What is distributed data consistency in microservices?
What was a transaction in a monolith becomes a saga across services. You need to handle partial failures, idempotency, and eventual consistency because no single database owns all the data.
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More FAQs in Pros and Cons of Microservices Architecture
Independent deployments, independent scaling, team autonomy, fault isolation, and tech flexibility. Each service can be deployed, scaled, and owned independently.
Complexity, network calls instead of function calls, distributed data consistency, harder debugging, and operational overhead. You need a real DevOps setup to run them.
A single request can hit multiple services. Tracing it requires distributed tracing and central logs. You cannot just set a breakpoint in one process and step through everything.
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