Monitor KubeDB managed MySQL With Datadog in Google Kubernetes Engine (GKE)


KubeDB is the Kubernetes Native Database Management Solution which simplifies and automates routine database tasks such as Provisioning, Monitoring, Upgrading, Patching, Scaling, Volume Expansion, Backup, Recovery, Failure detection, and Repair for various popular databases on private and public clouds. The databases that KubeDB supports are Redis, PostgreSQL, Kafka, MySQL, MongoDB, MariaDB, Elasticsearch, ProxySQL, Percona XtraDB, Memcached and PgBouncer. You can find the guides to all the supported databases in KubeDB . In this tutorial we will Monitor MySQL With Datadog in Google Kubernetes Engine (GKE) Using KubeDB. We will cover the following steps:

  1. Install KubeDB
  2. Install Datadog
  3. Deploy MySQL Cluster
  4. Read/Write Sample Data
  5. Monitor MySQL with Datadog

Get Cluster ID

We need the cluster ID to get the KubeDB License. To get cluster ID we can run the following command:

$ kubectl get ns kube-system -o jsonpath='{.metadata.uid}'

Get License

Go to Appscode License Server to get the license.txt file. For this tutorial, we will use KubeDB Enterprise Edition.

License Server

Install KubeDB

We will use helm to install KubeDB. Please install Helm if it is not already installed. Now, let’s install KubeDB.

$ helm repo add appscode
$ helm repo update

$ helm search repo appscode/kubedb
NAME                              	CHART VERSION	APP VERSION	DESCRIPTION                                       
appscode/kubedb                   	v2023.08.18  	v2023.08.18	KubeDB by AppsCode - Production ready databases...
appscode/kubedb-autoscaler        	v0.20.0      	v0.20.1    	KubeDB Autoscaler by AppsCode - Autoscale KubeD...
appscode/kubedb-catalog           	v2023.08.18  	v2023.08.18	KubeDB Catalog by AppsCode - Catalog for databa...
appscode/kubedb-community         	v0.24.2      	v0.24.2    	KubeDB Community by AppsCode - Community featur...
appscode/kubedb-crds              	v2023.08.18  	v2023.08.18	KubeDB Custom Resource Definitions                
appscode/kubedb-dashboard         	v0.11.0      	v0.11.0    	KubeDB Dashboard by AppsCode                      
appscode/kubedb-enterprise        	v0.11.2      	v0.11.2    	KubeDB Enterprise by AppsCode - Enterprise feat...
appscode/kubedb-grafana-dashboards	v2023.08.18  	v2023.08.18	A Helm chart for kubedb-grafana-dashboards by A...
appscode/kubedb-metrics           	v2023.08.18  	v2023.08.18	KubeDB State Metrics                              
appscode/kubedb-one               	v2023.08.18  	v2023.08.18	KubeDB and Stash by AppsCode - Production ready...
appscode/kubedb-ops-manager       	v0.22.0      	v0.22.8    	KubeDB Ops Manager by AppsCode - Enterprise fea...
appscode/kubedb-opscenter         	v2023.08.18  	v2023.08.18	KubeDB Opscenter by AppsCode                      
appscode/kubedb-provisioner       	v0.35.0      	v0.35.6    	KubeDB Provisioner by AppsCode - Community feat...
appscode/kubedb-schema-manager    	v0.11.0      	v0.11.0    	KubeDB Schema Manager by AppsCode                 
appscode/kubedb-ui                	v2023.03.23  	0.4.3      	A Helm chart for Kubernetes                       
appscode/kubedb-ui-server         	v2021.12.21  	v2021.12.21	A Helm chart for kubedb-ui-server by AppsCode     
appscode/kubedb-webhook-server    	v0.11.0      	v0.11.1    	KubeDB Webhook Server by AppsCode   

# Install KubeDB Enterprise operator chart
$ helm install kubedb appscode/kubedb \
  --version v2023.08.18 \
  --namespace kubedb --create-namespace \
  --set kubedb-provisioner.enabled=true \
  --set kubedb-ops-manager.enabled=true \
  --set kubedb-autoscaler.enabled=true \
  --set kubedb-dashboard.enabled=true \
  --set kubedb-schema-manager.enabled=true \
  --set-file global.license=/path/to/the/license.txt

Let’s verify the installation:

$ watch kubectl get pods --all-namespaces -l ""

NAMESPACE   NAME                                            READY   STATUS    RESTARTS   AGE
kubedb      kubedb-kubedb-autoscaler-57b9d979ff-grz6d       1/1     Running   0          71s
kubedb      kubedb-kubedb-dashboard-567859b978-8jc45        1/1     Running   0          71s
kubedb      kubedb-kubedb-ops-manager-954c4c6c8-s4s5q       1/1     Running   0          70s
kubedb      kubedb-kubedb-provisioner-56bdb59696-bkn7w      1/1     Running   0          71s
kubedb      kubedb-kubedb-schema-manager-658b6db6dc-2pcq6   1/1     Running   0          71s
kubedb      kubedb-kubedb-webhook-server-7f98695cb5-s49wq   1/1     Running   0          71s

We can list the CRD Groups that have been registered by the operator by running the following command:

$ kubectl get crd -l
NAME                                              CREATED AT   2023-10-06T04:44:17Z      2023-10-06T04:44:18Z                        2023-10-06T04:44:19Z           2023-10-06T04:44:25Z          2023-10-06T04:41:41Z                                  2023-10-06T04:44:25Z                   2023-10-06T04:41:41Z                                 2023-10-06T04:44:52Z                  2023-10-06T04:41:42Z         2023-10-06T04:44:18Z                2023-10-06T04:44:26Z                 2023-10-06T04:45:01Z                               2023-10-06T04:44:26Z                2023-10-06T04:41:42Z                             2023-10-06T04:44:26Z              2023-10-06T04:41:42Z         2023-10-06T04:44:18Z                2023-10-06T04:44:20Z                 2023-10-06T04:44:29Z                               2023-10-06T04:44:21Z                2023-10-06T04:41:42Z           2023-10-06T04:44:19Z                  2023-10-06T04:44:17Z                   2023-10-06T04:44:58Z                                 2023-10-06T04:44:18Z                  2023-10-06T04:41:43Z   2023-10-06T04:44:19Z           2023-10-06T04:45:15Z                         2023-10-06T04:44:46Z          2023-10-06T04:41:43Z                             2023-10-06T04:44:47Z              2023-10-06T04:41:44Z        2023-10-06T04:44:19Z               2023-10-06T04:44:24Z                             2023-10-06T04:44:25Z                2023-10-06T04:45:09Z               2023-10-06T04:41:44Z        2023-10-06T04:44:20Z                2023-10-06T04:45:12Z                              2023-10-06T04:44:50Z               2023-10-06T04:41:44Z                    2023-10-06T04:45:26Z           2023-10-06T04:44:21Z                                2023-10-06T04:44:50Z                   2023-10-06T04:45:05Z   2023-10-06T04:44:21Z           2023-10-06T04:45:19Z                         2023-10-06T04:44:51Z                  2023-10-06T04:41:45Z                   2023-10-06T04:45:29Z

Install Datadog

To install Datadog, we recommend using Helm. Below are the steps for the installation. For more installation options and details, visit Datadog’s official documentation .

$ helm repo add datadog
$ helm repo update
$ helm install datadog --set'' --set datadog.apiKey=<YOUR DATADOG API KEY> --set datadog.apm.enabled=true datadog/datadog

Let’s verify the installation:

$ kubectl get pods --all-namespaces -l ""

NAMESPACE   NAME                                     READY   STATUS    RESTARTS   AGE
default     datadog-bkbkg                            3/3     Running   0          87s
default     datadog-cluster-agent-5c9946d8d7-8kfpp   1/1     Running   0          86s
default     datadog-cx6c8                            3/3     Running   0          86s
default     datadog-hf5s6                            3/3     Running   0          86s
default     datadog-nw5vq                            3/3     Running   0          86s
default     datadog-r6pjd                            3/3     Running   0          86s
default     datadog-w8bjp                            3/3     Running   0          86s

Datadog Events

To view events from your Kubernetes cluster, go to Datadog’s Event Explorer . You’ll find valuable insights and information about your Kubernetes environment.

Datadog Events

Install MySQL Dashboard

To access the MySQL dashboard, go to Integrations and then install the MySQL integration from there. This will allow you to monitor your MySQL databases through Datadog’s dashboard.


Deploy MySQL Cluster

Now we are going to deploy MySQL cluster using KubeDB. You’ll need to deploy your MySQL cluster with the same namespace default where Datadog is installed.

Here is the yaml of the MySQL we are going to use:

kind: MySQL
  name: mysql-cluster-dd
  namespace: default
  version: "8.0.32"
  replicas: 3
    mode: GroupReplication
  storageType: Durable
    storageClassName: "standard"
      - ReadWriteOnce
        storage: 1Gi
  terminationPolicy: WipeOut
      annotations: |
            "mysql": {
              "instances": [
                  "server": "%%host%%",
                  "username": "datadog",
                  "password": "admin123"
          }          '[{"source": "mysql", "service": "mysql"}]'

Let’s save this yaml configuration into mysql-cluster-dd.yaml Then create the above MySQL CRD

$ kubectl apply -f mysql-cluster-dd.yaml created

In this yaml,

  • spec.version field specifies the version of MySQL. Here, we are using MySQL version 8.0.32. You can list the KubeDB supported versions of MySQL by running $ kubectl get mysqlversions command.
  • Another field to notice is the spec.storageType field. This can be Durable or Ephemeral depending on the requirements of the database to be persistent or not.
  • spec.terminationPolicy field is Wipeout means that the database will be deleted without restrictions. It can also be “Halt”, “Delete” and “DoNotTerminate”. Learn more about Termination Policy .
  • spec.podTemplate.metadata.annotations field specifes Autodiscovery Integrations Templates as pod annotations on your application container. Learn more about Autodiscovery Template Variables .

Note: To align with the configurations specified in our annotations, it is essential to create a MySQL user with the username datadog and the password admin123. You can change these fields to your preference.

Once everything handled correctly and the MySQL object is deployed, you will see that the following are created:

$ kubectl get all -n default

NAME                                         READY   STATUS    RESTARTS   AGE
pod/mysql-cluster-dd-0                       2/2     Running   0          3m
pod/mysql-cluster-dd-1                       2/2     Running   0          2m7s
pod/mysql-cluster-dd-2                       2/2     Running   0          2m11s

NAME                                                 TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)             AGE
service/mysql-cluster-dd                             ClusterIP   <none>        3306/TCP            3m
service/mysql-cluster-dd-pods                        ClusterIP   None           <none>        3306/TCP            2m7s
service/mysql-cluster-dd-standby                     ClusterIP    <none>        3306/TCP            2m11s

NAME                                READY   AGE
statefulset.apps/mysql-cluster-dd   3/3     3m

NAME                                                  TYPE               VERSION   AGE   8.0.32    3m

Let’s check if the database is ready to use,

$ kubectl get mysql -n default mysql-cluster-dd
NAME               VERSION   STATUS   AGE
mysql-cluster-dd   8.0.32    Ready    5m

We have successfully deployed MySQL in GKE with Datadog. Now we can exec into the container to use the database.

Accessing Database Through CLI

To access the database through CLI, we have to get the credentials to access. KubeDB will create Secret and Service for the database mysql-cluster-dd that we have deployed. Let’s check them using the following commands,

$ kubectl get secret -n default
NAME                    TYPE                       DATA   AGE
mysql-cluster-dd-auth   2      4m

$ kubectl get service -n default
NAME                       TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)    AGE
mysql-cluster-dd           ClusterIP   <none>        3306/TCP   4m
mysql-cluster-dd-pods      ClusterIP   None           <none>        3306/TCP   4m
mysql-cluster-dd-standby   ClusterIP    <none>        3306/TCP   4m

Now, we are going to use mysql-cluster-dd-auth to get the credentials.

$ kubectl get secrets -n default mysql-cluster-dd-auth -o jsonpath='{.data.username}' | base64 -d

$ kubectl get secrets -n default mysql-cluster-dd-auth -o jsonpath='{.data.password}' | base64 -d

Grant Permission to Datadog Agent

In this section, we’ll create a MySQL user with the username datadog and the password admin123 as defined in mysql-cluster-dd.yaml. Additionally, we’ll provide the user to have the necessary permissions to scrape metrics.

$ kubectl exec -it mysql-cluster-dd-0 -n default -c mysql -- bash
bash-4.4# mysql --user=root --password='EqsDcS6Meym91PpW'

Welcome to the MySQL monitor.  Commands end with ; or \g.
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql> CREATE USER 'datadog'@'%' IDENTIFIED BY 'admin123';
Query OK, 0 rows affected (0.03 sec)

mysql> GRANT REPLICATION CLIENT ON *.* TO 'datadog'@'%';
Query OK, 0 rows affected (0.01 sec)

mysql> GRANT PROCESS ON *.* TO 'datadog'@'%';
Query OK, 0 rows affected (0.00 sec)

mysql> GRANT SELECT ON performance_schema.* TO 'datadog'@'%';
Query OK, 0 rows affected (0.01 sec)

mysql> exit

Accessing MySQL Dashboards

To access the monitoring dashboards in the Datadog UI, navigate to the Dashboards section in your Datadog account’s main menu. From the dropdown menu, select Dashboards List, and you’ll find MySQL - Overview and MySQL. These dashboards provide insights into various aspects of your MySQL database, offering both a high-level summary and more detailed performance metrics for effective monitoring and management. Also, to access MySQL metrics, navigate to the Metrics section and select Summary in the Datadog UI.

Dashboards List

MySQL Overview


MySQL Metrics

Insert Sample Data

Let’s insert some sample data into our MySQL database.

$ kubectl exec -it mysql-cluster-dd-0 -n default -c mysql -- bash
bash-4.4# mysql --user=root --password='EqsDcS6Meym91PpW'

Welcome to the MySQL monitor.  Commands end with ; or \g.
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

Query OK, 1 row affected (0.03 sec)

Query OK, 0 rows affected, 1 warning (0.04 sec)

mysql> INSERT INTO Music.Artist (Name, Song) VALUES ("John Denver", "Country Roads");
Query OK, 1 row affected (0.01 sec)

mysql> SELECT * FROM Music.Artist;
| id | Name        | Song          |
|  1 | John Denver | Country Roads |
1 row in set (0.00 sec)

mysql> exit

We’ve successfully inserted some sample data to our database. More information about Run & Manage MySQL on Kubernetes can be found in MySQL Kubernetes

Following the insertion of sample data into our MySQL database, we can monitor any resultant changes in the Datadog UI. Go to the MySQL and MySQL - Overview dashboards to observe any updates in performance metrics and insights for our MySQL database.

MySQL Overview After

MySQL After


In this article, we’ve explored the process of monitoring MySQL with Datadog in the Google Kubernetes Engine (GKE) using KubeDB. Our aim was to provide insights into efficiently managing and analyzing MySQL performance within a Kubernetes environment. We’ve explored into the MySQL configuration, data insertion, and monitoring aspects. This is just the beginning of our journey in exploring the dynamic relationship between MySQL, Datadog, and Kubernetes. We have more articles and resources in the pipeline, all geared toward enhancing your understanding of these technologies and their effective integration. To stay updated and informed, be sure to follow our website for upcoming articles and insights.

If you want to learn more about Production-Grade MySQL you can have a look into that playlist below:


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More about MySQL on Kubernetes

If you have found a bug with KubeDB or want to request for new features, please file an issue .


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