Monitor service message processing

Latest Dynatrace
Tutorial
3-min read
Published Jan 15, 2026

Modern distributed systems rely heavily on asynchronous communication through message queues and streaming platforms. Understanding message flow, throughput, and processing failures is critical for maintaining system reliability.

Monitoring service message processing in Dynatrace addresses this need by providing comprehensive visibility into message-based transactions across your microservices architecture, helping you track throughput, identify bottlenecks, and resolve processing issues.

What is service message processing monitoring?

In Dynatrace, message processing refers to any transaction involving message queues or streaming platforms like Kafka, RabbitMQ, ActiveMQ, and AWS SQS. This includes messages published to topics, received from queues, and processed by consuming services.

Service message processing monitoring helps you understand how messages flow through your distributed systems, detect processing bottlenecks, and identify failures in asynchronous communication patterns.

You can access service message processing directly from Services Services, or through custom dashboards and alerts configured to monitor messaging metrics.

This feature is designed for SREs, developers, and platform engineers who need visibility into asynchronous communication patterns and message processing health.

Service message processing monitoring provides:

Real-time visibility into message publish, receive, and process rates
Identification of processing bottlenecks and queue lag
Tracking of message flow between producing and consuming services
Error rate monitoring for failed message processing
Infrastructure dependency mapping for messaging platforms
Integration with distributed traces for root cause analysis

Metrics reference

Dynatrace provides four core metrics for monitoring message processing:

Metric	Description	Unit
`dt.service.messaging.publish.count`	Messages sent to queues/topics	count
`dt.service.messaging.receive.count`	Messages received from queues/topics	count
`dt.service.messaging.process.count`	Messages successfully processed	count
`dt.service.messaging.process.failure_count`	Messages that failed processing	count

Key dimensions

Dimension	Description	Example values
`messaging.destination.name`	Queue or topic name	`authorQueue`, `orderEvents`
`dt.entity.service`	Service identifier	`spring-kafka-producer`
`messaging.system`	Messaging platform	`kafka`, `rabbitmq`, `aws_sqs`
`aws.account.id`	AWS account identifier	`123456789012`
`aws.region`	AWS region	`us-east-1`
`k8s.cluster.name`	Kubernetes cluster name	`prod-cluster`
`k8s.namespace.name`	Kubernetes namespace	`payment-services`

Get started

To begin monitoring service message processing

Go to Services, select the Explorer tab, and select Message processing.
Select the service and queue/topic you want to monitor.
View Publish rate, Receive rate, and Process rate in the time series charts.
Identify lag by comparing receive rates to process rates.
Drill down to distributed traces to investigate specific message failures.

Query examples

Monitor service messaging throughput:

timeseries throughput = sum(dt.service.messaging.process.count),
  by: {dt.smartscape.service}
| lookup [smartscapeNodes "SERVICE" | fields name,id],
  sourceField:dt.smartscape.service, lookupField:id
| fieldsAdd `Service` = lookup.name, dt.smartscape.service
| summarize throughput = sum(throughput[]),
  by: { timeframe, interval, `Service`, dt.smartscape.service }

Calculate service messaging failure rate:

timeseries { throughput = sum(dt.service.messaging.process.count),
             failure_count = sum(dt.service.messaging.process.failure_count) },
  by: {dt.smartscape.service}, nonempty:true, union:true
| lookup [ smartscapeNodes "SERVICE" | fields name, id],
  sourceField:dt.smartscape.service, lookupField:id
| fieldsAdd `Service` = lookup.name, dt.smartscape.service
| summarize failure_rate = sum((failure_count[] / throughput[]) * 100),
  by: { timeframe, interval, `Service`, dt.smartscape.service }