Gardener provides an integrated logging and monitoring stack for alerting, monitoring and troubleshooting of its managed components by operators or end users. For further information how to make use of it in these roles, refer to the corresponding guides for exploring logs and for monitoring with Grafana.
The components that constitute the logging and monitoring stack are managed by Gardener. By default, it deploys Prometheus, Alertmanager and Grafana into the garden namespace of all seed clusters. If the Logging feature gate in the gardenlet configuration is enabled, it will deploy fluent-bit and Loki in the garden namespace too.
Each shoot namespace hosts managed logging and monitoring components. As part of the shoot reconciliation flow, Gardener deploys a shoot-specific Prometheus, Grafana and, if configured, an Alertmanager into the shoot namespace, next to the other control plane components. If the Logging feature gate is enabled and the shoot purpose is not testing, it deploys a shoot-specific Loki in the shoot namespace too.
The logging and monitoring stack is extensible by configuration. Gardener extensions can take advantage of that and contribute configurations encoded in ConfigMaps for their own, specific dashboards, alerts, log parsers and other supported assets and integrate with it. As with other Gardener resources, they will be continuously reconciled.
This guide is about the roles and extensibility options of the logging and monitoring stack components, and how to integrate extensions with:
The central Prometheus instance in the garden namespace fetches metrics and data from all seed cluster nodes and all seed cluster pods.
It uses the federation concept to allow the shoot-specific instances to scrape only the metrics for the pods of the control plane they are responsible for.
This mechanism allows to scrape the metrics for the nodes/pods once for the whole cluster, and to have them distributed afterwards.
The shoot-specific metrics are then made available to operators and users in the shoot Grafana, using the shoot Prometheus as data source.
Extension controllers might deploy components as part of their reconciliation next to the shoot's control plane. Examples for this would be a cloud-controller-manager or CSI controller deployments. Extensions that want to have their managed control plane components integrated with monitoring can contribute their per-shoot configuration for scraping Prometheus metrics, Alertmanager alerts or Grafana dashboards.
Before deploying the shoot-specific Prometheus instance, Gardener will read all ConfigMaps in the shoot namespace, which are labeled with extensions.gardener.cloud/configuration=monitoring.
Such ConfigMaps may contain four fields in their data:
scrape_config: This field contains Prometheus scrape configuration for the component(s) and metrics that shall be scraped.alerting_rules: This field contains Alertmanager rules for alerts that shall be raised.dashboard_operators: This field contains a Grafana dashboard in JSON that is only relevant for Gardener operators.dashboard_users: This field contains a Grafana dashboard in JSON that is only relevant for Gardener users (shoot owners).
Example: A ControlPlane controller deploying a cloud-controller-manager into the shoot namespace wants to integrate monitoring configuration for scraping metrics, alerting rules and dashboards.
apiVersion: v1
kind: ConfigMap
metadata:
name: extension-controlplane-monitoring-ccm
namespace: shoot--project--name
labels:
extensions.gardener.cloud/configuration: monitoring
data:
scrape_config: |
- job_name: cloud-controller-manager
scheme: https
tls_config:
insecure_skip_verify: true
cert_file: /etc/prometheus/seed/prometheus.crt
key_file: /etc/prometheus/seed/prometheus.key
honor_labels: false
kubernetes_sd_configs:
- role: endpoints
namespaces:
names: [shoot--project--name]
relabel_configs:
- source_labels:
- __meta_kubernetes_service_name
- __meta_kubernetes_endpoint_port_name
action: keep
regex: cloud-controller-manager;metrics
# common metrics
- action: labelmap
regex: __meta_kubernetes_service_label_(.+)
- source_labels: [ __meta_kubernetes_pod_name ]
target_label: pod
metric_relabel_configs:
- process_max_fds
- process_open_fds
alerting_rules: |
cloud-controller-manager.rules.yaml: |
groups:
- name: cloud-controller-manager.rules
rules:
- alert: CloudControllerManagerDown
expr: absent(up{job="cloud-controller-manager"} == 1)
for: 15m
labels:
service: cloud-controller-manager
severity: critical
type: seed
visibility: all
annotations:
description: All infrastructure specific operations cannot be completed (e.g. creating load balancers or persistent volumes).
summary: Cloud controller manager is down.
dashboard_operators:
<some-json-describing-a-grafana-dashboard-for-operators>
dashboard_users:
<some-json-describing-a-grafana-dashboard-for-users>In Kubernetes clusters, container logs are non-persistent and do not survive stopped and destroyed containers. Gardener addresses this problem for the components hosted in a seed cluster, by introducing its own managed logging solution. It is integrated with the Gardener monitoring stack to have all troubleshooting context in one place.
Gardener logging consists of components in three roles - log collectors and forwarders, log persistency and exploration/consumption interfaces. All of them live in the seed clusters in multiple instances:
- Logs are persisted by Loki instances deployed as StatefulSets - one per shoot namespace, if the
Loggingfeature gate is enabled and the shoot purpose is nottesting, and one in thegardennamespace. The shoot instances store logs from the control plane components hosted there. ThegardenLoki instance is responsible for logs from the rest of the seed namespaces -kube-system,gardenextension-*and others. - Fluent-bit DaemonSets deployed on each seed node collect logs from it. A custom plugin takes care to distribute the collected log messages to the Loki instances that they are intended for. This allows to fetch the logs once for the whole cluster, and to distribute them afterwards.
- Grafana is the UI component used to explore monitoring and log data together for easier troubleshooting and in context. Grafana instances are configured to use the coresponding Loki instances, sharing the same namespace, as data providers. There is one Grafana Deployment in the
gardennamespace and two Deployments per shoot namespace (one exposed to the end users and one for the operators).
Logs can be produced from various sources, such as containers or systemd, and in different formats. The fluent-bit design supports configurable data pipeline to address that problem. Gardener provides such configuration for logs produced by all its core managed components as a ConfigMap. Extensions can contribute their own, specific configurations as ConfigMaps too. See for example the logging configuration for the Gardener AWS provider extension. The Gardener reconciliation loop watches such resources and updates the fluent-bit agents dynamically.
To integrate with Gardener logging, extensions can and should specify how fluent-bit will handle the logs produced by the managed components that they contribute to Gardener. Normally, that would require to configure a parser for the specific logging format, if none of the available is applicable, and a filter defining how to apply it. For a complete reference for the configuration options, refer to fluent-bit's documentation.
Note: At the moment only parser and filter configurations are supported.
To contribute its own configuration to the fluent-bit agents data pipelines, an extension must provide it as a ConfigMap labeled extensions.gardener.cloud/configuration=logging and deployed in the seed's garden namespace. Unlike the monitoring stack, where configurations are deployed per shoot, here a single configuration ConfigMap is sufficient and it applies to all fluent-bit agents in the seed. Its data field can have the following properties:
filter-kubernetes.conf- configuration for data pipeline filtersparser.conf- configuration for data pipeline parsers
Note: Take care to provide the correct data pipeline elements in the coresponding data field and not to mix them.
Example: Logging configuration for provider-specific (OpenStack) worker controller deploying a machine-controller-manager component into a shoot namespace that reuses the kubeapiserverParser defined in fluent-bit-configmap.yaml to parse the component logs
apiVersion: v1
kind: ConfigMap
metadata:
name: gardener-extension-provider-openstack-logging-config
namespace: garden
labels:
extensions.gardener.cloud/configuration: logging
data:
filter-kubernetes.conf: |
[FILTER]
Name parser
Match kubernetes.machine-controller-manager*openstack-machine-controller-manager*
Key_Name log
Parser kubeapiserverParser
Reserve_Data TrueFurther details how to define parsers and use them with examples can be found in the following guide.
The three types of Grafana instances found in a seed cluster are configured to expose logs of different origin in their dashboards:
- Garden Grafana dashboards expose logs from non-shoot namespaces of the seed clusters
- Shoot User Grafana dashboards expose a subset of the logs shown to operators
- Kube Apiserver
- Kube Controller Manager
- Kube Scheduler
- Cluster Autoscaler
- Shoot Operator Grafana dashboards expose logs from the shoot cluster namespace where they belong
- All user's dashboards
- Kubernetes Pods
If the type of logs exposed in the Grafana instances needs to be changed, it is necessary to update the coresponding instance dashboard configurations.
- Be careful to match exactly the log names that you need for a particular parser in your filters configuration. The regular expression you will supply will match names in the form
kubernetes.pod_name.<metadata>.container_name. If there are extensions with the same container and pod names, they will all match the same parser in a filter. That may be a desired effect, if they all share the same log format. But it will be a problem if they don't. To solve it, either the pod or container names must be unique, and the regular expression in the filter has to match that unique pattern. A recommended approach is to prefix containers with the extension name and tune the regular expression to match it. For example, usingmyextension-containeras container name, and a regular expressionkubernetes.mypod.*myextension-containerwill guarantee match of the right log name. Make sure that the regular expression does not match more than you expect. For example,kubernetes.systemd.*systemd.*will match bothsystemd-serviceandsystemd-monitor-service. You will want to be as specific as possible. - It's a good idea to put the logging configuration into the Helm chart that also deploys the extension controller, while the monitoring configuration can be part of the Helm chart/deployment routine that deploys the component managed by the controller.