To install the Cluster Observability Operator please refer to this YouTube video. It should take only about 5 minutes in total and is easy to install. It has been supported since Red Hat OpenShift Container Platform 4.17.
What is the Cluster Observability Operator (COO)?
The Cluster Observability Operator (COO) is an optional component on the Red Hat OpenShift platform designed for creating and managing highly customizable monitoring stacks. It enables cluster administrators to automate configuration and management of monitoring needs extensively, offering a more tailored and detailed view of each namespace compared to the default OpenShift Container Platform monitoring system.
The COO structure is shown in Figures 1 and 2.
Why use COO in OpenShift?
There are a number of compelling reasons to utilize COO. For instance, the operator:
- Updates independently of OpenShift versions.
- Supports deployment of multiple monitoring stacks within a single cluster.
- Simplifies management in multi-tenant environments.
- Enables creation of custom monitoring views for user-defined projects.
- Provides flexibility to monitor Prometheus metrics at the instance, namespace, or tenant level.
- Allows extended retention of monitoring metrics.
What is the difference between OpenShift default monitoring stack and COO?
The table below summarizes he differences between OpenShift default monitoring stack and Cluster Observability Operator:
Aspect | OpenShift default monitoring stack | Cluster Observability Operator (COO) |
Scope | Limited to core components within the cluster (e.g., API server, ETCD) and OpenShift-specific namespaces. Provides basic monitoring suitable for standard needs. | Offers comprehensive monitoring and analytics for enterprise-level needs, covering cluster and workload performance. |
Functional Goals | Focuses on infrastructure health, using Prometheus and Alertmanager for basic monitoring and alerting. | Provides in-depth insights, focusing on granular performance and trend analysis. Supports historical analysis and capacity forecasting. |
Configuration Management | Built-in configurations offer limited customization. Users can set alerting and notification methods but lack options to adjust storage or retention policies. | Broader configuration options, including data retention periods, storage methods, and collected data types. High customization and extensibility via COO. |
Data Retention and Storage | Shorter data retention times, designed for short-term monitoring and real-time detection. | Supports long-term data retention, enabling historical data analysis and capacity planning. |
Use Cases | Suitable for basic needs, like tracking cluster component status and application health checks. | Ideal for advanced monitoring scenarios, such as trend forecasting and anomaly detection, suited for larger enterprises. |
Integration | Much more integrated into OpenShift Container Platform. For instance, WebConsole dashboard and alert management. | Lacks direct integration with OpenShift Container Platform and typically requires an external Grafana instance for dashboards. |
What do we need to use COO?
The following is required in order to use COO:
- Support installing the Operator in restricted networks or disconnected environments.
- Tempo Operator, OpenTelemetry Operator, Network Operator are optional (only needed if you wish to customize additional functionalities).
Who should use Cluster Observability Operator?
COO is useful to a variety of roles:
- Enterprise-level users and administrators: Those who require in-depth monitoring capabilities for OpenShift clusters, including advanced performance analysis, long-term data retention, trend forecasting, and historical analysis will find COO useful. These features help enterprises better understand resource usage, prevent performance issues, and optimize resource allocation.
- Operations teams in multi-tenant environments: With multi-tenancy support, COO allows different teams to configure monitoring views for their projects and applications, making it suitable for teams with flexible monitoring needs.
- Development and operations teams: Teams that need fine-grained monitoring and customizable observability views for in-depth troubleshooting, anomaly detection, and performance tuning during development and operations.
In summary, COO is ideal for users who need high customizability, scalability, and long-term data retention, particularly in complex, multi-tenant enterprise environments.
