Multi-Instance Deployment

You might say

Run several instances to share requests, but keep users logged in when their next request reaches another instance.

Multi-instance deployment runs multiple instances of the same service that receive requests together.A load balancer can send requests to instance-a and instance-b, so another instance can serve traffic when one restarts. If a login session lives only in one instance's local memory, a user may be logged out after the next request reaches another instance; the state must be shared or externalized. Multiple instances can improve service redundancy and throughput, but they do not automatically make a database highly available or solve concurrency coordination and consistency.

Know first

Deployment Monitoring Single-Instance Deployment

What must remain visible when requests move between instances

Multi-instance web servicereplicas = 3

traffic / network

load balancerdistributes traffic

web-1 / web-2Healthy

web-3Healthy

EvidenceRequest logs show several instance IDs

Multiple replicas of one service share traffic.

What multi-instance deployment adds and leaves open

Multiple instances share requests and offer takeover: An entry point can route requests to several equivalent service instances; when one is maintained or fails, other healthy instances may continue serving traffic. Verify replica count and routing against the service goal instead of trusting a deployment page that merely lists processes.

Cross-request state cannot hide in one instance: If a user's first request reaches instance-a and the next reaches instance-b, b cannot identify the user when the session exists only in a's memory. Put session state and similar data in shared or external storage, then route the same user to different instances and verify the session remains valid. This still does not prove database high availability or correct business coordination.

Scheduled reports reveal another multi-instance issue: After a daily-report service scales to multiple instances, each instance may trigger the same report at the same time. Coordinate through a shared task record or a single-execution rule so the report is not generated and sent more than once.

You can say this to an AI Agent

Deploy this stateless web service with multiple instances and confirm the entry point can send requests to any healthy instance. Inspect state that must survive across requests, such as login sessions and upload progress; do not keep it only in one instance's memory. After the change, send the same user's requests to different instances and verify the session remains valid. Also state which database high-availability and coordination problems this multi-instance setup does not solve automatically.

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After a multi-instance release, users are occasionally asked to sign in again. What should you inspect first?

A. Check only whether the database has backups and conclude instance state is unrelatedB. Check whether requests reach different instances and whether the session exists only in one instance's local memoryC. Add more instances because more replicas automatically share login state