Does this tool connect to my GCP account?

No. This tool runs entirely in your browser and generates configuration JSON that you can copy and paste into your infrastructure-as-code templates, CLI commands, or cloud console. It never connects to any cloud account or sends data externally.

Are the generated configurations production-ready?

The tool produces syntactically valid configurations based on current GCP service specifications. Always review generated configs against your organization security policies and test in a non-production environment before deploying.

GCP Dataproc Serverless Batch Builder

MonitoringGCP

Build Dataproc Serverless Spark batch configurations with runtime settings and dynamic allocation.

Dataproc Serverless Configuration

Build Dataproc Serverless Spark batch configurations with runtime settings, dynamic allocation, networking, and metastore integration.

Required Fields

nameruntimeConfig.versionenvironmentConfig.executionConfig.serviceAccount

{
  "name": "projects/my-project/locations/us-central1/batches/etl-daily-20260314",
  "sparkBatch": {
    "mainJarFileUri": "gs://my-project-jars/etl-pipeline-2.0.jar",
    "mainClass": "com.example.etl.DailyPipeline",
    "args": [
      "--input=gs://my-project-data/raw/2026-03-14/",
      "--output=gs://my-project-data/processed/2026-03-14/",
      "--date=2026-03-14"
    ],
    "jarFileUris": [
      "gs://my-project-jars/connectors/spark-bigquery-latest.jar"
    ],
    "fileUris": [
      "gs://my-project-config/etl-config.properties"
    ],
    "archiveUris": []
  },
  "pysparkBatch": null,
  "runtimeConfig": {
    "version": "2.2",
    "containerImage": "us-central1-docker.pkg.dev/my-project/spark/custom-spark:v2.0",
    "properties": {
      "spark.executor.memory": "8g",
      "spark.executor.cores": "4",
      "spark.driver.memory": "4g",
      "spark.sql.adaptive.enabled": "true",
      "spark.dynamicAllocation.enabled": "true",
      "spark.dynamicAllocation.minExecutors": "2",
      "spark.dynamicAllocation.maxExecutors": "20"
    },
    "cohort": ""
  },
  "environmentConfig": {
    "executionConfig": {
      "serviceAccount": "dataproc-sa@my-project.iam.gserviceaccount.com",
      "networkUri": "projects/my-project/global/networks/prod-vpc",
      "subnetworkUri": "projects/my-project/regions/us-central1/subnetworks/dataproc-subnet",
      "kmsKey": "projects/my-project/locations/us-central1/keyRings/dataproc-ring/cryptoKeys/dataproc-key",
      "ttl": "14400s",
      "stagingBucket": "my-project-dataproc-staging"
    },
    "peripheralsConfig": {
      "metastoreService": "projects/my-project/locations/us-central1/services/hive-metastore",
      "sparkHistoryServerConfig": {
        "dataprocCluster": "projects/my-project/regions/us-central1/clusters/history-cluster"
      }
    }
  },
  "labels": {
    "pipeline": "daily-etl",
    "team": "data-engineering"
  }
}

Generated Output

Output will appear here...

About This Tool

Build Dataproc Serverless Spark batch configurations with runtime settings and dynamic allocation. This tool helps GCP engineers generate valid configurations quickly without consulting documentation, reducing errors and accelerating infrastructure deployment. All processing runs in your browser with no data sent to external servers.

When to Use This Tool

•Generating gcp dataproc serverless batch configurations for new infrastructure deployments.
•Validating existing configurations against best practices before applying changes.
•Learning GCP service configuration patterns through interactive examples.
•Accelerating infrastructure-as-code development by producing correct JSON/YAML starting points.

Frequently Asked Questions

Does this tool connect to my GCP account?: No. This tool runs entirely in your browser and generates configuration JSON that you can copy and paste into your infrastructure-as-code templates, CLI commands, or cloud console. It never connects to any cloud account or sends data externally.
Are the generated configurations production-ready?: The tool produces syntactically valid configurations based on current GCP service specifications. Always review generated configs against your organization security policies and test in a non-production environment before deploying.

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Disclaimer: This tool runs entirely in your browser. No data is sent to our servers. Always verify outputs before using them in production. AWS, Azure, and GCP are trademarks of their respective owners.