Opensearch remote model connection error

Versions (relevant - OpenSearch/Dashboard/Server OS/Browser):

“type”: “status_exception”,
“reason”: “Error communicating with remote model: Acquire operation took longer than the configured maximum time. This indicates that a request cannot get a connection from the pool within the specified maximum time. This can be due to high request rate.\nConsider taking any of the following actions to mitigate the issue: increase max connections, increase acquire timeout, or slowing the request rate.\nIncreasing the max connections can increase client throughput (unless the network interface is already fully utilized), but can eventually start to hit operation system limitations on the number of file descriptors used by the process. If you already are fully utilizing your network interface or cannot further increase your connection count, increasing the acquire timeout gives extra time for requests to acquire a connection before timing out. If the connections doesn’t free up, the subsequent requests will still timeout.\nIf the above mechanisms are not able to fix the issue, try smoothing out your requests so that large traffic bursts cannot overload the client, being more efficient with the number of times you need to call AWS, or by increasing the number of hosts sending requests.”
},
“status”: 500
}

Describe the issue:

Configuration:

Relevant Logs or Screenshots:

Any idea how can solve this issue, I am using docker image opensearch 2.15.0

Remote model instance is reachable(ping is working).

Caused by: org.opensearch.OpenSearchStatusException: Error communicating with remote model: Acquire operation took longer than the configured maximum time. This indicates that a request cannot get a connection from the pool within the specified maximum time. This can be due to high request rate.

Could you try configuring client_config values specified in this doc: Connector blueprints - OpenSearch Documentation

I tried this as well, but finally removed dashboard and took new 2.15.0 fresh then I worked.

So I see some of jar’s were not update in dashboard docker image, which is solved now.

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