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Reconnect backoff can make each client wait longer without stopping many clients from trying again at the same moment. If a service outage makes a large group disconnect together, clients following the same deterministic schedule can reconnect in synchronized bursts. Those bursts add work while the service is recovering, potentially prolonging the failure.
The fix is not simply “wait longer.” A robust retry policy also spreads attempts with jitter, sets a maximum delay and an overall retry budget, and avoids retrying permanently failing operations. The exact behavior depends on what is reconnecting: browser WebSockets and server-sent events (EventSource), for example, do not handle reconnection the same way.
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Why can reconnecting make an outage last longer?
Suppose many clients lose their connections at once. If they all wait the same fixed interval, they will all try again together. Exponential backoff increases the interval after successive failures, but if every client uses the same schedule, it can preserve that alignment: many clients still make each next attempt in a cluster.
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That burst can arrive when the service is already short of capacity. Failed attempts consume resources too, and retrying during overload can increase the strain rather than help recovery. AWS describes the pattern directly: “Simple backoff alone is not enough because in distributed systems all clients may backoff simultaneously, creating clusters of retry calls.” The statement is guidance about a distributed-systems risk, not a measurement of how often reconnects cause outages. AWS Well-Architected, REL05-BP03
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What does reconnecting mean for WebSockets and EventSource?
WebSockets
Creating a browser WebSocket starts a connection attempt. If it cannot be established, the browser fires an error event followed by a close event. The WebSocket API does not supply a general application retry policy: client code or a library decides whether and when to create a replacement connection. A longer delay you observe may therefore come from that application logic rather than from the browser itself. MDN: WebSocket() constructor
EventSource (server-sent events)
EventSource reconnects by default when its stream ends. The server can specify a reconnection delay in the stream using a retry field whose value is an integer number of milliseconds. This is EventSource behavior; it should not be assumed to describe WebSockets. MDN: Using server-sent events
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How does jitter change the retry pattern?
Jitter adds randomness to the wait so clients that failed together are more likely to make their next attempts at different times. A common policy combines increasing delays with a cap, then randomizes the actual wait. The result is a spread of attempts instead of a single synchronized wave. AWS’s explanation of exponential backoff and jitter uses illustrative simulations to compare contention patterns; those simulations should not be read as production fleet failure rates. AWS Architecture Blog: Exponential Backoff And Jitter
There is no universally correct delay, cap, or retry count in the guidance cited here. Choose them according to service capacity and how quickly users need recovery, then test how the system behaves during both an outage and recovery. For broader discussion of timeouts, retries, backoff, overload, and safe repeated operations, see the Amazon Builders’ Library article on timeouts, retries, and backoff with jitter.
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What should a reconnect policy include?
- Increasing delay with a cap: lengthen waits after successive failures, but prevent the delay from growing without bound.
- Jitter: randomize the wait so a group of clients does not repeatedly retry in lockstep.
- A retry budget: limit attempts, elapsed retry time, or both, so work remains bounded.
- Failure classification: retry transient failures where another attempt may succeed; stop or surface failures that are permanent instead of retrying them blindly.
- Cancellation: stop scheduled attempts when the user leaves, the operation is no longer needed, or the application has otherwise abandoned recovery.
- Safe handling of repeated work: protect writes and commands against duplicate effects if the client may resend them after reconnecting.
A failed response does not prove that the server performed no side effect. If reconnect logic replays queued commands or writes, make those operations idempotent where possible, or use another design that safely handles duplicates. Both the Amazon Builders’ Library and AWS Well-Architected guidance discuss retry safety and limiting retry calls. Amazon Builders’ Library; AWS Well-Architected, REL05-BP03
How can multiple retry layers multiply traffic?
A reconnect may be retried by more than one part of an application: UI code, a connection library, a service worker, a proxy, or a downstream SDK. If each layer retries independently, the total attempts can multiply. Choose which layer owns retries, inspect the behavior of the other layers, and avoid assuming that an SDK’s default policy is appropriate for a browser connection. AWS recommends limiting retries, selecting retry ownership, handling errors, and observing retry behavior. AWS Well-Architected, REL05-BP03
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Useful diagnostics include the attempt number, chosen delay, error or close classification, time to recovery, and whether an attempt was cancelled. These help distinguish a single client’s slow recovery from synchronized retries across many clients and give you evidence for tuning the policy.
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- How the delay grows and where it is capped.
- Which jitter method is used and how widely it spreads attempts.
- Whether the retry limit is based on attempt count, elapsed time, or both.
- Which failure types are retried and which stop the process.
- Which application layer owns the retries.
- How cancellation works, how long users may wait, and whether repeated operations are safe.
These trade-offs depend on the system and user need; the cited guidance does not establish one numeric configuration as best for every application.
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