Message Queue Throughput Calculator Connector for AI agents.

Yes, it's designed to help you plan capacity for Kafka, RabbitMQ, and SQS. You can use it to figure out how many partitions or consumers you need for specific throughput targets.

It takes your current backlog size and your processing speed to predict exactly how long it will take to clear. This helps you give accurate recovery times during an incident.

It's perfect for that. It lets you verify if your current SQS consumer setup can handle your workload or if you need to scale up.

Yes, it works for RabbitMQ too. You can use it to calculate your concurrency levels and ensure your message processing is staying within your limits.

It uses Little's Law to calculate your average in-flight messages. This tells you how many messages your system is processing at any given moment.

It helps you avoid over-provisioning. By calculating the exact number of consumers you need for a target throughput, you can save money on unnecessary resources.

You can use the calculate_consumer_needs capability. By providing your target messages per second and average processing time, it will tell you exactly how many consumers or partitions are required.

Yes. Use the estimate_backlog_drain capability by inputting your current lag count and your current processing throughput to get an estimated drain time in seconds and minutes.

The calculate_inflight_concurrency capability uses Little's Law to determine the average number of messages being processed simultaneously based on your arrival rate and processing latency.