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Monitoring overview - Monitoring | Observability | OKD 4.14
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About OKD monitoring

OKD includes a preconfigured, preinstalled, and self-updating monitoring stack that provides monitoring for core platform components. You also have the option to enable monitoring for user-defined projects.

A cluster administrator can configure the monitoring stack with the supported configurations. OKD delivers monitoring best practices out of the box.

A set of alerts are included by default that immediately notify administrators about issues with a cluster. Default dashboards in the OKD web console include visual representations of cluster metrics to help you to quickly understand the state of your cluster. With the OKD web console, you can view and manage metrics, alerts, and review monitoring dashboards.

In the Observe section of OKD web console, you can access and manage monitoring features such as metrics, alerts, monitoring dashboards, and metrics targets.

After installing OKD, cluster administrators can optionally enable monitoring for user-defined projects. By using this feature, cluster administrators, developers, and other users can specify how services and pods are monitored in their own projects. As a cluster administrator, you can find answers to common problems such as user metrics unavailability and high consumption of disk space by Prometheus in Troubleshooting monitoring issues.

Understanding the monitoring stack

The OKD monitoring stack is based on the Prometheus open source project and its wider ecosystem. The monitoring stack includes the following:

  • Default platform monitoring components. A set of platform monitoring components are installed in the openshift-monitoring project by default during an OpenShift Container Platform installation. This provides monitoring for core cluster components including Kubernetes services. The default monitoring stack also enables remote health monitoring for clusters.

    These components are illustrated in the Installed by default section in the following diagram.

  • Components for monitoring user-defined projects. After optionally enabling monitoring for user-defined projects, additional monitoring components are installed in the openshift-user-workload-monitoring project. This provides monitoring for user-defined projects. These components are illustrated in the user section in the following diagram.

OKD monitoring architecture

Default monitoring components

By default, the OKD 4.14 monitoring stack includes these components:

Table 1. Default monitoring stack components
Component Description

Cluster Monitoring Operator

The Cluster Monitoring Operator (CMO) is a central component of the monitoring stack. It deploys, manages, and automatically updates Prometheus and Alertmanager instances, Thanos Querier, Telemeter Client, and metrics targets. The CMO is deployed by the Cluster Version Operator (CVO).

Prometheus Operator

The Prometheus Operator (PO) in the openshift-monitoring project creates, configures, and manages platform Prometheus instances and Alertmanager instances. It also automatically generates monitoring target configurations based on Kubernetes label queries.

Prometheus

Prometheus is the monitoring system on which the OKD monitoring stack is based. Prometheus is a time-series database and a rule evaluation engine for metrics. Prometheus sends alerts to Alertmanager for processing.

Prometheus Adapter

The Prometheus Adapter (PA in the preceding diagram) translates Kubernetes node and pod queries for use in Prometheus. The resource metrics that are translated include CPU and memory utilization metrics. The Prometheus Adapter exposes the cluster resource metrics API for horizontal pod autoscaling. The Prometheus Adapter is also used by the oc adm top nodes and oc adm top pods commands.

Alertmanager

The Alertmanager service handles alerts received from Prometheus. Alertmanager is also responsible for sending the alerts to external notification systems.

kube-state-metrics agent

The kube-state-metrics exporter agent (KSM in the preceding diagram) converts Kubernetes objects to metrics that Prometheus can use.

monitoring-plugin

The monitoring-plugin dynamic plugin component deploys the monitoring pages in the Observe section of the OKD web console. You can use Cluster Monitoring Operator (CMO) config map settings to manage monitoring-plugin resources for the web console pages.

openshift-state-metrics agent

The openshift-state-metrics exporter (OSM in the preceding diagram) expands upon kube-state-metrics by adding metrics for OKD-specific resources.

node-exporter agent

The node-exporter agent (NE in the preceding diagram) collects metrics about every node in a cluster. The node-exporter agent is deployed on every node.

Thanos Querier

Thanos Querier aggregates and optionally deduplicates core OKD metrics and metrics for user-defined projects under a single, multi-tenant interface.

Telemeter Client

Telemeter Client sends a subsection of the data from platform Prometheus instances to Red Hat to facilitate Remote Health Monitoring for clusters.

All of the components in the monitoring stack are monitored by the stack and are automatically updated when OKD is updated.

All components of the monitoring stack use the TLS security profile settings that are centrally configured by a cluster administrator. If you configure a monitoring stack component that uses TLS security settings, the component uses the TLS security profile settings that already exist in the tlsSecurityProfile field in the global OKD apiservers.config.openshift.io/cluster resource.

Default monitoring targets

In addition to the components of the stack itself, the default monitoring stack monitors additional platform components.

The following are examples of monitoring targets:

  • CoreDNS

  • etcd

  • HAProxy

  • Image registry

  • Kubelets

  • Kubernetes API server

  • Kubernetes controller manager

  • Kubernetes scheduler

  • OpenShift API server

  • OpenShift Controller Manager

  • Operator Lifecycle Manager (OLM)

  • The exact list of targets can vary depending on your cluster capabilities and installed components.

  • Each OKD component is responsible for its monitoring configuration. For problems with the monitoring of an OKD component, open a Jira issue against that component, not against the general monitoring component.

Other OKD framework components might be exposing metrics as well. For details, see their respective documentation.

Components for monitoring user-defined projects

OKD 4.14 includes an optional enhancement to the monitoring stack that enables you to monitor services and pods in user-defined projects. This feature includes the following components:

Table 2. Components for monitoring user-defined projects
Component Description

Prometheus Operator

The Prometheus Operator (PO) in the openshift-user-workload-monitoring project creates, configures, and manages Prometheus and Thanos Ruler instances in the same project.

Prometheus

Prometheus is the monitoring system through which monitoring is provided for user-defined projects. Prometheus sends alerts to Alertmanager for processing.

Thanos Ruler

The Thanos Ruler is a rule evaluation engine for Prometheus that is deployed as a separate process. In OKD 4.14 , Thanos Ruler provides rule and alerting evaluation for the monitoring of user-defined projects.

Alertmanager

The Alertmanager service handles alerts received from Prometheus and Thanos Ruler. Alertmanager is also responsible for sending user-defined alerts to external notification systems. Deploying this service is optional.

The components in the preceding table are deployed after monitoring is enabled for user-defined projects.

All of these components are monitored by the stack and are automatically updated when OKD is updated.

Monitoring targets for user-defined projects

When monitoring is enabled for user-defined projects, you can monitor:

  • Metrics provided through service endpoints in user-defined projects.

  • Pods running in user-defined projects.

Understanding the monitoring stack in high-availability clusters

By default, in multi-node clusters, the following components run in high-availability (HA) mode to prevent data loss and service interruption:

  • Prometheus

  • Alertmanager

  • Thanos Ruler

  • Thanos Querier

  • Prometheus Adapter

  • Monitoring plugin

The component is replicated across two pods, each running on a separate node. This means that the monitoring stack can tolerate the loss of one pod.

Prometheus in HA mode
  • Both replicas independently scrape the same targets and evaluate the same rules.

  • The replicas do not communicate with each other. Therefore, data might differ between the pods.

Alertmanager in HA mode
  • The two replicas synchronize notification and silence states with each other. This ensures that each notification is sent at least once.

  • If the replicas fail to communicate or if there is an issue on the receiving side, notifications are still sent, but they might be duplicated.

Prometheus, Alertmanager, and Thanos Ruler are stateful components. To ensure high availability, you must configure them with persistent storage.

Glossary of common terms for OKD monitoring

This glossary defines common terms that are used in OKD architecture.

Alertmanager

Alertmanager handles alerts received from Prometheus. Alertmanager is also responsible for sending the alerts to external notification systems.

Alerting rules

Alerting rules contain a set of conditions that outline a particular state within a cluster. Alerts are triggered when those conditions are true. An alerting rule can be assigned a severity that defines how the alerts are routed.

Cluster Monitoring Operator

The Cluster Monitoring Operator (CMO) is a central component of the monitoring stack. It deploys and manages Prometheus instances such as, the Thanos Querier, the Telemeter Client, and metrics targets to ensure that they are up to date. The CMO is deployed by the Cluster Version Operator (CVO).

Cluster Version Operator

The Cluster Version Operator (CVO) manages the lifecycle of cluster Operators, many of which are installed in OKD by default.

config map

A config map provides a way to inject configuration data into pods. You can reference the data stored in a config map in a volume of type ConfigMap. Applications running in a pod can use this data.

Container

A container is a lightweight and executable image that includes software and all its dependencies. Containers virtualize the operating system. As a result, you can run containers anywhere from a data center to a public or private cloud as well as a developer’s laptop.

custom resource (CR)

A CR is an extension of the Kubernetes API. You can create custom resources.

etcd

etcd is the key-value store for OKD, which stores the state of all resource objects.

Fluentd

Fluentd is a log collector that resides on each OKD node. It gathers application, infrastructure, and audit logs and forwards them to different outputs.

Fluentd is deprecated and is planned to be removed in a future release. Red Hat provides bug fixes and support for this feature during the current release lifecycle, but this feature no longer receives enhancements. As an alternative to Fluentd, you can use Vector instead.

Kubelets

Runs on nodes and reads the container manifests. Ensures that the defined containers have started and are running.

Kubernetes API server

Kubernetes API server validates and configures data for the API objects.

Kubernetes controller manager

Kubernetes controller manager governs the state of the cluster.

Kubernetes scheduler

Kubernetes scheduler allocates pods to nodes.

labels

Labels are key-value pairs that you can use to organize and select subsets of objects such as a pod.

node

A worker machine in the OKD cluster. A node is either a virtual machine (VM) or a physical machine.

Operator

The preferred method of packaging, deploying, and managing a Kubernetes application in an OKD cluster. An Operator takes human operational knowledge and encodes it into software that is packaged and shared with customers.

Operator Lifecycle Manager (OLM)

OLM helps you install, update, and manage the lifecycle of Kubernetes native applications. OLM is an open source toolkit designed to manage Operators in an effective, automated, and scalable way.

Persistent storage

Stores the data even after the device is shut down. Kubernetes uses persistent volumes to store the application data.

Persistent volume claim (PVC)

You can use a PVC to mount a PersistentVolume into a Pod. You can access the storage without knowing the details of the cloud environment.

pod

The pod is the smallest logical unit in Kubernetes. A pod is comprised of one or more containers to run in a worker node.

Prometheus

Prometheus is the monitoring system on which the OKD monitoring stack is based. Prometheus is a time-series database and a rule evaluation engine for metrics. Prometheus sends alerts to Alertmanager for processing.

Prometheus adapter

The Prometheus Adapter translates Kubernetes node and pod queries for use in Prometheus. The resource metrics that are translated include CPU and memory utilization. The Prometheus Adapter exposes the cluster resource metrics API for horizontal pod autoscaling.

Prometheus Operator

The Prometheus Operator (PO) in the openshift-monitoring project creates, configures, and manages platform Prometheus and Alertmanager instances. It also automatically generates monitoring target configurations based on Kubernetes label queries.

Silences

A silence can be applied to an alert to prevent notifications from being sent when the conditions for an alert are true. You can mute an alert after the initial notification, while you work on resolving the underlying issue.

storage

OKD supports many types of storage, both for on-premise and cloud providers. You can manage container storage for persistent and non-persistent data in an OKD cluster.

Thanos Ruler

The Thanos Ruler is a rule evaluation engine for Prometheus that is deployed as a separate process. In OKD, Thanos Ruler provides rule and alerting evaluation for the monitoring of user-defined projects.

Vector

Vector is a log collector that deploys to each OKD node. It collects log data from each node, transforms the data, and forwards it to configured outputs.

web console

A user interface (UI) to manage OKD.