[WIP]Feature/postgres integration

[kaikaila]

Summary

This PR adds full PostgreSQL (pgx driver) support to Kubeflow Pipelines backend, enabling users to choose between MySQL and PostgreSQL as the metadata database. The implementation introduces a clean dialect abstraction layer and includes a major query optimization that benefits both database backends.

Key achievements
✅ Complete PostgreSQL integration for API Server and Cache Server, addressing #7512, #9813
✅ All CI tests passing (MySQL + PostgreSQL).
✅ Significant performance improvement for ListRuns queries. This PR is expected to address the root causes behind #10778, #10230, #9780, #9701
✅ Zero breaking changes - backward compatible with existing MySQL deployments

What Changed

1. Storage Layer Refactoring - Dialect Abstraction ([backend/src/apiserver/common/sql/dialect]

• Problem
  SQL syntax was tightly coupled to MySQL.

• Solution
  Introduced a DBDialect interface that encapsulates database-specific behavior
  Identifier quoting (MySQL backticks vs PostgreSQL double quotes)
  Placeholder styles (? vs $1, $2, ...)
  Aggregation functions (GROUP_CONCAT vs string_agg)
  Concatenation syntax (CONCAT() vs ||)

• Files

  • Core dialect implementation → backend/src/apiserver/common/sql/dialect/dialect.go
  • Dialect-aware utility functions → backend/src/apiserver/storage/sql_dialect_util.go
  • Reusable filter builders with proper quoting → backend/src/apiserver/storage/list_filters.go

All storage layer code now uses

q := s.dbDialect.QuoteIdentifier
qb := s.dbDialect.QueryBuilder()

This ensures queries work correctly across MySQL, PostgreSQL, and SQLite (for tests).

2. ListRuns Query Performance Optimization

• Problem
  The original ListRuns query called addMetricsResourceReferencesAndTasks which performed a 3-layer LEFT JOIN with GROUP BY on all columns, including LONGTEXT fields like PipelineSpecManifest WorkflowSpecManifest etc. This caused slow response times for large datasets.
• Solution
  Layers 1-3: LEFT JOIN only on PrimaryKeyUUID + aggregated columns (refs, tasks, metrics)
  Final layer: INNER JOIN back to run_details to fetch LONGTEXT columns
• Performance impact
  Eliminates GROUP BY on LONGTEXT columns entirely. Expected substantial performance improvements for deployments with large pipeline specifications, though formal load testing has not yet been conducted.

3. Deployment Configurations

• Production-ready PostgreSQL kustomization → manifests/kustomize/env/platform-agnostic-postgresql/
• Local development setup → manifests/kustomize/env/dev-kind-postgresql/
• PostgreSQL StatefulSet → manifests/kustomize/third-party/postgresql/

Configuration is symmetric to existing MySQL manifests for consistency.

4. CI Manifest Overlays

Created CI-specific Kustomize overlays to ensure tests use locally built images from the Kind registry instead of pulling official images from ghcr.io:

• Add PostgreSQL CI overlay .github/resources/manifests/standalone/postgresql/
• Added kfp-cache-server image override to .github/resources/manifests/standalone/base/kustomization.yaml

5. Added 2 PostgreSQL-specific CI workflows

• V2 API and integration tests (cache enabled/disabled matrix) → api-server-test-Postgres.yml
• V1 integration tests → integration-tests-v1-postgres.yml

PostgreSQL tests cover the core cache enabled/disabled matrix.

6. Local development support

• make dev-kind-cluster-pg - Provision Kind cluster with PostgreSQL
• Updated README for PostgreSQL setup and debugging, achieving parity with MySQL documentation.

Testing

Unit Tests

23 test files modified/added
New test coverage: dialect_test.go, list_filters_test.go, sql_dialect_util_test.go
All existing tests updated to use dialect abstraction

Integration Tests

✅ V1 API integration tests (PostgreSQL)
✅ V2 API integration tests (PostgreSQL, cache enabled/disabled)
✅ Existing MySQL tests remain green

Migration Guide

• For new deployments:
  kubectl apply -k manifests/kustomize/env/platform-agnostic-postgresql
• For existing MySQL deployments:
  No action required. This PR is fully backward compatible.
• For local development, to set up the kind cluster with Postgres
  make -C backend dev-kind-cluster-pg

This PR continues from #12063.

[google-oss-prow]

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[google-oss-prow]

Hi @kaikaila. Thanks for your PR.

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[github-actions]

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[kaikaila]

Currently, both MySQL and PGX setups use the DB superuser for all KFP operations, which is why client_manager.go contains a “create database if not exist” step here.

From a security standpoint, would it be preferable to:

1. Move DB creation out of the client manager and into the deployment/init phase (i.e. add a manifests/kustomize/third-party/postgresql/base/pg-init-configmap.yaml) and
2. Introduce a dedicated restricted user for KFP components, limited to the mlpipeline database?

If the team agrees, I can propose a follow-up PR to refactor accordingly.

[HumairAK]

I'm fine with this, I don't think it's great that KFP tries to create a database (or a bucket frankly)

fyi @mprahl / @droctothorpe

[kaikaila]

Thanks, @HumairAK — totally agree on the security point.
Since this PR is already getting quite heavy, would you be okay if I leave the user permission changes for a separate follow-up PR?

[HumairAK]

yes that is fine

[kaikaila]

Question about the PostgreSQL test workflow organization

Current situation

The V2 integration tests for PostgreSQL logically belong in a "PostgreSQL counterpart" to legacy-v2-api-integration-tests.yml
However, I didn't want to create a new workflow with "legacy" in the name from day one.
As a temporary solution, I merged them into api-server-test-Postgres.yml
This causes asymmetry with api-server-tests.yml and the workflow has mixed responsibilities.

Question: What's the recommended workflow organization for PostgreSQL tests?

Should I:

• a. Create legacy-v2-api-integration-tests-postgres.yml for consistency (even though it's new)?
• b. Keep current structure and accept the asymmetry?
• c. Refactor both MySQL and PostgreSQL to a unified structure?

Would love guidance on the long-term vision for test workflow organization, especially from @nsingla