Case Study : Performance tuning and monitoring of RabbitMQ instances in CSN

The CSN team decided to scale the system both vertically and horizontally in terms of the RabbitMQ message broker by introducing more RAM and disk space on each of the RabbitMQ instance servers and change the RabbitMQ configuration parameters accordingly so that the broker can use more memory and disk space, if needed. The team also decided to introduce more RAM nodes for the chat queues along with a deployment of Nagios to monitor all the parts of the system (including the message broker) and send notifications to the team in case of issues with resource utilization based on defined thresholds.

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