Grafana packaged by Bitnami¶

Grafana is an open source metric analytics and visualization suite for visualizing time series data that supports various types of data sources.

Overview of Grafana

Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

TL;DR¶

使用加速地址添加仓库:

helm repo add bitnami "https://helm-charts.itboon.top/bitnami" --force-update
helm update bitnami

helm install my-release bitnami/grafana

Introduction¶

This chart bootstraps a grafana deployment on a Kubernetes cluster using the Helm package manager.

Bitnami charts can be used with Kubeapps for deployment and management of Helm Charts in clusters.

Looking to use Grafana in production? Try VMware Application Catalog, the enterprise edition of Bitnami Application Catalog.

Prerequisites¶

• Kubernetes 1.19+
• Helm 3.2.0+
• PV provisioner support in the underlying infrastructure
• ReadWriteMany volumes for deployment scaling

Installing the Chart¶

To install the chart with the release name my-release:

helm install my-release bitnami/grafana

These commands deploy grafana on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation.

Tip: List all releases using helm list

Uninstalling the Chart¶

To uninstall/delete the my-release deployment:

helm delete my-release

The command removes all the Kubernetes components associated with the chart and deletes the release. Use the option --purge to delete all persistent volumes too.

Differences between the Bitnami Grafana chart and the Bitnami Grafana Operator chart¶

In the Bitnami catalog we offer both the bitnami/grafana and bitnami/grafana-operator charts. Each solution covers different needs and use cases.

The bitnami/grafana chart deploys a single Grafana installation (with grafana-image-renderer) using a Kubernetes Deployment object (together with Services, PVCs, ConfigMaps, etc.). The figure below shows the deployed objects in the cluster after executing helm install:

                    +--------------+             +-----+
                    |              |             |     |
 Service & Ingress  |    Grafana   +<------------+ PVC |
<-------------------+              |             |     |
                    |  Deployment  |             +-----+
                    |              |
                    +-----------+--+
                                ^                +------------+
                                |                |            |
                                +----------------+ Configmaps |
                                                 |   Secrets  |
                                                 |            |
                                                 +------------+

Its lifecycle is managed using Helm and, at the Grafana container level, the following operations are automated: persistence management, configuration based on environment variables and plugin initialization. The chart also allows deploying dashboards and data sources using ConfigMaps. The Deployments do not require any ServiceAccounts with special RBAC privileges so this solution would fit better in more restricted Kubernetes installations.

The bitnami/grafana-operator chart deploys a Grafana Operator installation using a Kubernetes Deployment. The figure below shows the Grafana operator deployment after executing helm install:

+--------------------+
|                    |      +---------------+
|  Grafana Operator  |      |               |
|                    |      |     RBAC      |
|    Deployment      |      |   Privileges  |
|                    |      |               |
+-------+------------+      +-------+-------+
        ^                           |
        |   +-----------------+     |
        +---+ Service Account +<----+
            +-----------------+

The operator will extend the Kubernetes API with the following objects: Grafana, GrafanaDashboards and GrafanaDataSources. From that moment, the user will be able to deploy objects of these kinds and the previously deployed Operator will take care of deploying all the required Deployments, ConfigMaps and Services for running a Grafana instance. Its lifecycle is managed using kubectl on the Grafana, GrafanaDashboards and GrafanaDataSource objects. The following figure shows the deployed objects after deploying a Grafana object using kubectl:

+--------------------+
|                    |      +---------------+
|  Grafana Operator  |      |               |
|                    |      |     RBAC      |
|    Deployment      |      |   Privileges  |
|                    |      |               |
+--+----+------------+      +-------+-------+
   |    ^                           |
   |    |   +-----------------+     |
   |    +---+ Service Account +<----+
   |        +-----------------+
   |
   |
   |
   |
   |                                                   Grafana
   |                     +---------------------------------------------------------------------------+
   |                     |                                                                           |
   |                     |                          +--------------+             +-----+             |
   |                     |                          |              |             |     |             |
   +-------------------->+       Service & Ingress  |    Grafana   +<------------+ PVC |             |
                         |      <-------------------+              |             |     |             |
                         |                          |  Deployment  |             +-----+             |
                         |                          |              |                                 |
                         |                          +-----------+--+                                 |
                         |                                      ^                +------------+      |
                         |                                      |                |            |      |
                         |                                      +----------------+ Configmaps |      |
                         |                                                       |   Secrets  |      |
                         |                                                       |            |      |
                         |                                                       +------------+      |
                         |                                                                           |
                         +---------------------------------------------------------------------------+

This solution allows to easily deploy multiple Grafana instances compared to the bitnami/grafana chart. As the operator automatically deploys Grafana installations, the Grafana Operator pods will require a ServiceAccount with privileges to create and destroy mulitple Kubernetes objects. This may be problematic for Kubernetes clusters with strict role-based access policies.

Parameters¶

Global parameters¶

Common parameters¶

Grafana parameters¶

Grafana Deployment parameters¶

Persistence parameters¶

RBAC parameters¶

Traffic exposure parameters¶

Metrics parameters¶

Grafana Image Renderer parameters¶

Volume permissions init Container Parameters¶

Diagnostic Mode Parameters¶

Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,

helm install my-release \
  --set admin.user=admin-user bitnami/grafana

The above command sets the Grafana admin user to admin-user.

NOTE: Once this chart is deployed, it is not possible to change the application's access credentials, such as usernames or passwords, using Helm. To change these application credentials after deployment, delete any persistent volumes (PVs) used by the chart and re-deploy it, or use the application's built-in administrative tools if available.

Alternatively, a YAML file that specifies the values for the parameters can be provided while installing the chart. For example,

helm install my-release -f values.yaml bitnami/grafana

Tip: You can use the default values.yaml

Configuration and installation details¶

Rolling VS Immutable tags¶

It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.

Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.

Using custom configuration¶

Grafana supports multiples configuration files. Using kubernetes you can mount a file using a ConfigMap or a Secret. For example, to mount a custom grafana.ini file or custom.ini file you can create a ConfigMap like the following:

apiVersion: v1
kind: ConfigMap
metadata:
  name: myconfig
data:
  grafana.ini: |-
    # Raw text of the file

And now you need to pass the ConfigMap name, to the corresponding parameters: config.useGrafanaIniFile=true and config.grafanaIniConfigMap=myconfig.

To provide dashboards on deployment time, Grafana needs a dashboards provider and the dashboards themselves. A default provider is created if enabled, or you can mount your own provider using a ConfigMap, but have in mind that the path to the dashboard folder must be /opt/bitnami/grafana/dashboards.

1. To create a dashboard, it is needed to have a datasource for it. The datasources must be created mounting a secret with all the datasource files in it. In this case, it is not a ConfigMap because the datasource could contain sensitive information.
2. To load the dashboards themselves you need to create a ConfigMap for each one containing the json file that defines the dashboard and set the array with the ConfigMap names into the dashboardsConfigMaps parameter. Note the difference between the datasources and the dashboards creation. For the datasources we can use just one secret with all of the files, while for the dashboards we need one ConfigMap per file.

For example, create the dashboard ConfigMap(s) and datasource Secret as described below:

kubectl create secret generic datasource-secret --from-file=datasource-secret.yaml
kubectl create configmap my-dashboard-1 --from-file=my-dashboard-1.json
kubectl create configmap my-dashboard-2 --from-file=my-dashboard-2.json

Note: the commands above assume you had previously exported your dashboards in the JSON files: my-dashboard-1.json and my-dashboard-2.json Note: the commands above assume you had previously created a datasource config file datasource-secret.yaml. Find an example at https://grafana.com/docs/grafana/latest/administration/provisioning/#example-datasource-config-file

Once you have them, use the following parameters to deploy Grafana with 2 custom dashboards:

dashboardsProvider.enabled=true
datasources.secretName=datasource-secret
dashboardsConfigMaps[0].configMapName=my-dashboard-1
dashboardsConfigMaps[0].fileName=my-dashboard-1.json
dashboardsConfigMaps[1].configMapName=my-dashboard-2
dashboardsConfigMaps[1].fileName=my-dashboard-2.json

More info at Grafana documentation.

LDAP configuration¶

To enable LDAP authentication it is necessary to provide a ConfigMap with the Grafana LDAP configuration file. For instance:

configmap.yaml:

apiVersion: v1
kind: ConfigMap
metadata:
  name: ldap-config
data:
  ldap.toml: |-
      [[servers]]
      # Ldap server host (specify multiple hosts space separated)
      host = "ldap"
      # Default port is 389 or 636 if use_ssl = true
      port = 389
      # Set to true if ldap server supports TLS
      use_ssl = false
      # Set to true if connect ldap server with STARTTLS pattern (create connection in insecure, then upgrade to secure connection with TLS)
      start_tls = false
      # set to true if you want to skip ssl cert validation
      ssl_skip_verify = false
      # set to the path to your root CA certificate or leave unset to use system defaults
      # root_ca_cert = "/path/to/certificate.crt"
      # Authentication against LDAP servers requiring client certificates
      # client_cert = "/path/to/client.crt"
      # client_key = "/path/to/client.key"

      # Search user bind dn
      bind_dn = "cn=admin,dc=example,dc=org"
      # Search user bind password
      # If the password contains # or ; you have to wrap it with triple quotes. Ex """#password;"""
      bind_password = 'admin'

      # User search filter, for example "(cn=%s)" or "(sAMAccountName=%s)" or "(uid=%s)"
      # Allow login from email or username, example "(|(sAMAccountName=%s)(userPrincipalName=%s))"
      search_filter = "(uid=%s)"

      # An array of base dns to search through
      search_base_dns = ["ou=People,dc=support,dc=example,dc=org"]

      # group_search_filter = "(&(objectClass=posixGroup)(memberUid=%s))"
      # group_search_filter_user_attribute = "distinguishedName"
      # group_search_base_dns = ["ou=groups,dc=grafana,dc=org"]

      # Specify names of the ldap attributes your ldap uses
      [servers.attributes]
      name = "givenName"
      surname = "sn"
      username = "cn"
      member_of = "memberOf"
      email =  "email"

Create the ConfigMap into the cluster and deploy the Grafana Helm Chart using the existing ConfigMap and the following parameters:

ldap.enabled=true
ldap.configMapName=ldap-config
ldap.allowSignUp=true

Supporting HA (High Availability)¶

To support HA Grafana just need an external database where store dashboards, users and other persistent data. To configure the external database provide a configuration file containing the database section

More information about Grafana HA here

Setting Pod's affinity¶

This chart allows you to set your custom affinity using the affinity parameter. Find more information about Pod's affinity in the kubernetes documentation.

As an alternative, you can use of the preset configurations for pod affinity, pod anti-affinity, and node affinity available at the bitnami/common chart. To do so, set the podAffinityPreset, podAntiAffinityPreset, or nodeAffinityPreset parameters.

Persistence¶

The Bitnami Grafana image stores the Grafana data and configurations at the /opt/bitnami/grafana/data path of the container.

Persistent Volume Claims are used to keep the data across deployments. This is known to work in GCE, AWS, and minikube. See the Parameters section to configure the PVC or to disable persistence.

Troubleshooting¶

Find more information about how to deal with common errors related to Bitnami's Helm charts in this troubleshooting guide.

Upgrading¶

To 8.0.0¶

This major release only bumps the Grafana version to 9.x. No major issues are expected during the upgrade. See the upstream changelog https://grafana.com/docs/grafana/latest/release-notes/release-notes-9-0-0/ for more info about the changes included in this new major version of the application

To 7.0.0¶

This major release renames several values in this chart and adds missing features, in order to be inline with the rest of assets in the Bitnami charts repository.

Since the volume access mode when persistence is enabled is ReadWriteOnce in order to upgrade the deployment you will need to either use the Recreate strategy or delete the old deployment.

kubectl delete deployment <deployment-name>
helm upgrade <release-name> bitnami/grafana

To 4.1.0¶

This version also introduces bitnami/common, a library chart as a dependency. More documentation about this new utility could be found here. Please, make sure that you have updated the chart dependencies before executing any upgrade.

To 4.0.0¶

On November 13, 2020, Helm v2 support was formally finished, this major version is the result of the required changes applied to the Helm Chart to be able to incorporate the different features added in Helm v3 and to be consistent with the Helm project itself regarding the Helm v2 EOL.

What changes were introduced in this major version?¶

• Previous versions of this Helm Chart use apiVersion: v1 (installable by both Helm 2 and 3), this Helm Chart was updated to apiVersion: v2 (installable by Helm 3 only). Here you can find more information about the apiVersion field.
• The different fields present in the Chart.yaml file has been ordered alphabetically in a homogeneous way for all the Bitnami Helm Charts

Considerations when upgrading to this version¶

• If you want to upgrade to this version from a previous one installed with Helm v3, you shouldn't face any issues
• If you want to upgrade to this version using Helm v2, this scenario is not supported as this version doesn't support Helm v2 anymore
• If you installed the previous version with Helm v2 and wants to upgrade to this version with Helm v3, please refer to the official Helm documentation about migrating from Helm v2 to v3

Useful links¶

• https://docs.bitnami.com/tutorials/resolve-helm2-helm3-post-migration-issues/
• https://helm.sh/docs/topics/v2_v3_migration/
• https://helm.sh/blog/migrate-from-helm-v2-to-helm-v3/

To 3.0.0¶

Deployment label selector is immutable after it gets created, so you cannot "upgrade".

In https://github.com/bitnami/charts/pull/2773 the deployment label selectors of the resources were updated to add the component name. Resulting in compatibility breakage.

In order to "upgrade" from a previous version, you will need to uninstall the existing chart manually.

This major version signifies this change.

License¶

Copyright © 2023 VMware, Inc.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.