 50 engineers in one merge queue. One line changed means redeploying the entire backend. One bug takes down the whole app. One hot feature and you're scaling all five. So you move the line. Five services. Five deploys. Scale checkout without scaling notifications. Payments ships without asking the search team. But that function call is now a network request. And networks fail. Retries. Timeouts. Service discovery. Load balancing. Distributed tracing. Auth between services. Monitoring. Events. Queues. Idempotency. Eventual consistency. Eleven things you now have to run — before you ship a single feature. Then the payment succeeds and the order service crashes before recording it. And now you're debugging a request that travelled through six services instead of reading one log. Microservices don't remove complexity. They move it. You trade codebase complexity for distributed systems complexity — which is why the answer depends on scale. Five engineers splitting into 30 services on day one is a disaster. A well-structured monolith takes you surprisingly far. Then you extract the painful part. Payments first. Then search. Then notifications. The goal was never more services. It's putting complexity where your team can actually handle it. Which side are you on right now? 👇 #systemdesign #microservices #softwareengineering #backenddev #codingreels

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