Perhatikan bahwa Konektor Mainframe menggunakan Google Analytics untuk mengumpulkan data penggunaan. Hal ini membantu kami meningkatkan kualitas software dan memberikan
pengalaman pengguna yang lebih baik. Secara default, Google Analytics diaktifkan.
Namun, Anda dapat memilih untuk tidak ikut dengan mengonfigurasi variabel lingkungan saat
menjalankan Konektor Mainframe.
Penggunaan Google Analytics tunduk pada Persyaratan Layanan dan Kebijakan Privasi Google Analytics.
Dengan mendownload Mainframe Connector, Anda menyatakan bahwa Anda telah
membaca, memahami, dan menyetujui persyaratan dan ketentuan.
File main.tf dan vars.tf diekstrak dari file tar deployment.
Tinjau dan edit variabel dalam file vars.tf. Sebagian besar variabel sudah memiliki nilai default. Satu-satunya variabel wajib yang perlu
Anda tetapkan adalah project dan connector_service_account_email.
project: Project Google Cloud tempat Anda ingin
menginstal Mainframe Connector.
connector_service_account_email: Akun layanan yang memiliki semua izin untuk operasi yang ingin Anda lakukan menggunakan Mainframe Connector.
Anda juga dapat menetapkan konfigurasi jaringan menggunakan variabel connector_service_ingress dan connector_service_vpc_access.
Jalankan perintah terraform init dengan bucket dan awalan Cloud Storage sebagai argumen. Menggunakan bucket dan awalan Cloud Storage membantu Anda menyimpan status deployment di bucket. Anda juga dapat menggunakan kembali bucket dan awalan yang sama saat mengupgrade Mainframe Connector.
DEPLOYMENT_STATE_BUCKET: Nama bucket Cloud Storage.
BUCKET_PREFIX: Awalan yang ingin Anda gunakan di bucket Cloud Storage.
Buat file .tfvars untuk menentukan variabel yang ingin Anda gunakan Terraform selama deployment Konektor Mainframe.
Buka file .tfvars dan tentukan variabel berikut sebagai key-value pair.
instance_id: Menentukan instance_id untuk
memisahkan berbagai beban kerja jika Anda ingin memiliki beberapa instance
Mainframe Connector, atau menggunakan akun layanan yang berbeda.
project: Project tempat Anda ingin men-deploy
Mainframe Connector.
connector_service_ingress: Jenis traffic masuk.
additional_labels: Label tambahan jika Anda ingin menguji deployment.
connector_service_account_email: ID email akun layanan
Mainframe Connector.
Simpan perubahan Anda dan tutup file tersebut.
Men-deploy Mainframe Connector.
terraform apply -var-file=VARIABLE_FILE_NAME
Ganti VARIABLE_FILE_NAME dengan file variabel yang Anda buat di
langkah sebelumnya.
(Opsional) Untuk memeriksa apakah Mainframe Connector di-deploy dan berjalan,
buka halaman Cloud Run, lalu pilih tab Services. Anda
akan melihat deployment tercantum dalam tabel.
Untuk membatasi akses untuk tugas tertentu, Anda mungkin perlu men-deploy beberapa instance
Mainframe Connector. Anda dapat melakukannya dengan men-deploy
Mainframe Connector beberapa kali dengan variabel dan akun layanan
yang berbeda. Karena layanan jarak jauh Mainframe Connector didasarkan pada
Cloud Run, Anda hanya akan ditagih saat setiap layanan benar-benar berjalan.
Anda juga tidak perlu menyiapkan ketersediaan tinggi (HA) karena setiap instance sudah
di-load balance dan memiliki ketersediaan tinggi.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-03 UTC."],[],[],null,["# Deploy Mainframe Connector on Cloud Run\n\nThis page discusses how you can deploy Mainframe Connector on\nCloud Run as a remote service using [Terraform](https://www.terraform.io/).\nYou can then use the Mainframe Connector remote service to transcode,\nstore, and export mainframe data on Google Cloud. You can trigger this service\nfrom your mainframe to [perform remote transcoding](/mainframe-connector/docs/remote-transcoding),\nor as a [standalone instance that is integrated with an existing extract, transfer, and load (ETL) workflow](/mainframe-connector/docs/standalone-mode).\n\nYou can also deploy multiple instances of the Mainframe Connector\nremote service. For more information, see [Deploy multiple instances of the Mainframe Connector](#deploy-multiple-instances).\n\nTo deploy Mainframe Connector on Cloud Run using\n[Terraform](https://www.terraform.io/), use the following steps:\n\n1. Download the [Mainframe Connector deployment tar file]().\n\n ### Important\n\n Be aware that Mainframe Connector uses Google Analytics\n to collect usage data. This helps us improve the software and provide a\n better user experience. By default, Google Analytics is enabled.\n However, you can opt out by configuring an [environment variable](/mainframe-connector/docs/environment-variables#disable_analytics) when\n running Mainframe Connector.\n\n\n \u003cbr /\u003e\n\n\n The use of Google Analytics is subject to the Google Analytics\n [Terms of Service and Privacy Policy](https://www.google.com/analytics/terms).\n By downloading Mainframe Connector, you acknowledge that you have\n read, understood, and accepted the terms and conditions. \n [Download](https://storage.googleapis.com/mainframe-connector-release/latest/deployment.tar) Cancel\n2. Extract the files in the deployment tar file.\n\n ```\n tar -xvf ./deployment.tar\n ```\n\n The `main.tf` and `vars.tf` files are extracted from\n deployment tar file.\n3. Review and edit the variables in the `vars.tf` file. Most of the\n variables already have default values. The only mandatory variables you need\n to set are `project` and `connector_service_account_email`.\n\n - **`project`:** The Google Cloud project in which you want to install Mainframe Connector.\n - **`connector_service_account_email`:** The service account that has all the permissions for the operations you want to perform using Mainframe Connector.\n\n You can also set the network configuration using the\n `connector_service_ingress` and `connector_service_vpc_access`\n variables.\n4. Run the [`terraform init`](https://developer.hashicorp.com/terraform/cli/commands/init)\n command with a Cloud Storage *bucket* and *prefix* as\n arguments. Using a Cloud Storage bucket and prefix helps you save the\n deployment state in the bucket. You can also reuse the same bucket and prefix\n when you upgrade Mainframe Connector.\n\n ```\n terraform init \\\n -backend-config bucket=DEPLOYMENT_STATE_BUCKET \\\n -backend-config prefix=BUCKET_PREFIX\n ```\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003eDEPLOYMENT_STATE_BUCKET\u003c/var\u003e: The name of the Cloud Storage bucket.\n - \u003cvar translate=\"no\"\u003eBUCKET_PREFIX\u003c/var\u003e: The prefix that you want to use in the Cloud Storage bucket.\n5. Create a `.tfvars` file to define variables that you want\n Terraform to use during the Mainframe Connector deployment.\n\n6. Open the `.tfvars` file and define the following variables as\n key-value pairs.\n\n - **`instance_id`:** Define an `instance_id` to separate different workloads when you want to have multiple instances of Mainframe Connector, or to use different service accounts.\n - **`project`:** The project in which you want to deploy Mainframe Connector.\n - **`connector_service_ingress`:** The ingress type.\n - **`additional_labels`:** Additional labels if you want to test the deployment.\n - **`connector_service_account_email`:** The service account email ID of Mainframe Connector.\n\n Save your changes and close the file.\n7. Deploy Mainframe Connector.\n\n ```\n terraform apply -var-file=VARIABLE_FILE_NAME\n ```\n\n Replace \u003cvar translate=\"no\"\u003eVARIABLE_FILE_NAME\u003c/var\u003e with the variables file you created in\n the previous step.\n8. (Optional) To check if Mainframe Connector is deployed and running,\n go to the Cloud Run page, and select the **Services** tab. You\n should see your deployment listed in the table.\n\n [Go to Cloud Run](https://console.cloud.google.com/run?enableapi=true)\n\nDeploy multiple instances of the Mainframe Connector\n----------------------------------------------------\n\nTo limit access for specific jobs, you might need to deploy multiple instances\nof the Mainframe Connector. You can do this by deploying the\nMainframe Connector multiple times with different variables and service\naccounts. Since the Mainframe Connector remote service is based on\nCloud Run, you will only be billed when each service is actually running.\nYou also don't need to set up high availability (HA) as each instance is already\nload balanced and highly available.\n\nWhat's next\n-----------\n\n- [Transcode mainframe data remotely on Google Cloud](/mainframe-connector/docs/remote-transcoding)\n- [Transcode mainframe data moved to Google Cloud using a virtual tape library](/mainframe-connector/docs/vtl-transcoding)\n- [Run Mainframe Connector as a standalone job](/mainframe-connector/docs/standalone-mode)"]]
