Event-driven architecture vs microservices
Microservices and event-driven architecture answer different questions, so they are not alternatives. Microservices is a decomposition choice: how many independently deployable services you run. Event-driven architecture is a communication choice: whether those services call each other directly or publish events that others react to. Most teams end up combining them.
That is why the comparison feels slippery when you search for it. You can run twenty microservices that only ever talk over synchronous HTTP, and you can run a single deployable application that is internally event-driven, with modules publishing to an in-process bus. Neither arrangement is a contradiction. The question worth arguing about is narrower: should service A call service B, or should service A announce that something happened and let B decide what to do about it?
What microservices decide
Microservices is about deployment boundaries. Each service owns its data, ships on its own schedule, and can be scaled or rewritten without coordinating a release with everyone else. The payoff is organizational as much as technical: small teams can move without waiting in line behind a shared deploy.
The costs are equally concrete. A call that used to be a function invocation becomes a network hop that can time out. Data that used to live in one transaction now lives in three databases, so you give up cross-service transactions and start reasoning about consistency by hand. Debugging turns into tracing a request across services. None of this is caused by events. It is the price of splitting the system up, and you pay it whether the services communicate with REST calls or with messages.
What event-driven architecture decides
Event-driven architecture changes the direction of knowledge. In a request/response system, the caller knows who it needs and what that service is for. In an event-driven system, the producer publishes a fact ("order.paid") to a message broker or event broker, and it does not know or care which consumers exist. Adding a fifth consumer for the same event costs nothing on the producer's side.
That inversion is the real feature. When the billing service wants to react to a new signup, it subscribes instead of asking the signup service to add another outbound call. Producers stop accumulating a list of everyone who depends on them, and a slow or broken consumer no longer takes the producer down with it, because the broker holds the message until the consumer catches up.
The costs are real too. Flow is harder to see, because no single file describes what happens after an order is paid. Ordering guarantees become something you configure rather than something you get for free. Consumers must tolerate duplicates, since almost every broker delivers at least once. And failures move from the caller to a dead letter queue that somebody has to actually watch.
Why the two get compared
The pairing shows up so often because microservices make the weaknesses of synchronous communication expensive. With three services, a chain of direct calls is fine. With thirty, a single request can fan out through six services, and its latency becomes the sum of all six, while its availability becomes the product of all six. One slow dependency at the bottom of the chain shows up as a timeout at the top.
Events break that chain. The producer writes to the broker and returns; consumers work through the backlog at their own pace. This is the same tradeoff as webhooks versus a message queue, one level up: you trade an immediate answer for the ability to keep going when the other side is not ready.
Choosing between synchronous calls and events
Use a direct call when the caller needs the answer to continue: authorization checks, price quotes, anything where the user is waiting on a value. Reaching for events here just adds a round trip through a broker and a correlation ID to keep track of.
Use events when the trigger and the reaction belong to different concerns. Sending a receipt, updating a search index, warming a cache, notifying an analytics pipeline: none of these need to happen before the checkout response is returned, and all of them will eventually be joined by a sixth and seventh consumer nobody has thought of yet. Consistent event naming matters more than usual here, because the event name is the contract.
Most systems land in the middle. Synchronous calls inside a request path, events for everything downstream of it. If you are choosing the plumbing, event bus versus message queue covers the difference between broadcasting an event and handing work to exactly one worker.
When your events need to leave the building
There is a third case that neither term covers: your customers want the events too. Internal brokers are not reachable from a customer's infrastructure, so the usual answer is webhooks, which are the same publish-and-forget model delivered over HTTP to endpoints you do not control.
Fanning events out to thousands of external endpoints turns out to be a different problem from routing them internally: per-customer retries, signature verification, endpoint health, rate limits, and a way for customers to replay what they missed. Svix handles that layer, so the event-driven design you built for internal consumers can serve external ones without a second delivery system growing inside your codebase.