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Copy file name to clipboardExpand all lines: content/integrate/redis-data-integration/data-pipelines/prepare-dbs/spanner.md
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@@ -60,9 +60,9 @@ for more details, including additional configuration options and dialect-specifi
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## 3. Create a service account
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To allow RDI to access the Spanner instance, you'll need to create a service account with the
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appropriate permissions. This service account will then be provided to RDI as a secret for
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authentication.
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To allow RDI to access the Spanner instance, you'll need to create a service account with the
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appropriate permissions. By default, RDI uses Google Cloud Workload Identity authentication. In this case RDI will assume the [service account is assigned to the GKE cluster](https://cloud.google.com/kubernetes-engine/docs/how-to/workload-identity#enable_on_clusters_and_node_pools). Alternatively, you can provide the
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service account credentials as a Kubernetes secret (see step 4 for details).
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1. Create the service account
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--project=YOUR_PROJECT_ID
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```
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## 4. Set up secrets for Kubernetes deployment
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### Authentication methods
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Before deploying the RDI pipeline, you need to configure the necessary secrets for both the source
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and target databases. Instructions forsetting up the target database secrets are availablein the
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RDI supports two authentication methods for accessing Spanner:
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1. **Workload Identity (default)**: The service account is assigned to the GKE cluster, and RDI
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automatically uses the cluster's identity to authenticate. This is the recommended approach
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as it's more secure and doesn't require managing credential files.
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2. **Service account credentials file**: You provide the service account key file as a Kubernetes
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secret. This method requires setting `use_credentials_file: true` in your RDI configuration.
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## 4. Set up secrets for Kubernetes deployment (optional)
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Before deploying the RDI pipeline, you need to configure the necessary secrets for the target
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database. Instructions for setting up the target database secrets are available in the
RDI’s mission is to help Redis customers sync Redis Enterprise with live data from their slow disk-based databases to:
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- Meet the required speed and scale of read queries and provide an excellent and predictable user experience.
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- Save resources and time when building pipelines and coding data transformations.
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- Reduce the total cost of ownership by saving money on expensive database read replicas.
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RDI keeps the Redis cache up to date with changes in the primary database, using a [_Change Data Capture (CDC)_](https://en.wikipedia.org/wiki/Change_data_capture) mechanism.
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It also lets you _transform_ the data from relational tables into convenient and fast data structures that match your app's requirements. You specify the transformations using a configuration system, so no coding is required.
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## What's New in 1.14.1
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- Support for Google Cloud Workload Identity authentication when a service account is assigned to the GKE cluster
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- Fixed RDI API job validation that was incorrectly failing when schemas are not explicitly specified in source configuration, even though the configuration was valid
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## Limitations
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RDI can write data to a Redis Active-Active database. However, it doesn't support writing data to two or more Active-Active replicas. Writing data from RDI to several Active-Active replicas could easily harm data integrity as RDI is not synchronous with the source database commits.
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