support lakefs solution docs

docs/en/solutions/How_to_Use_lakeFS.md

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+---
+kind:
+   - Solution
+products:
+  - Alauda Application Services
+ProductsVersion:
+   - 4.x
+id: KB251000010
+---
+
+# lakeFS Data Version Control Solution Guide
+
+## Background
+
+### The Challenge
+
+Modern data lakes face significant challenges in managing data versioning, reproducibility, and collaboration. Traditional approaches often lead to:
+
+- **Data Quality Issues**: Difficulty tracking changes and rolling back problematic data updates
+- **Reproducibility Problems**: Inability to recreate specific data states for analysis or debugging
+- **Collaboration Conflicts**: Multiple teams working on the same data without proper isolation
+- **Testing Complexity**: Challenges in testing data transformations before applying to production
+
+### The Solution
+
+lakeFS provides Git-like version control for data lakes, enabling:
+
+- **Branching and Merging**: Isolate changes in branches and merge them safely
+- **Data Versioning**: Track changes to data with commit-like semantics
+- **Reproducible Analytics**: Reference specific data versions for consistent results
+- **CI/CD for Data**: Implement testing and validation workflows for data pipelines
+
+## Environment Information
+
+Applicable Versions: >=ACP 4.1.0, lakeFS: >=1.70.1
+
+## Quick Reference
+
+### Key Concepts
+- **Repository**: A collection of branches, tags, and commits that track changes to data
+- **Branch**: An isolated line of development within a repository
+- **Commit**: A snapshot of the repository at a specific point in time
+- **Merge**: Combining changes from one branch into another
+
+### Common Use Cases
+
+| Scenario | Recommended Approach | Section Reference |
+|----------|---------------------|------------------|
+| **Data Versioning** | Create repositories and commit changes | [Basic Operations](#basic-operations) |
+| **Collaborative Development** | Use feature branches for isolated work | [Branching Strategy](#branching-strategy) |
+| **Data Quality Validation** | Implement pre-commit hooks and testing | [Data Validation](#data-validation) |
+| **Production Deployment** | Merge validated changes to main branch | [Production Workflows](#production-workflows) |
+
+## Prerequisites
+
+Before implementing lakeFS, ensure you have:
+
+- ACP v4.1.0 or later
+- PostgreSQL instance for metadata storage
+- Object storage backend (Ceph RGW recommended or MinIO)
+- Basic understanding of Git workflows and data lake concepts
+
+### Storage Requirements
+
+- **PostgreSQL**: Minimum 10GB storage for metadata
+- **Object Storage**: Sufficient capacity for your data assets
+- **Backup Strategy**: Regular backups of PostgreSQL database
+
+## Installation Guide
+
+### Chart Upload
+
+ Download the lakeFS chart from the Marketplace in the Alauda Customer Portal and upload the lakeFS chart to your ACP catalog:
+
+```bash
+CHART=lakefs.ALL.1.7.9.tgz
+ADDR="https://your-acp-domain.com"
+USER="[email protected]"
+PASS="your-password"
+
+violet push $CHART \
+--platform-address "$ADDR" \
+--platform-username "$USER" \
+--platform-password "$PASS"
+```
+
+### Backend Storage Configuration
+
+#### Recommended: Ceph RGW Setup
+
+1. Deploy Ceph storage system following the [Ceph installation guide](https://docs.alauda.io/container_platform/4.1/storage/storagesystem_ceph/installation/create_service_stand.html)
+
+2. Create Ceph Object Store User:
+
+```yaml
+apiVersion: ceph.rook.io/v1
+kind: CephObjectStoreUser
+metadata:
+  name: lakefs-user
+  namespace: rook-ceph
+spec:
+  store: object-pool
+  displayName: object-pool
+  quotas:
+    maxBuckets: 100
+    maxSize: -1
+    maxObjects: -1
+  capabilities:
+    user: "*"
+    bucket: "*"
+```
+
+3. Retrieve access credentials:
+
+```bash
+user_secret=$(kubectl -n rook-ceph get cephobjectstoreuser lakefs-user -o jsonpath='{.status.info.secretName}')
+ACCESS_KEY=$(kubectl -n rook-ceph get secret $user_secret -o jsonpath='{.data.AccessKey}' | base64 --decode)
+SECRET_KEY=$(kubectl -n rook-ceph get secret $user_secret -o jsonpath='{.data.SecretKey}' | base64 --decode)
+```
+
+#### Alternative: MinIO Setup
+
+Deploy MinIO following the [MinIO installation guide](https://docs.alauda.io/container_platform/4.1/storage/storagesystem_minio/installation.html)
+
+### PostgreSQL Database Setup
+
+1. Deploy PostgreSQL following the [PostgreSQL installation guide](https://docs.alauda.io/postgresql/4.1/installation.html)
+
+2. Create database for lakeFS:
+
+```sql
+CREATE DATABASE lakefs;
+```
+
+### lakeFS Deployment
+
+1. Access ACP web console and navigate to "Applications" → "Create" → "Create from Catalog"
+
+2. Select the lakeFS chart
+
+3. Configure deployment values:
+
+```yaml
+image:
+  repository: your-registry-domain.com/3rdparty/treeverse/lakefs
+
+lakefsConfig: |
+  database:
+    type: postgres
+  blockstore:
+    type: s3
+    s3:
+      force_path_style: true
+      endpoint: "http://rook-ceph-rgw-object-pool.rook-ceph.svc:7480"
+      discover_bucket_region: false
+      credentials:
+        access_key_id: QFKEJGDSGWFG44SL495W
+        secret_access_key: 67yy3SE5Epu2RC9EADlFIxedPcnO9AAglX8tYJyy
+
+secrets:
+  databaseConnectionString: "postgres://postgres:password@postgres-service:5432/lakefs"
+
+service:
+  type: NodePort
+
+livenessProbe:
+  failureThreshold: 30
+  periodSeconds: 10
+  timeoutSeconds: 2
+```
+
+4. Deploy and verify the application reaches "Ready" status
+
+## Configuration Guide
+
+### Accessing lakeFS
+
+1. Retrieve the NodePort service endpoint:
+
+```bash
+kubectl get svc lakefs-service -n your-namespace
+```
+
+2. Access the lakeFS web UI through the NodePort
+
+3. Download initial credentials from the web UI
+
+### Getting Started with lakeFS
+
+For detailed usage instructions, workflows, and advanced features, please refer to the official [lakeFS documentation](https://docs.lakefs.io/).
+
+The official documentation covers:
+- Basic operations (branching, committing, merging)
+- Advanced features (hooks, retention policies, cross-repository operations)
+- Integration with data tools (Spark, Airflow, dbt, etc.)
+- API reference and CLI usage
+- Best practices and use cases
+
+## Troubleshooting
+
+### Common Issues
+
+#### Authentication Problems
+
+**Symptoms**: Unable to access lakeFS UI or API
+
+**Solutions**:
+- Verify credentials are correctly set in deployment
+- Check PostgreSQL connection string format
+- Validate object storage credentials
+
+#### Performance Issues
+
+**Symptoms**: Slow operations or timeouts
+
+**Solutions**:
+- Monitor PostgreSQL performance
+- Check object storage latency
+- Review network connectivity between components
+
+### Diagnostic Commands
+
+Check lakeFS health:
+
+```bash
+curl http://lakefs-service:8000/health
+```
+
+Verify PostgreSQL connection:
+
+```bash
+kubectl exec -it lakefs-pod -- pg_isready -h postgres-service -p 5432
+```
+
+## Best Practices
+
+### Repository Structure
+
+- Organize data by domain or team
+- Use descriptive branch names (feature/, bugfix/, hotfix/)
+- Implement clear commit message conventions
+
+### Security Considerations
+
+- Regularly rotate access credentials
+- Implement principle of least privilege for repository access
+- Enable audit logging for sensitive operations
+
+### Backup Strategy
+
+- Regular backups of PostgreSQL metadata database
+- Object storage redundancy through backend configuration
+- Test restoration procedures periodically
+
+## Reference
+
+### Configuration Parameters
+
+**lakeFS Deployment:**
+- `databaseConnectionString`: PostgreSQL connection string
+- `blockstore.type`: Storage backend type (s3, gs, azure)
+- `blockstore.s3.endpoint`: Object storage endpoint
+- `blockstore.s3.credentials`: Access credentials
+
+### Useful Links
+
+- [lakeFS Documentation](https://docs.lakefs.io/) - Comprehensive usage guide and API reference
+- [PostgreSQL Operator Documentation](https://docs.alauda.io/postgresql/4.1/functions/index.html)
+- [Ceph Object Storage Guide](https://docs.alauda.io/container_platform/4.1/storage/storagesystem_ceph/how_to/create_object_user.html)
+
+## Summary
+
+This guide provides comprehensive instructions for implementing lakeFS on Alauda Container Platform. The solution delivers Git-like version control for data lakes, enabling:
+
+- **Reproducible Data Analytics**: Track and reference specific data versions
+- **Collaborative Development**: Isolate changes with branching and merging
+- **Data Quality Assurance**: Implement validation workflows
+- **Production Reliability**: Controlled promotion of data changes
+
+By following these practices, organizations can significantly improve their data management capabilities while maintaining the flexibility and scalability of modern data lake architectures.