As a service owner, you can use Jaeger to instrument your services to gather insights into your service architecture. Jaeger is an open source distributed tracing platform that you can use for monitoring, network profiling, and troubleshooting the interaction between components in modern, cloud-native, microservices-based applications.
Using Jaeger lets you perform the following functions:
Monitor distributed transactions
Optimize performance and latency
Perform root cause analysis
Jaeger is based on the vendor-neutral OpenTracing APIs and instrumentation.
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This release of OpenShift Jaeger adds support for installing Jaeger as a standalone solution, rather than as a component of Red Hat OpenShift Service Mesh.
These limitations exist in Jaeger:
While Kafka publisher is included as part of Jaeger, it is not supported.
Apache Spark is not supported.
Only self-provisioned Elasticsearch instances are supported. External Elasticsearch instances are not supported in this release.
These are the known issues in Jaeger:
TRACING-1166 It is not currently possible to use the Jaeger streaming strategy within a disconnected environment. When a Kafka cluster is being provisioned, it results in a error:
Failed to pull image registry.redhat.io/amq7/amq-streams-kafka-24-rhel7@sha256:f9ceca004f1b7dccb3b82d9a8027961f9fe4104e0ed69752c0bdd8078b4a1076.
TRACING-809 Jaeger Ingester is incompatible with Kafka 2.3. When there are two or more instances of the Jaeger Ingester and enough traffic it will continuously generate rebalancing messages in the logs. This is due to a regression in Kafka 2.3 that was fixed in Kafka 2.3.1. For more information, see Jaegertracing-1819.