Webhooks, Polling, or a Real Event Stream: Choosing an Integration
Use polling when a few minutes of staleness is fine, a webhook when one source needs to notify one destination quickly, and a shared event stream when several systems must react to the same data. Teams often default to whichever pattern they already know instead of the one that fits the integration.
Here's how to actually choose, and what breaks when you pick the wrong one for a given case.
Polling: simple, but you're always somewhere between stale and wasteful
Polling means asking "anything new?" on a fixed schedule. It's the easiest pattern to build and debug, and it works fine when a few minutes of staleness is genuinely fine, like syncing a product catalog once an hour. The cost is that you're always tuned wrong in one direction: poll too often and you waste calls checking for nothing, poll too rarely and you're stale exactly when it matters.
Polling also scales badly with the number of things you're watching. Checking one resource every five minutes is trivial; checking ten thousand resources every five minutes each is a real load problem for whichever system is being polled.
Webhooks: near-instant, but you own retries and ordering
A webhook flips the direction: the source system pushes a notification the moment something happens, so there's no polling delay. The tradeoff is that you're now responsible for everything a message broker would normally handle for you: what happens if your endpoint is down when the webhook fires, what happens if two webhooks arrive out of order, and how you detect and ignore a duplicate delivery.
Webhooks work well for a single event type from a single source with modest volume, where building basic retry and idempotency handling around one endpoint is a reasonable amount of work. They get painful fast once you're receiving webhooks from many sources, each with its own retry behavior and payload format.
A real event stream: more setup, but ordering and replay come built in
Putting both systems on a shared event stream (a topic in a broker, rather than a direct call between two systems) means ordering within a partition, replay from a point in history, and multiple independent consumers reading the same events are handled by the platform instead of by each integration's custom code.
The cost is setup: someone has to run or manage the broker, define the topic and schema, and onboard each new consumer properly. That's real overhead for a single, simple integration, but it pays for itself once you have several systems that all need to react to the same events, since each new consumer is an addition to the stream rather than a new point-to-point connection to build and maintain.
How do you match the pattern to your number of consumers?
The deciding factor usually isn't event volume, it's how many independent systems need to react to the same data. One source feeding one destination rarely justifies a shared stream; poll or webhook it directly. One source feeding four or five downstream systems, each needing its own view of the same events, is exactly the case a shared stream is built for.
If you're migrating from webhooks to a stream because consumers have multiplied, keep the webhook endpoint running as a thin producer into the stream during the transition, rather than asking every existing integration to switch at once.
Use these rules of thumb to pick a pattern:
- Poll when a few minutes of staleness is acceptable and you're watching a small number of resources.
- Use a webhook for a near-instant notification, once you've built for retries, ordering, and duplicate detection.
- Use a shared event stream when several independent systems each need their own view of the same events.
- Write down the contract: which fields are guaranteed, how schema changes are handled, and what to do with unrecognized fields.
- Mix patterns deliberately instead of defaulting to one everywhere.
How should you define the integration contract?
Whichever integration pattern you choose, write down the actual contract: what fields are guaranteed to be present, what happens on a schema change, and what a consumer should do with a field it doesn't recognize. Undocumented contracts are the real source of most integration breakage, far more often than the choice between polling, webhooks, or streaming.
Version the contract explicitly (a version field in the payload, or a versioned topic name) so a breaking change doesn't take down every consumer built against the assumption that the format never changes.
Mixing patterns is normal, defaulting to one everywhere isn't
Most mature systems end up using all three patterns at once, and that's a sign of good judgment rather than inconsistency: polling for a low-stakes nightly sync with a vendor, a webhook for a single third-party notification, and a shared stream for the handful of events several internal systems all need to react to. The mistake isn't mixing patterns, it's picking one pattern early and forcing every later integration through it regardless of fit.
When a new integration comes up, ask the same two questions each time: how many independent systems need this data, and how much staleness or delivery risk is actually acceptable. Those two answers point to a pattern far more reliably than defaulting to whatever the last integration used.
What Good Looks Like
Integration is solid when the pattern (polling, webhook, or stream) matches how many systems actually need the data, and the contract each consumer relies on is documented and versioned.
Building The Capability (5-Stage Skill Ladder)
How to Get Started
Frequently Asked Questions
Is a real event stream always the more scalable choice?
Not automatically. A stream adds real operational overhead: someone has to run the broker, manage schemas, and onboard consumers correctly. For a single source feeding a single destination, a well-built webhook is simpler and just as reliable. Streams earn their overhead once several independent consumers need the same events.
How do we handle a webhook endpoint that's temporarily down?
Most webhook providers retry with backoff for a limited window, but you should never assume delivery is guaranteed. Build your endpoint to be idempotent (safe to receive the same event twice) and, for anything critical, poll a reconciliation endpoint periodically to catch events a webhook might have missed entirely.
What's the biggest mistake teams make switching from webhooks to a stream?
Trying to migrate every consumer at once instead of running both in parallel during a transition. Keep the webhook endpoint alive as a thin producer feeding the new stream, let consumers move over one at a time, and only retire the webhook once the last one has switched.
About the numbers
This guide doesn't quote a sourced benchmark. Figures in it are estimates or general guidance, so check them against your own numbers.
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