Introduction
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 MongoDB With Datadog in Amazon Elastic Kubernetes Service (Amazon EKS). We will cover the following steps:
- Install KubeDB
- Install Datadog
- Deploy MongoDB Sharded Cluster
- Read/Write Sample Data
- Monitor MongoDB 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}'
8e336615-0dbb-4ae8-b72f-2e7ec34c399d
Get License
Go to Appscode License Server to get the license.txt file. For this tutorial, we will use KubeDB Enterprise Edition.
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 https://charts.appscode.com/stable/
$ helm repo update
$ helm search repo appscode/kubedb
NAME CHART VERSION APP VERSION DESCRIPTION
appscode/kubedb v2023.10.9 v2023.10.9 KubeDB by AppsCode - Production ready databases...
appscode/kubedb-autoscaler v0.21.0 v0.21.0 KubeDB Autoscaler by AppsCode - Autoscale KubeD...
appscode/kubedb-catalog v2023.10.9 v2023.10.9 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 v2023.10.9 v2023.10.9 KubeDB Custom Resource Definitions
appscode/kubedb-dashboard v0.12.0 v0.12.0 KubeDB Dashboard by AppsCode
appscode/kubedb-enterprise v0.11.2 v0.11.2 KubeDB Enterprise by AppsCode - Enterprise feat...
appscode/kubedb-grafana-dashboards v2023.10.9 v2023.10.9 A Helm chart for kubedb-grafana-dashboards by A...
appscode/kubedb-metrics v2023.10.9 v2023.10.9 KubeDB State Metrics
appscode/kubedb-one v2023.10.9 v2023.10.9 KubeDB and Stash by AppsCode - Production ready...
appscode/kubedb-ops-manager v0.23.0 v0.23.2 KubeDB Ops Manager by AppsCode - Enterprise fea...
appscode/kubedb-opscenter v2023.10.9 v2023.10.9 KubeDB Opscenter by AppsCode
appscode/kubedb-provisioner v0.36.0 v0.36.2 KubeDB Provisioner by AppsCode - Community feat...
appscode/kubedb-schema-manager v0.12.0 v0.12.0 KubeDB Schema Manager by AppsCode
appscode/kubedb-ui v2023.10.1 0.4.5 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 v0.12.0 v0.12.0 KubeDB Webhook Server by AppsCode
# Install KubeDB Enterprise operator chart
$ helm install kubedb appscode/kubedb \
--version v2023.10.9 \
--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 "app.kubernetes.io/instance=kubedb"
NAMESPACE NAME READY STATUS RESTARTS AGE
kubedb kubedb-kubedb-autoscaler-68978dfc88-ksfg2 1/1 Running 0 2m14s
kubedb kubedb-kubedb-dashboard-644cccc9b8-btmqh 1/1 Running 0 2m14s
kubedb kubedb-kubedb-ops-manager-568fcf7d6-k2bs2 1/1 Running 0 2m14s
kubedb kubedb-kubedb-provisioner-77484995c6-w76mw 1/1 Running 0 2m14s
kubedb kubedb-kubedb-schema-manager-5bd79984cd-t8zll 1/1 Running 0 2m14s
kubedb kubedb-kubedb-webhook-server-64c9987668-p5gwp 1/1 Running 0 2m14s
We can list the CRD Groups that have been registered by the operator by running the following command:
$ kubectl get crd -l app.kubernetes.io/name=kubedb
NAME CREATED AT
elasticsearchautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
elasticsearchdashboards.dashboard.kubedb.com 2023-10-24T05:37:05Z
elasticsearches.kubedb.com 2023-10-24T05:35:47Z
elasticsearchopsrequests.ops.kubedb.com 2023-10-24T05:36:53Z
elasticsearchversions.catalog.kubedb.com 2023-10-24T05:35:06Z
etcds.kubedb.com 2023-10-24T05:35:47Z
etcdversions.catalog.kubedb.com 2023-10-24T05:35:06Z
kafkaopsrequests.ops.kubedb.com 2023-10-24T05:37:25Z
kafkas.kubedb.com 2023-10-24T05:35:48Z
kafkaversions.catalog.kubedb.com 2023-10-24T05:35:06Z
mariadbautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
mariadbdatabases.schema.kubedb.com 2023-10-24T05:36:37Z
mariadbopsrequests.ops.kubedb.com 2023-10-24T05:37:06Z
mariadbs.kubedb.com 2023-10-24T05:35:47Z
mariadbversions.catalog.kubedb.com 2023-10-24T05:35:06Z
memcacheds.kubedb.com 2023-10-24T05:35:47Z
memcachedversions.catalog.kubedb.com 2023-10-24T05:35:06Z
mongodbautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
mongodbdatabases.schema.kubedb.com 2023-10-24T05:36:37Z
mongodbopsrequests.ops.kubedb.com 2023-10-24T05:36:56Z
mongodbs.kubedb.com 2023-10-24T05:35:47Z
mongodbversions.catalog.kubedb.com 2023-10-24T05:35:06Z
mysqlautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
mysqldatabases.schema.kubedb.com 2023-10-24T05:36:36Z
mysqlopsrequests.ops.kubedb.com 2023-10-24T05:37:03Z
mysqls.kubedb.com 2023-10-24T05:35:47Z
mysqlversions.catalog.kubedb.com 2023-10-24T05:35:06Z
perconaxtradbautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
perconaxtradbopsrequests.ops.kubedb.com 2023-10-24T05:37:19Z
perconaxtradbs.kubedb.com 2023-10-24T05:35:47Z
perconaxtradbversions.catalog.kubedb.com 2023-10-24T05:35:07Z
pgbouncers.kubedb.com 2023-10-24T05:35:47Z
pgbouncerversions.catalog.kubedb.com 2023-10-24T05:35:07Z
postgresautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
postgresdatabases.schema.kubedb.com 2023-10-24T05:36:37Z
postgreses.kubedb.com 2023-10-24T05:35:47Z
postgresopsrequests.ops.kubedb.com 2023-10-24T05:37:13Z
postgresversions.catalog.kubedb.com 2023-10-24T05:35:07Z
proxysqlautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
proxysqlopsrequests.ops.kubedb.com 2023-10-24T05:37:16Z
proxysqls.kubedb.com 2023-10-24T05:35:48Z
proxysqlversions.catalog.kubedb.com 2023-10-24T05:35:07Z
publishers.postgres.kubedb.com 2023-10-24T05:37:29Z
redisautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
redises.kubedb.com 2023-10-24T05:35:48Z
redisopsrequests.ops.kubedb.com 2023-10-24T05:37:10Z
redissentinelautoscalers.autoscaling.kubedb.com 2023-10-24T05:35:34Z
redissentinelopsrequests.ops.kubedb.com 2023-10-24T05:37:22Z
redissentinels.kubedb.com 2023-10-24T05:35:48Z
redisversions.catalog.kubedb.com 2023-10-24T05:35:07Z
subscribers.postgres.kubedb.com 2023-10-24T05:37:32Z
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 https://helm.datadoghq.com
$ helm repo update
$ helm install datadog --set datadog.site='datadoghq.com' --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 "app.kubernetes.io/instance=datadog"
NAMESPACE NAME READY STATUS RESTARTS AGE
default datadog-59gdg 3/3 Running 0 2m25s
default datadog-5kt8k 3/3 Running 0 2m25s
default datadog-7j29x 3/3 Running 0 2m27s
default datadog-cluster-agent-6fc8b55877-h8sqg 1/1 Running 0 2m26s
default datadog-jb58m 3/3 Running 0 2m26s
default datadog-m4hks 3/3 Running 0 2m26s
default datadog-vz4bz 3/3 Running 0 2m25s
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.
Install MongoDB Dashboard
To access the MongoDB dashboard, go to Integrations and then install the MongoDB integration from there. This will allow you to monitor your MongoDB databases through Datadog’s dashboard.
Deploy MongoDB Sharded Cluster
Now we are going to deploy MongoDB sharded cluster using KubeDB. You’ll need to deploy your MongoDB cluster with the same namespace default where Datadog is installed.
Here is the yaml of the MongoDB we are going to use:
apiVersion: kubedb.com/v1alpha2
kind: MongoDB
metadata:
name: mongodb-cluster-dd
namespace: default
spec:
version: "4.4.6"
shardTopology:
configServer:
replicas: 3
podTemplate:
metadata:
annotations:
ad.datadoghq.com/mongodb.checks: |
{
"mongo": {
"init_config": {},
"instances": [
{
"hosts": ["%%host%%:%%port%%"],
"username": "datadog",
"password": "admin123",
"database": "admin"
}
]
}
}
storage:
resources:
requests:
storage: 512Mi
storageClassName: "gp2"
mongos:
replicas: 2
podTemplate:
metadata:
annotations:
ad.datadoghq.com/mongodb.checks: |
{
"mongo": {
"init_config": {},
"instances": [
{
"hosts": ["%%host%%:%%port%%"],
"username": "datadog",
"password": "admin123",
"database": "admin"
}
]
}
}
shard:
replicas: 2
podTemplate:
metadata:
annotations:
ad.datadoghq.com/mongodb.checks: |
{
"mongo": {
"init_config": {},
"instances": [
{
"hosts": ["%%host%%:%%port%%"],
"username": "datadog",
"password": "admin123",
"database": "admin"
}
]
}
}
shards: 1
storage:
resources:
requests:
storage: 512Mi
storageClassName: "gp2"
terminationPolicy: WipeOut
Let’s save this yaml configuration into mongodb-cluster-dd.yaml
Then create the above MongoDB CRD
$ kubectl apply -f mongodb-cluster-dd.yaml
mongodb.kubedb.com/mongodb-cluster-dd created
In this yaml,
spec.versionfield specifies the version of MongoDB. Here, we are using MongoDBversion 4.4.6. You can list the KubeDB supported versions of MongoDB by running$ kubectl get mongodbversionscommand.spec.shardTopologyrepresents the topology configuration for sharding.spec.shardTopology.configServerdefines configuration for ConfigServer component of MongoDB.spec.shardTopology.configServer.replicasrepresents number of replicas for configServer replicaset.spec.shardTopology.mongosdefines configuration for Mongos component of MongoDB.spec.shardTopology.mongos.replicasspecifies number of replicas of Mongos instance. Here, Mongos is not deployed as replicaset.spec.shardTopology.<shard/mongos/configServer>.storage.storageClassNameis the name of the StorageClass used to provision PVCs.spec.terminationPolicyfield is Wipeout means that the database will be deleted without restrictions. It can also be “Halt”, “Delete” and “DoNotTerminate”. Learn More about these checkout Termination Policy .podTemplate.metadata.annotationsfield 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 MongoDB user with the username
datadogand the passwordadmin123in the databaseadmin. You can change these fields to your preference.
Once everything handled correctly and the MongoDB object is deployed, you will see that the following are created:
$ kubectl get all -n default -l=app.kubernetes.io/instance=mongodb-cluster-dd
NAME READY STATUS RESTARTS AGE
pod/mongodb-cluster-dd-configsvr-0 1/1 Running 0 5m37s
pod/mongodb-cluster-dd-configsvr-1 1/1 Running 0 4m39s
pod/mongodb-cluster-dd-configsvr-2 1/1 Running 0 4m13s
pod/mongodb-cluster-dd-mongos-0 1/1 Running 0 3m31s
pod/mongodb-cluster-dd-mongos-1 1/1 Running 0 3m23s
pod/mongodb-cluster-dd-shard0-0 1/1 Running 0 5m31s
pod/mongodb-cluster-dd-shard0-1 1/1 Running 0 4m37s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/mongodb-cluster-dd ClusterIP 10.96.122.63 <none> 27017/TCP 5m43s
service/mongodb-cluster-dd-configsvr-pods ClusterIP None <none> 27017/TCP 5m43s
service/mongodb-cluster-dd-mongos-pods ClusterIP None <none> 27017/TCP 5m43s
service/mongodb-cluster-dd-shard0-pods ClusterIP None <none> 27017/TCP 5m43s
NAME READY AGE
statefulset.apps/mongodb-cluster-dd-configsvr 3/3 5m37s
statefulset.apps/mongodb-cluster-dd-mongos 2/2 3m31s
statefulset.apps/mongodb-cluster-dd-shard0 2/2 5m31s
NAME TYPE VERSION AGE
appbinding.appcatalog.appscode.com/mongodb-cluster-dd kubedb.com/mongodb 4.4.6 3m13s
Let’s check if the database is ready to use,
$ kubectl get mongodb -n default mongodb-cluster-dd
NAME VERSION STATUS AGE
mongodb-cluster-dd 4.4.6 Ready 6m7s
We have successfully deployed MongoDB in AWS 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 mongodb-cluster-dd that we have deployed. Let’s check them using the following commands,
$ kubectl get secret -n default -l=app.kubernetes.io/instance=mongodb-cluster-dd
NAME TYPE DATA AGE
mongodb-cluster-dd-auth kubernetes.io/basic-auth 2 6m40s
mongodb-cluster-dd-key Opaque 1 6m40s
$ kubectl get service -n default -l=app.kubernetes.io/instance=mongodb-cluster-dd
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
mongodb-cluster-dd ClusterIP 10.96.122.63 <none> 27017/TCP 6m57s
mongodb-cluster-dd-configsvr-pods ClusterIP None <none> 27017/TCP 6m57s
mongodb-cluster-dd-mongos-pods ClusterIP None <none> 27017/TCP 6m57s
mongodb-cluster-dd-shard0-pods ClusterIP None <none> 27017/TCP 6m57s
Now, we are going to use mongodb-cluster-dd-auth to get the credentials.
$ kubectl get secrets -n default mongodb-cluster-dd-auth -o jsonpath='{.data.username}' | base64 -d
root
$ kubectl get secrets -n default mongodb-cluster-dd-auth -o jsonpath='{.data.password}' | base64 -d
cDHBeFGPA!6X_qHX
Grant Permission to Datadog Agent
In this section, we’ll create a MongoDB user with the username datadog and the password admin123 as defined in mongodb-cluster-dd.yaml. Additionally, we’ll provide the user to have the necessary permissions to scrape metrics.
$ kubectl exec -it -n default mongodb-cluster-dd-shard0-0 -- mongo admin -u $USER -p $PASSWORD
Defaulted container "mongodb" out of: mongodb, copy-config (init)
shard0:PRIMARY> show dbs
admin 0.000GB
config 0.000GB
kubedb-system 0.000GB
local 0.001GB
shard0:PRIMARY> use admin
switched to db admin
shard0:PRIMARY> db.createUser({
... "user": "datadog",
... "pwd": "admin123",
... "roles": [
... { role: "read", db: "admin" },
... { role: "clusterMonitor", db: "admin" },
... { role: "read", db: "local" }
... ]
... })
Successfully added user: {
"user" : "datadog",
"roles" : [
{
"role" : "read",
"db" : "admin"
},
{
"role" : "clusterMonitor",
"db" : "admin"
},
{
"role" : "read",
"db" : "local"
}
]
}
shard0:PRIMARY> exit
bye
Accessing MongoDB Dashboard
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 MongoDB - Overview. This dashboard provide insights into various aspects of your MongoDB database, offering both a high-level summary and more detailed performance metrics for effective monitoring and management. Also, to access MongoDB metrics, navigate to the Metrics section and select Summary in the Datadog UI.
Insert Sample Data
Let’s insert some sample data into our MongoDB database.
$ kubectl exec -it -n default mongodb-cluster-dd-shard0-0 -- mongo admin -u $USER -p $PASSWORD
Defaulted container "mongodb" out of: mongodb, copy-config (init)
shard0:PRIMARY> use admin
switched to db admin
shard0:PRIMARY> db.product.insert({"name":"KubeDB"});
WriteResult({ "nInserted" : 1 })
shard0:PRIMARY> db.product.find().pretty()
{ "_id" : ObjectId("65324225de67c08183bdf7f0"), "name" : "KubeDB" }
shard0:PRIMARY> exit
bye
We’ve successfully inserted some sample data to our database. More information about Run & Manage MongoDB on Kubernetes can be found in MongoDB Kubernetes
Following the insertion of sample data into our MongoDB database, we can monitor any resultant changes in the Datadog UI. Go to the MongoDB - Overview dashboard to observe any updates in performance metrics and insights for our MongoDB database.
Conclusion
In this article, we’ve explored the process of monitoring MongoDB with Datadog in the Amazon Elastic Kubernetes Service (Amazon EKS) using KubeDB. Our aim was to provide insights into efficiently managing and analyzing MongoDB performance within a Kubernetes environment. We’ve explored into the MongoDB configuration, data insertion, and monitoring aspects. This is just the beginning of our journey in exploring the dynamic relationship between MongoDB, 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 MongoDB you can have a look into that playlist below:
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More about MongoDB on Kubernetes
If you have found a bug with KubeDB or want to request for new features, please file an issue .