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Sticky routing preserves a client’s affinity to a previously selected backend; it does not guarantee that the assignment remains useful forever. If inactive clients’ records never expire, those records can inflate assignment counts and make a backend appear busier than it is. Use an inactivity TTL to release idle assignments, and check expiry in the routing decision itself rather than relying on a datastore’s background cleanup.
What sticky routing preserves
A sticky-routing system maps a client or session to a backend, then consults that mapping on later requests so the client can return to the same destination. In one common design, the router stores one client-to-backend assignment and consults the table before assigning new clients to the least-loaded node.
Affinity is not durable state storage, and it is not an unconditional promise that a client will stay on one backend. For example, NVIDIA Dynamo v1.2.0 documents a StickySessionRouter with an in-memory mapping from session_id to (worker_id, dp_rank) and a sliding-window TTL. A bind action creates router-only affinity; later requests with that session ID go to the pinned worker and rank while the mapping remains valid. NVIDIA Dynamo v1.2.0 documentation.
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How permanent records distort an assignment-count signal
Suppose the router counts every row in its assignment table as a current assignment. A client uses a backend, then becomes idle, but its row remains indefinitely. The row still contributes to that backend’s apparent load even though the client may no longer be using it. If the router uses those counts to choose a least-loaded node, the stale row can influence later placements and make the count a misleading proxy for current activity.
This is a failure pattern, not a claim that every permanent mapping inevitably creates imbalance. The scale and effect depend on the routing design and workload; no frequency or impact measurement is established here. The diagnostic question is: when does this stop being true? If the answer is “never,” the table can preserve historical assignments rather than reflect active demand.
Use inactivity expiry to release idle assignments
Give each assignment a TTL that is renewed after the successful event that should count as continued use. This makes the expiry a sliding inactivity window: a returning client refreshes its mapping, while a client that stays away long enough eventually loses it. A later request can then be assigned anew.
Choose the refresh event and duration for the application’s behavior; there is no universally correct routing TTL established by these sources. Consider what the assignment protects, how long a legitimate client may be idle between requests, and whether the backend’s own session or resource timeout is coordinated with the affinity window.
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- Fixed expiry: the record expires at a set time regardless of continued activity.
- Sliding expiry: qualifying successful use renews the inactivity window.
- Backend failure: decide whether to invalidate the pin and reassign, or follow another recovery path; affinity alone cannot make an unavailable backend usable.
Why disconnect events are not enough
A delete triggered by an orderly disconnect can clean up some assignments, but clients do not always disconnect cleanly. A process can crash, a tab can close, a connection can drop, or a network partition can prevent a final event from reaching the service. If cleanup depends only on that event, these assignments may remain indefinitely. An inactivity TTL handles silent departures by keeping a mapping alive only when the client returns and refreshes it before expiry.
Separate expiry correctness from DynamoDB cleanup
DynamoDB TTL is a storage cleanup mechanism, not a synchronous guarantee that an expired item has disappeared. Amazon Web Services says, “DynamoDB typically deletes expired items within two days of expiration.” AWS also says timing varies with workload; expired items awaiting deletion can still appear in reads, queries, and scans. This is a cleanup timing statement, not a routing-performance statistic. Amazon DynamoDB API Reference: TTL.
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If an expired assignment must not affect routing, evaluate its expiry timestamp when reading or using the record. AWS documents filtering expired records, and application logic should likewise treat an expired mapping as invalid even while the item remains physically present. A background TTL sweep can eventually remove old rows, but it should not be the mechanism that decides whether a mapping is valid for the current routing decision.
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What to verify in a sticky-routing design
- Is expiry fixed or sliding?
- Which successful request or action refreshes the TTL?
- Does the read path reject an expired mapping, independently of datastore cleanup?
- What happens to a pin when its worker or backend disappears?
- Are local session or resource timeouts aligned with the routing-affinity window?
These questions matter in Kubernetes-based routing too. TrueFoundry describes sticky routing with a client-provided session header and consistent hashing, while warning that pods and nodes are transient. Deletion, eviction, or scaling can cause reassignment, so affinity is best effort; its documentation cautions against placing critical stateful logic in Services. TrueFoundry sticky routing documentation.
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