Step 4: Configure the Collector
Configuring the collector on Amazon EKS
To start, download the example values.yaml file for the Helm chart:
helm show values pganalyze/pganalyze-collector > values.yaml
Update the serviceAccount section in the values.yaml file to use the role just created in the previous step. For the name, use "pganalyze-service-account" as specified in the Pod Identity association (for Pod Identity) or the assume role policy (for IRSA):
serviceAccount:
# -- Specifies whether a service account should be created
create: true
# -- Annotations to add to the service account
annotations: {}
# Update above annotation if you're using IRSA
# annotations:
# eks.amazonaws.com/role-arn: "arn:aws:iam::<aws-account-id>:role/pganalyzeServiceAccountRole"
# -- The name of the service account to use.
# If not set and create is true, a name is generated using the fullname template
name: "pganalyze-service-account"
Next, update the extraEnv
section in the values.yaml file with the following.
This example uses extraEnv
field for a temporary demonstration. For production
environments or any sensitive data handling, follow your organization's security
best practices and use Kubernetes secrets.
extraEnv:
PGA_API_KEY: your-organization-api-key
DB_HOST: your_database_host
DB_NAME: your_database_name
DB_USERNAME: your_monitoring_user
DB_PASSWORD: your_monitoring_user_password
DB_SSLROOTCERT: rds-ca-global
DB_SSLMODE: verify-full
Fill in the values step-by-step:
- The
PGA_API_KEY
can be found on the pganalyze Settings page for your organization under the API keys tab - The
DB_HOST
is the hostname / endpoint of your RDS instance (for Amazon Aurora you can use the cluster endpoint in many cases, see for details below) - The
DB_NAME
is the database name on the Postgres instance you want to monitor - The
DB_USERNAME
andDB_PASSWORD
should be the monitoring user we created in Step 2 - The
DB_SSLROOTCERT
andDB_SSLMODE
is the recommended SSL connection configuration that you can usually keep as specified above
When using Kubernetes secrets, it's easier to use the INI
file style for the
config. You can find the example of this in the Multiple DB Instances example
above, where it is used as the value of the CONFIG_CONTENTS
environment variable.
For instance, you can create a secret called pganalyze-secrets
and add a key
pganalyze-collector.conf
, setting the INI
collector config as its value.
apiVersion: v1
kind: Secret
metadata:
name: pganalyze-secrets
data:
pganalyze-collector.conf: |
[pganalyze]
api_key = your_api_key
[instance1]
db_host = your_database_host
db_name = your_database_name
...
Then, create a secret volume config-volume
and mount it to the /config
path
so that the config file will be created in the default config file location:
# -- List of volumes to attach to the pod
volumes:
- name: scratch
emptyDir: {}
- name: config-volume
secret:
secretName: pganalyze-secrets
# -- List of volume mounts to attach to the container
volumeMounts:
- mountPath: /tmp
name: scratch
subPath: tmp
- mountPath: /state
name: scratch
subPath: state
- mountPath: /config
name: config-volume
With this, the config-volume
volume will contain a pganalyze-collector.conf
file, with its content being the value of the secret, mounted at /config/pganalyze-collector.conf
.
Note: The pganalyze collector allows for more optional settings (e.g. AWS access keys, multiple database names)
Handling Amazon Aurora clusters vs instances
In the case of Amazon Aurora, the collector automatically resolves cluster
endpoints to the underlying writer instance.
DB_HOST: mydbcluster.cluster-123456789012.us-east-1.rds.amazonaws.com
This will only monitor the writer instance. If you also want to monitor a reader instance,
you'll need to use the Multiple Instances method above and specify the reader instance as a
second instance within the CONFIG_CONTENTS
environment variable.
[pganalyze]
api_key = 'your_pga_organization_api_key'
[writer_instance]
db_host = mydbcluster.cluster-123456789012.us-east-1.rds.amazonaws.com
...
[reader_instance]
db_host = mydbcluster.cluster-ro-123456789012.us-east-1.rds.amazonaws.com
...
Alternatively, you can install a Helm chart with the separate release name to
monitor a reader instance.
Use the cluster-ro
endpoint as the DB_HOST
of the environment variables:
DB_HOST: mydbcluster.cluster-ro-123456789012.us-east-1.rds.amazonaws.com
If you have multiple readers you want to monitor, you either need to specify
using CONFIG_CONTENTS
environment variable, or install one pganalyze collector
Helm chart for each instance.
Install a Helm chart
We can now install a Helm chart to your EKS cluster. First, add a pganalyze repo:
helm repo add pganalyze https://charts.pganalyze.com/
Then, install a chart, using the values.yaml file created earlier:
helm upgrade --install my-collector pganalyze/pganalyze-collector --values=values.yaml
Adjust the namespace if needed. You can run the same command when you make a change to the values.yaml file.
To verify that the install went well, check the deployment:
$ kubectl get deployment
NAME READY UP-TO-DATE AVAILABLE AGE
my-collector-pganalyze-collector 1/1 1 1 1m10s
The deployment will create one pod for the collector. Check the pod name and obtain the logs to make sure that the collector is running successfully:
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
my-collector-pganalyze-collector-7d599b49c8-dgxzk 1/1 Running 0 1m10s
$ kubectl logs my-collector-pganalyze-collector-7d599b49c8-dgxzk
I [default] Submitted compact snapshots successfully: 6 activity, 2 logs
The Submitted compact snapshots successfully
message indicates that you have
configured the collector correctly.
Your setup is complete. The dashboard will start showing data within 15 minutes.
Once you've confirmed the install is successful and you're receiving query data in pganalyze, we recommend setting up Log Insights as a follow-up step, to automatically track log events in your database.
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