# Getting started with vertical autoscaling for Amazon EMR on EKS
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Use vertical autoscaling for Amazon EMR on EKS when you want automatic tuning of memory and CPU resources to adapt to your Amazon EMR Spark application workload. For more information, see [Using vertical autoscaling with Amazon EMR Spark jobs](jobruns-vas.html).

## Submitting a Spark job with vertical autoscaling
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When you submit a job through the [StartJobRun](https://docs.aws.amazon.com/emr-on-eks/latest/APIReference/API_StartJobRun.html) API, add the following two configurations to the driver for your Spark job to turn on vertical autoscaling:

```
"spark.kubernetes.driver.annotation.emr-containers.amazonaws.com/dynamic.sizing":"true",
"spark.kubernetes.driver.annotation.emr-containers.amazonaws.com/dynamic.sizing.signature":"YOUR_JOB_SIGNATURE"
```

In the code above, the first line enables the vertical autoscaling capability. The next line is a required signature configuration that lets you choose a signature for your job.

For more information on these configurations and acceptable parameter values, see [Configuring vertical autoscaling for Amazon EMR on EKS](jobruns-vas-configure.md). By default, your job submits in the monitoring-only **Off** mode of vertical autoscaling. This monitoring state lets you compute and view resource recommendations without performing autoscaling. For more information, see [Vertical autoscaling modes](jobruns-vas-configure.md#jobruns-vas-parameters-opt-mode).

The following example shows how to complete a sample `start-job-run` command with vertical autoscaling:

```
aws emr-containers start-job-run \
--virtual-cluster-id $VIRTUAL_CLUSTER_ID \
--name $JOB_NAME \
--execution-role-arn $EMR_ROLE_ARN \
--release-label emr-6.10.0-latest \
--job-driver '{
  "sparkSubmitJobDriver": {
     "entryPoint": "local:///usr/lib/spark/examples/src/main/python/pi.py"
   }
 }' \
--configuration-overrides '{
    "applicationConfiguration": [{
        "classification": "spark-defaults",
        "properties": {
          "spark.kubernetes.driver.annotation.emr-containers.amazonaws.com/dynamic.sizing": "true",
          "spark.kubernetes.driver.annotation.emr-containers.amazonaws.com/dynamic.sizing.signature": "test-signature"
        }
    }]
  }'
```

## Verifying the vertical autoscaling functionality
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To verify that vertical autoscaling works correctly for the submitted job, use kubectl to get the `verticalpodautoscaler` custom resource and view your scaling recommendations. For example, the following command queries for recommendations on the example job from the [Submitting a Spark job with vertical autoscaling](#jobruns-vas-spark-submit) section:

```
kubectl get verticalpodautoscalers --all-namespaces \
-l=emr-containers.amazonaws.com/dynamic.sizing.signature=test-signature
```

The output from this query should resemble the following:

```
NAME                                                          MODE   CPU         MEM PROVIDED   AGE
ds-jceyefkxnhrvdzw6djum3naf2abm6o63a6dvjkkedqtkhlrf25eq-vpa   Off    3304504865  True           87m
```

If your output doesn't look similar or contains an error code, see [Troubleshooting Amazon EMR on EKS vertical autoscaling](troubleshooting-vas.md) for steps to help resolve the issue.