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Chapter 1. About Observability
Red Hat OpenShift Observability provides real-time visibility, monitoring, and analysis of various system metrics, logs, and events to help users quickly diagnose and troubleshoot issues before they impact systems or applications. To help ensure the reliability, performance, and security of your applications and infrastructure, OpenShift Dedicated offers the following Observability components:
- Monitoring
- Logging
Red Hat OpenShift Observability connects open-source observability tools and technologies to create a unified Observability solution. The components of Red Hat OpenShift Observability work together to help you collect, store, deliver, analyze, and visualize data.
With the exception of monitoring, Red Hat OpenShift Observability components have distinct release cycles separate from the core OpenShift Dedicated release cycles. See the Red Hat OpenShift Operator Life Cycles page for their release compatibility.
1.1. Monitoring
Monitor the in-cluster health and performance of your applications running on OpenShift Dedicated with metrics and customized alerts for CPU and memory usage, network connectivity, and other resource usage. Monitoring stack components are deployed and managed by the Cluster Monitoring Operator.
Monitoring stack components are deployed by default in every OpenShift Dedicated installation and are managed by the Cluster Monitoring Operator (CMO). These components include Prometheus, Alertmanager, Thanos Querier, and others. The CMO also deploys the Telemeter Client, which sends a subset of data from platform Prometheus instances to Red Hat to facilitate Remote Health Monitoring for clusters.
For more information, see About OpenShift Dedicated monitoring and About remote health monitoring.
1.2. Logging
Collect, visualize, forward, and store log data to troubleshoot issues, identify performance bottlenecks, and detect security threats. In logging 5.7 and later versions, users can configure the LokiStack deployment to produce customized alerts and recorded metrics.
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